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Validity – Types, Examples and Guide

Table of Contents

Validity is a fundamental concept in research, referring to the extent to which a test, measurement, or study accurately reflects or assesses the specific concept that the researcher is attempting to measure. Ensuring validity is crucial as it determines the trustworthiness and credibility of the research findings.

Research Validity

Research validity pertains to the accuracy and truthfulness of the research. It examines whether the research truly measures what it claims to measure. Without validity, research results can be misleading or erroneous, leading to incorrect conclusions and potentially flawed applications.

How to Ensure Validity in Research

Ensuring validity in research involves several strategies:

• Clear Operational Definitions : Define variables clearly and precisely.
• Use of Reliable Instruments : Employ measurement tools that have been tested for reliability.
• Pilot Testing : Conduct preliminary studies to refine the research design and instruments.
• Triangulation : Use multiple methods or sources to cross-verify results.
• Control Variables : Control extraneous variables that might influence the outcomes.

Types of Validity

Validity is categorized into several types, each addressing different aspects of measurement accuracy.

Internal Validity

Internal validity refers to the degree to which the results of a study can be attributed to the treatments or interventions rather than other factors. It is about ensuring that the study is free from confounding variables that could affect the outcome.

External Validity

External validity concerns the extent to which the research findings can be generalized to other settings, populations, or times. High external validity means the results are applicable beyond the specific context of the study.

Construct Validity

Construct validity evaluates whether a test or instrument measures the theoretical construct it is intended to measure. It involves ensuring that the test is truly assessing the concept it claims to represent.

Content Validity

Content validity examines whether a test covers the entire range of the concept being measured. It ensures that the test items represent all facets of the concept.

Criterion Validity

Criterion validity assesses how well one measure predicts an outcome based on another measure. It is divided into two types:

• Predictive Validity : How well a test predicts future performance.
• Concurrent Validity : How well a test correlates with a currently existing measure.

Face Validity

Face validity refers to the extent to which a test appears to measure what it is supposed to measure, based on superficial inspection. While it is the least scientific measure of validity, it is important for ensuring that stakeholders believe in the test’s relevance.

Importance of Validity

Validity is crucial because it directly affects the credibility of research findings. Valid results ensure that conclusions drawn from research are accurate and can be trusted. This, in turn, influences the decisions and policies based on the research.

Examples of Validity

• Internal Validity : A randomized controlled trial (RCT) where the random assignment of participants helps eliminate biases.
• External Validity : A study on educational interventions that can be applied to different schools across various regions.
• Construct Validity : A psychological test that accurately measures depression levels.
• Content Validity : An exam that covers all topics taught in a course.
• Criterion Validity : A job performance test that predicts future job success.

Where to Write About Validity in A Thesis

In a thesis, the methodology section should include discussions about validity. Here, you explain how you ensured the validity of your research instruments and design. Additionally, you may discuss validity in the results section, interpreting how the validity of your measurements affects your findings.

Applications of Validity

Validity has wide applications across various fields:

• Education : Ensuring assessments accurately measure student learning.
• Psychology : Developing tests that correctly diagnose mental health conditions.
• Market Research : Creating surveys that accurately capture consumer preferences.

Limitations of Validity

While ensuring validity is essential, it has its limitations:

• Complexity : Achieving high validity can be complex and resource-intensive.
• Context-Specific : Some validity types may not be universally applicable across all contexts.
• Subjectivity : Certain types of validity, like face validity, involve subjective judgments.

By understanding and addressing these aspects of validity, researchers can enhance the quality and impact of their studies, leading to more reliable and actionable results.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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• The 4 Types of Validity in Research | Definitions & Examples

The 4 Types of Validity in Research | Definitions & Examples

Published on September 6, 2019 by Fiona Middleton . Revised on June 22, 2023.

Validity tells you how accurately a method measures something. If a method measures what it claims to measure, and the results closely correspond to real-world values, then it can be considered valid. There are four main types of validity:

• Construct validity : Does the test measure the concept that it’s intended to measure?
• Content validity : Is the test fully representative of what it aims to measure?
• Face validity : Does the content of the test appear to be suitable to its aims?
• Criterion validity : Do the results accurately measure the concrete outcome they are designed to measure?

In quantitative research , you have to consider the reliability and validity of your methods and measurements.

Note that this article deals with types of test validity, which determine the accuracy of the actual components of a measure. If you are doing experimental research, you also need to consider internal and external validity , which deal with the experimental design and the generalizability of results.

Table of contents

Construct validity, content validity, face validity, criterion validity, other interesting articles, frequently asked questions about types of validity.

Construct validity evaluates whether a measurement tool really represents the thing we are interested in measuring. It’s central to establishing the overall validity of a method.

What is a construct?

A construct refers to a concept or characteristic that can’t be directly observed, but can be measured by observing other indicators that are associated with it.

Constructs can be characteristics of individuals, such as intelligence, obesity, job satisfaction, or depression; they can also be broader concepts applied to organizations or social groups, such as gender equality, corporate social responsibility, or freedom of speech.

There is no objective, observable entity called “depression” that we can measure directly. But based on existing psychological research and theory, we can measure depression based on a collection of symptoms and indicators, such as low self-confidence and low energy levels.

What is construct validity?

Construct validity is about ensuring that the method of measurement matches the construct you want to measure. If you develop a questionnaire to diagnose depression, you need to know: does the questionnaire really measure the construct of depression? Or is it actually measuring the respondent’s mood, self-esteem, or some other construct?

To achieve construct validity, you have to ensure that your indicators and measurements are carefully developed based on relevant existing knowledge. The questionnaire must include only relevant questions that measure known indicators of depression.

The other types of validity described below can all be considered as forms of evidence for construct validity.

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Content validity assesses whether a test is representative of all aspects of the construct.

To produce valid results, the content of a test, survey or measurement method must cover all relevant parts of the subject it aims to measure. If some aspects are missing from the measurement (or if irrelevant aspects are included), the validity is threatened and the research is likely suffering from omitted variable bias .

A mathematics teacher develops an end-of-semester algebra test for her class. The test should cover every form of algebra that was taught in the class. If some types of algebra are left out, then the results may not be an accurate indication of students’ understanding of the subject. Similarly, if she includes questions that are not related to algebra, the results are no longer a valid measure of algebra knowledge.

Face validity considers how suitable the content of a test seems to be on the surface. It’s similar to content validity, but face validity is a more informal and subjective assessment.

You create a survey to measure the regularity of people’s dietary habits. You review the survey items, which ask questions about every meal of the day and snacks eaten in between for every day of the week. On its surface, the survey seems like a good representation of what you want to test, so you consider it to have high face validity.

As face validity is a subjective measure, it’s often considered the weakest form of validity. However, it can be useful in the initial stages of developing a method.

Criterion validity evaluates how well a test can predict a concrete outcome, or how well the results of your test approximate the results of another test.

What is a criterion variable?

A criterion variable is an established and effective measurement that is widely considered valid, sometimes referred to as a “gold standard” measurement. Criterion variables can be very difficult to find.

What is criterion validity?

To evaluate criterion validity, you calculate the correlation between the results of your measurement and the results of the criterion measurement. If there is a high correlation, this gives a good indication that your test is measuring what it intends to measure.

A university professor creates a new test to measure applicants’ English writing ability. To assess how well the test really does measure students’ writing ability, she finds an existing test that is considered a valid measurement of English writing ability, and compares the results when the same group of students take both tests. If the outcomes are very similar, the new test has high criterion validity.

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If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

Face validity and content validity are similar in that they both evaluate how suitable the content of a test is. The difference is that face validity is subjective, and assesses content at surface level.

When a test has strong face validity, anyone would agree that the test’s questions appear to measure what they are intended to measure.

For example, looking at a 4th grade math test consisting of problems in which students have to add and multiply, most people would agree that it has strong face validity (i.e., it looks like a math test).

On the other hand, content validity evaluates how well a test represents all the aspects of a topic. Assessing content validity is more systematic and relies on expert evaluation. of each question, analyzing whether each one covers the aspects that the test was designed to cover.

A 4th grade math test would have high content validity if it covered all the skills taught in that grade. Experts(in this case, math teachers), would have to evaluate the content validity by comparing the test to the learning objectives.

Criterion validity evaluates how well a test measures the outcome it was designed to measure. An outcome can be, for example, the onset of a disease.

Criterion validity consists of two subtypes depending on the time at which the two measures (the criterion and your test) are obtained:

• Concurrent validity is a validation strategy where the the scores of a test and the criterion are obtained at the same time .
• Predictive validity is a validation strategy where the criterion variables are measured after the scores of the test.

Convergent validity and discriminant validity are both subtypes of construct validity . Together, they help you evaluate whether a test measures the concept it was designed to measure.

• Convergent validity indicates whether a test that is designed to measure a particular construct correlates with other tests that assess the same or similar construct.
• Discriminant validity indicates whether two tests that should not be highly related to each other are indeed not related. This type of validity is also called divergent validity .

You need to assess both in order to demonstrate construct validity. Neither one alone is sufficient for establishing construct validity.

The purpose of theory-testing mode is to find evidence in order to disprove, refine, or support a theory. As such, generalizability is not the aim of theory-testing mode.

Due to this, the priority of researchers in theory-testing mode is to eliminate alternative causes for relationships between variables . In other words, they prioritize internal validity over external validity , including ecological validity .

It’s often best to ask a variety of people to review your measurements. You can ask experts, such as other researchers, or laypeople, such as potential participants, to judge the face validity of tests.

While experts have a deep understanding of research methods , the people you’re studying can provide you with valuable insights you may have missed otherwise.

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Market Research: What It Is and How to Do It

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In other words, it’s the process of understanding who your business is targeting so you can better position your marketing strategy.

In this guide, you’ll learn:

• The role of market research in a marketing strategy
• When to conduct market research

Types of market research

• Market research methods and their benefits
• How to conduct market research (example included)
• Market research tools and resources

What is the role of market research in a marketing strategy?

A marketing strategy is a business’s overall game plan for reaching consumers and turning them into customers.

The key word in the above definition is “game plan”. Entering a market with a product is like starting a new game. Since you’re new to the game, you don’t know the rules, and you don’t know who you’re playing against.

This is exactly where market research comes in . Market research allows you to discover the rules of the marketing game by understanding your target audience. Moreover, it allows you to understand who your opponent is by assessing the strengths and weaknesses of your competition.

Research is what marketing pros do to plan their moves, and outperform their competition.  It’s also what marketing pros use to identify the strengths and weaknesses of their own marketing strategy .

But is market research the ultimate business oracle? Unfortunately no. Even companies that specialize in market research admit it - here’s a quote from one of them :

(…) it cannot be assumed that market research is an exact science, as it would be unrealistic and unreasonable to expect market researchers to predict the precise demand for a new concept, given that there are numerous variables that can impact demand outside of the market researchers’ remit.

That’s why market research with all of its significance is “only” a part of marketing, and it’s “only” an experiment.  It’s up to you whether you will conduct your experiment, and when you will end it.

For example, Crystal Pepsi seemed very promising in the market research phase, yet it failed when released onto the market (a similar thing happened to New Coke). Xerox’s idea for a commercial photocopier was a no-go in the eyes of research analysts; Xerox did it anyway, and the rest is history.

When should you conduct market research?

Paul N. Hauge and Peter Jackson in their book “Do Your Own Market Research” point to three specific situations when market research is really useful:

• Setting goals . Knowing things like the size of the market, or defining your potential customers can help you set your sales goals.
• Problem-solving . Low sales? Low profitability? Market research will help you understand whether your problems are internal, like a low-quality product, or external, like aggressive competition.
• Supporting company growth.  Understanding how and why consumers decide on products will help you decide what products to introduce to the market.

Another answer to the “when” is the importance of the decision that you need to make. The more important the marketing issue you’re tackling, the more market research comes in handy.

For example, launching a new car on the market is quite a big event, right? So maybe Ford could have avoided losing 350 million dollars with the Ford Edsel if they had done their research properly. I mean, with the right methods in place it shouldn’t be that hard to predict that consumers will deem the car overpriced and ugly.

That said, market research doesn’t always have to be a large, complex project. The relatively new trend of agile market research  allows you to research the market regularly and in a cost-effective way. This is where you employ bite-size, iterative, and evolutionary methods to react to fast-changing circumstances and adapt to unknown market territories.

Furthermore, if you’re working in startup conditions, especially if you’re developing an innovative product, you may be interested in customer development . In this methodology market research is at its “agilest” and it’s tightly woven into the product development process.

Take Ahrefs for example. We stick to agile market research hacks anyone can use. As you will see later in the article, we use simple (but effective!) stuff like social media polls, crowdsourcing, in-house competitive analysis, or just tracking the pricing of our competitors.

Case in point, just recently we asked our fellow marketers on Twitter how they go about researching the market. It seems that market research comes in all shapes and sizes:

Have you ever performed “market research?“ What was it for? — Tim Soulo (@timsoulo) May 3, 2021

Just because somebody does market research in a certain way doesn’t mean that you need to copy that. You should know your options, and they start with the different types of market research.

Primary research

Whenever the research is done by you or on your behalf, and you need to create the data to solve a given problem, that is called primary market research.

Examples:  Focus groups, interviews, surveys (more on those later in the article).

Key benefits: It’s specific to your brand and products or services, and you can control the quality of the data.

Secondary research

Whenever you’re using already existing data, such as that put together by other businesses and organizations, you’re doing secondary market research.

Examples: Second-party and third-party sources like articles, whitepapers, reports, industry statistics, already collected internal data.

Key benefits: Get a macro perspective of your marketplace, as secondary research includes other players in the market, and most probably utilizes a bigger set of data than your primary sources.

Primary research vs. secondary research

Primary and secondary market research are different but by no means opposite. It’s actually recommended to use both.

While primary sources will give you a focused, micro perspective of your business, secondary research will tell you how other businesses are doing and how your research findings compare to bigger research sample sizes. 

Market research subtypes

A bit more theory for all you marketing geeks out there. Professional market researchers distinguish between the following primary and secondary market research subtypes:

• Qualitative research.  Think interviews, open-ended questions, results expressed in words rather than numbers and graphs. This type of research is used to understand underlying reasons, opinions, and motivations.
• Quantitative research. Think surveys, polls, usually closed-ended questions, results expressed in numbers and statistics. This type of research is used to test or confirm hypotheses or assumptions by quantifying defined variables (such as opinions or behaviours) and generalizing results from larger data samples.

Overview of market research methods

Let’s go over some popular market research methods you can use yourself and/or outsource.

Internal data analysis

The data you’ve already collected in your company is an invaluable secondary research data source. The more time you’re in the business, the more data you have on your hands.

The best thing about your internal data is that it’s been put into practice in real-life market conditions, so you just need to find the patterns and draw conclusions.

Here are some internal data sources you can leverage :

• Website data (like Google Analytics)
• Past campaigns performance data
• Internal interviews with employees

Interviews allow for face-to-face discussions and are great for exploratory qualitative research.

In unstructured interviews, you have an informal, free-flowing conversation on a given set of topics.

In structured interviews, you prepare a detailed, rigorous interview protocol where you list every question you want to ask and you can’t divert from them.

You can also choose the “middle way” with semi-structured interviews which revolve around predefined themes or questions, but allow for open-ended discussion.

A word of advice here would be to always remain neutral and unbiased, even during unstructured interviews. Also, it’s helpful to perform a pilot test of the interview to quickly spot some defects of your protocol.

Recording the interview may influence the answers, so use it wisely.

Focus groups

Focus groups are where 5 to 10 people with common characteristics take part in an interactive discussion with a moderator. They’re used to learn how a particular group thinks about a given issue or to provide feedback on a product.

Now, you might know that Steve Jobs famously hated focus groups. He’s on record saying:

It’s really hard to design products by focus groups. A lot of times, people don’t know what they want until you show it to them.

If you’re trying to create a leapfrog product like the iPhone, there’s probably some validity to this statement. But most of us aren’t wrestling with that level of ambition. We just want to know if customers will like a proposed new feature or not. For this, focus groups are super useful.

Surveys involve polling your audience. They’re usually performed online for customer satisfaction and loyalty research, and are one of the most popular and cost-effective market research methods.

Some of the tried and tested use cases of online surveys  are:

• Product feature desirability
• User satisfaction feedback
• Quantitative analysis of certain issue occurrences
• Identifying friction points in your customer journey
• Discovering the reasons to convert to or cancel your service
• During product onboarding to create a customer profile (and for marketing automation)
• Opinion about a recently made change

An interesting example of surveying the market is crowdsourcing . That’s what Ahrefs does to understand what features to build, how important they are, and what customers expect from them.

What’s unique about crowdsourcing is that it allows the users to add their own ideas, and upvote or comment on existing ideas rather than answer predetermined questions, so this method leaves less room for marketing myopia. You improve your business, and the users get a better product—everybody wins.

How we crowdsource ideas at Ahrefs

Social media is another great place to survey the marketplace.

How many of you have disavowed links in GSC this year? — Tim Soulo (@timsoulo) October 8, 2020

Market segmentation

Market segmentation is the practice of categorizing a market into homogeneous groups based on specific criteria, also called segmentation variables (like age, sex, company size, country, etc.).

If you think you’re building a product for everyone, think again. Not everyone will want to buy from you.

Smart companies pick their target audience carefully. They pinpoint groups of people or organizations that could be valuable customers for the business. That way they also discover their non-ideal customers and develop a plan to attract customer segments gradually. 

Ever wondered why Procter and Gamble creates so many, often competing, brands? You guessed it: market segmentation. P&G simply divides and conquers. Different people have different needs, so they need different products (and possibly brands).

Competitive analysis

Another powerful, yet often overlooked, market research method is the process of understanding one’s market environment. Seriously, if there’s only one thing you could do to learn what works and what doesn’t in your market, you should do a competitive analysis.

“Whenever we discuss building a certain feature, we would definitely research our competitors and see how they do it.” Tim Soulo, CMO

You’d be surprised by how much you can learn about and from your competition and how much of it can be done online. There are certain tried and tested techniques, hacks, and tools for this type of research, and you can find them in this guide .

Analyze commercial data

Secondary market research data is relatively affordable, fast to acquire, and easy to use. Think market reports, industry insights, and a ton of research data someone has already gathered and analyzed so you don’t have to.

The most reputable sources are Gartner , Forrester , and Pew . Apart from those, make sure to check if there is a trustworthy commercial data source specific to your niche.

Sites like G2, Capterra and Trust Pilot also count. Not only do they give you an overview of your industry, but you can also find some real gems in your users’ reviews and your competitors’ reviews as well. Ahrefs uses that data source regularly internally and externally, like for this section of our Ahrefs vs Semrush vs Moz  landing page:

Benefits of market research - a comparison

Let’s quickly summarize the above 7 different methods of market research by their key benefits.

How to do market research process in 5 key steps

So now we know what market research is, why and when to do it, and we’ve learned about all of the important types and methods.

Let’s see how we can use that knowledge to conduct any type of market research in 5 steps.  As an example of market research, I’ll tell you about some of my past experiences with a 3D printing company.

• Identify the market research problem
• Choose the sample and research method
• Collect the data
• Analyze the data
• Interpret and present conclusions

1. Identify the market research problem

This is where every research project starts. You will also find that market research, in general, follows the pattern of the scientific method . First, you need to establish what exactly you are researching.

Do you have a question about your business you want to answer? Maybe you see an opportunity in the market. Or maybe you’ve observed something curious about your product use and you have a hypothesis that you want to validate? State that in the first step of the market research process.

Let me share an example.

In the past, I ran marketing for a few companies, and one of them was a 3D printer manufacturer. Early on I stumbled upon two problems with that company.

First: one of our market segments was saturated with similar products of similar quality at significantly lower price (classic, right?). Second: more and more 3D printing manufacturers seemed to be drifting away from the hobby segment to tackle the professional segments with more expensive products, yet we remained in the hobby/DIY niche. So we were too expensive for hobbyists but too hobbyist for customers who could afford us.

The hypothesis that I wanted to verify was that if the marketplace was showing a trend towards more professional use cases of 3D printing, our company should follow that trend. In other words, I wanted to check the viability of shifting the brand positioning into the professional/premium sector.

2. Choose the sample and research method

We’ve already covered the main types and methods of market research. You should already have a good idea of the differences between primary and secondary research, or whether qualitative or quantitative methods would best suit your needs.

As for the sample of your research, this refers to the portion of the entire data source in question that you will use. For example, if you want to run a survey among your customers, the sample will refer to the selection of customers you will include in your survey. There are a few options for choosing a sample:

• Use the entire data source . Obviously, it’s not a sample per se. Nevertheless, if sending a survey to all of your customers is doable (and reasonable), this is a perfectly good choice.
• Choose a random sample. Systematic sampling is the easiest way to choose a random sample. This is where you select every x/nth individual for the sample, where x is the population, n is the sample. For example, if you want a sample size of 100 from a population of 1000, select every 1000/100 = 10th member of the population.
• Convenience sampling: choose respondents available and willing to take part in the survey.
• Purposive sampling: choose respondents that in your judgement will be representative or possess some other feature that is important to the research.
• Quota sampling:  choose some arbitrary quota of respondents, e.g. 10 non-paying customers, 10 paying small companies and 10 paying large companies.

Back to our example. As a method for verifying my hypotheses, I chose a mix of:

• Surveys sent to all of our resellers.  We wanted to see if they also had seen a paradigm shift in the market and what segment of clients they had encountered the most. We also wanted to know their perspective on the longevity of that trend, and whether they potentially be interested in a more premium version of our product.
• In-depth interviews  on the phone with our resellers conducted by our sales team. We used purposive sampling here. Our sample comprised resellers with which we had the best relations (we knew they would be more eager to share).
• Competitive analysis.  We were mostly interested in market players who tried to penetrate the professional/industrial segment, so this was our sample ( purposive sampling ). We were interested in stuff like: what features were they building into their 3D printers, what was their brand positioning, what was their pricing, what language they used to communicate with their target audience, etc.
• Wohler’s industry report, anything 3D printing from Gartner and the like, reports by 3D printing services providers, and basically any scrape of serious data we could find ( convenience sampling ).
• Internal data:  customer satisfaction issues, and just general current customer profile based on Google Analytics and Facebook data.

3. Collect the data

Once you’ve got your problem, method, and sample nailed, all you need to do is to gather the data. This is the step where you send out your surveys, conduct your interviews, or reach out for industry insights.

A word of advice, choose your market research tool carefully; it will greatly influence the amount of work you will have with analyzing the data. For example, Google Forms  automatically makes graphs out of quantifiable data (plus it’s free).

Here’s the data we collected for the 3D printing company:

• Reseller survey data (both quantitative and qualitative data).
• Reseller interview data (qualitative data).
• Customer satisfaction issues (qualitative data gathered through all customer support channels, we analysed about 200 issues and requests).
• Competitive analysis data (from about 10 competitors).
• We managed to gather 3 comprehensive, independent industry reports, a few smaller reports made by other 3D printing companies, and dozens of scrapes of data, like statistics and noteworthy insights. We pulled out data like: 3D printer manufacturer market share, market growth in time, market segmentation, key 3D printing applications, 3D printing adoption by region, key players’ sales numbers.
• Any demographic, sociographic and psychographic data on customers and website visitors we could find in our internal data.

4. Analyze the data

Now that you have your data collected, the next step is to look for patterns, trends, concepts, or often repeated words—all dependent on whether your method was qualitative or quantitative (or both).

Simple research performed on a small sample will be relatively easy to analyze, or even analyzed automatically, like with the aforementioned Google Forms. Sometimes you will have to use expensive and harder to master software like Tableau , NVivo , PowerBI , or SPSS . Or you can use Python or R for data analysis (if you have a data analyst or data scientist on board, you’re in luck).

Continuing the example: Google Forms made it easy for us to spot patterns in surveys since quantitative data was calculated automatically. The most time-consuming part was reading through all of the responses and manually looking for patterns (back then I wasn’t aware of any tool that could do the job). Both sales and marketing teams worked on analyzing some of the qualitative data to have more than one reference point.

When it comes to researching the competition, coming up with some kind of data structure makes the work more comprehensive (and saner). We put our competitors’ data in specific categories, like products & services (prices included), target market, benefits, values, and brand message. We also used something called a brand positioning map which looks like this:

Analyzing secondary data was probably the easiest part, as the data we needed was already prepared in ready-to-use graphs, statistics and insights. We just had to sift through the contents to look for answers to our questions.

5. Interpret and present conclusions

Analyzing the data is not enough. You need to compile your data in a communicative, actionable way for the decision makers. A good practice is to include in your report: all your information, a description of your research process, the results, conclusions, and recommended actions.

Summing up my 3D printing example, I hypothesised that our market was experiencing a major shift and that the company should follow that trend. The research we did verified that hypothesis positively:

• Our resellers were getting more and more inquiries about professional/industrial use cases and machines. As you can imagine, the budget of this kind of client was significantly higher than hobbyists but so were the expectations.
• Our resellers indicated that this phenomenon is here to stay. Moreover, they declared interest in a new 3D printer tailored to the needs of their more demanding clientele.
• Our customers were outgrowing their early-adopter habits and wanted something easier to use, something plug-and-play that just worked reliably. Tinkering with the printer was something only hardcore makers were interested in.
• The companies we were interested in had already started adapting to the professional/premium market both with their offer and smart marketing communication.
• We also found a ton of other interesting data that we used later on. For example, we found that apart from engineers and designers, an equally interesting segment was educational institutions.

Our initial market research lasted for about two months. We also came back to it whenever we had the chance (or the necessity) and reiterated it to see if we were on the right track.

Was it worth it? Let me tell you this: it saved the company. Our research showed us that this was the last call to reposition the brand and the product. Our original target segment was being gradually dominated by companies we couldn’t compete with.

It took us some time to get buy-in from key stakeholders and implement the conclusions throughout the whole company (eventually, we got it right). As a result, we increased sales, increased customer satisfaction and put ourselves on a more profitable growth track—a win-win for everyone. We even went as far as merging with another manufacturer to shorten the time to get to that sweet market spot.

Looking back, no one from our close competitors survived. They didn’t adapt as we did, and we owed everything to market research.

Whatever you do, avoid these common market research mistakes :

• Poor sampling.
• Ambiguous questions.
• Leading or loaded questions (questions that show bias or contain controversial assumptions).
• Unclear or too many research objectives.
• Mixing correlation with causation.
• Ignoring competitive analysis.
• Allowing biases to influence your research ( confirmation bias  being arguably the most common and the most dangerous one).
• Not tracking data on a regular basis.

Online market research tools and resources

Market research reaches back to the 1930s and it’s probably rooted even “deeper” than the 20th century. Everything you could do then you can do now better, faster and cheaper thanks to these online tools and resources.

SEO tools - research the market with Ahrefs

I’ve put together 3 quick wins that can help with your market research—and that’s only a taste of what you can do with Ahrefs.

1. Brand awareness

In the early 20th century, you’d have to hire market researchers to spend days or even weeks asking people “have you heard about brand X”. Today, you can simply look up the search volume for that brand.

So let’s say you run a drone manufacturing brand, and you want to check out your competitors’ brand awareness in France. Go to Ahrefs Keywords Explorer , input the names of the brands, select “France” as your market, and in a flash you get:

The branded keyword volume indicates the brand awareness of that brand in a particular market. You can also keep track of that data by performing this search regularly to see if there are significant changes over time (for example, impacted by a recent campaign).

2. Feature demand

The next game-changing feature for electric cars will concern batteries, charging time, and charging cost (and not autopilot). How do I know?

Well, I opened Ahrefs Keywords Explorer , typed in “electric cars”, and went to the Questions report to find out what people search for. This gave me an idea of what problems electric car owners have (and potential owners worry about). You can easily perform similar research for your niche.

3. Understand the language of your market

Gerald Zaltman in his popular book “How Customers Think” proposes the idea that one of the major erroneous assumptions of marketing is that consumers think in words.

On the other hand, when consumers Google something they have to think in words. And when we market to those consumers we have to think in words as well. The question is: which words?

Let’s say that you want to enter a new and innovative market in the USA, for example the synthetic fermentation-derived dairy industry, also called animal-free dairy.

To you, this set of words “animal-free dairy” may be the very center of your business and marketing efforts. But let’s see what other people think. Let’s use Keywords Explorer  to see how many people search Google in the U.S. just for that phrase:

Whoops! Looks like your product category has disappointingly low awareness. Does this mean you’re doomed? Not necessarily. 

Let’s try other words. Words that mean something different, but still closely related to your new product.

Now we’re onto something. People search for “vegan dairy” and “lactose free dairy” more often. Not the same, but closely related. Yet, look at the difference in search volume.

Words make a huge difference.  And Google knows that.

The only reason you were able to put all of those three phrases in the same bucket was that you knew the connection between those words. The problem is that your target audience may not know that connection; they may not even know that this kind of product exists. This quick analysis of search volume shows that you may want to make that connection, for example with content marketing .

If you create content around related higher volume keywords, you can potentially get more organic traffic than simply focusing on the keyword designating your product category.  Look, even though you might believe the main benefit of your animal-free product is something unrelated to lactose, e.g., cruelty-free production, you might want to address the problem of lactose intolerance to appeal to people with this condition.

But that’s not all. You may have noticed “low lactose cheese” in the bottom right corner. This refers to the nifty feature of Ahrefs’ Keyword Explorer called “Parent topic”. Parent topic indicates that Google sees a given keyword as part of a broader topic.

If we click on this Parent topic, we uncover even more search demand:

We can see that the search for the topic “low lactose cheese” exceeds the “vegan dairy” topic by almost 300% in the US. Also, uncovering that parent topic gave us 879 potential keyword ideas (some of them have even higher search volume, like “lactose free cheese”).

Want to discover even more topic associations? No problem. You can dive deeper into this research by using other features of Ahrefs’ Keyword explorer. For example,the  Also rank for  report allows you to see which other keywords (and topics) the top 100 ranking pages for your target keyword also rank for.

This market research quick-win ties into the broader topic of keyword research. If you want to uncover even more keyword ideas and learn how to analyze them, read  our keyword research guide .

Source: https://hubspot.com

Customer Relationship Management software is used to manage and track interactions between a company and its customers and prospects. Usually, it works in tandem with sales or marketing automation software (or has integrations for them). If used properly, it is a true cornucopia of market insight.

As I pointed out earlier, it’s one of those primary data sources that you can leverage to discover patterns in your customer behaviour or characteristics. Popular choices are Hubspot, Salesforce, Intercom, but there is a ton of CRM software out there, so check out a software comparison like G2  to see what best suits your needs.

User feedback tools

This type of tool allows you to carry out our aforementioned survey research method online.

Create targeted, user-specific surveys and analyze answers with tools like Google Forms , SurveyMonkey , Typeform , or Qualaroo .  

Sending out your typical email with a survey is not the only option, for example with Qualaroo you can display surveys:

• In your digital product
• In your SaaS product
• Inside your web app
• Inside your mobile app
• On your website
• On your mobile site
• On your prototypes.
• On most public URLs. Even competitor sites

Need more? No problem, check out SurveyMonkey’s Market Research solution . It taps into the agile market research models we’ve discussed. They’ve got 14 online solutions that help you stay on top of your game, including customer segmentation, monitoring market dynamics, brand, creative analysis, feature importance, finding the right price for your products, and more.

So you think you have a tough business challenge? This daring gentleman is trying to disrupt… eggs. Extremely hard, but doable with market research on his side.

Website/app analytics

Tracking your website or app traffic is absolute marketing basics. Just look at some data dimensions Google Analytics offers:

• Demographics

Sounds familiar? Yup, that sounds like good ol’ market segmentation. Here’s the best part: it’s free, quick to perform and it’s based on your primary data.

If you’ve never dug deeper into Google Analytics, or similar analytics software (e.g., Matomo , Woopra ) here are some questions that this marketing technology can answer for you: 

• What do people search for once they’re on my site?
• What differentiates customers who have made a purchase from the ones that haven’t?
• What are my top countries by revenue?
• What are my best selling products?

If you’re already using Google Analytics, see if you’re not making these Google Analytics tracking mistakes. 

User experience research tools

Commonly used by UX designers, but just listen to the value propositions of these tools:

• “See and hear real people using your website, online shop or app.” ( https://userpeek.com/ )
• “Real-time feedback. From real customers. Wherever you work. So you can create experiences that get real results.” ( https://www.usertesting.com/ )
• “Scalable & Customized User Research” ( https://www.userlytics.com/ )
• “Record video and audio of your users, so you see and hear their exact experience with your product.” ( https://www.loop11.com/ )

Again, sounds much like our market research methods, right? And it’s no joke, thousands of companies use these tools.

User experience research tools allow you to get user feedback and insights on your products, prototypes, websites, and apps.

Testing is based on tasks your test-takers perform. You can either use your own user base or define a custom base using their services. You’ll get written reports and even recorded videos that you can incorporate into your market research and make sure you’re properly taking advantage of that market opportunity.

Ad planning tools

That’s right—the Facebook, LinkedIn, and Twitter ad planner you already use for running ads can give you some insight into the numbers behind the market segments you’re interested in.

30+ males with higher education interested in technology gadgets? No problem. Female C-suite decision-makers from Europe? It’s all there.

Census data

The availability of this kind of data may vary based on your target market. For example, in the US the Census Bureau  offers a free resource for searching the country’s census data. You can filter the data by topics, years, geography, surveys, or industry codes. You can also access premade interactive tables (which you can also download) or simply explore certain regions of the country using their maps.

Business intelligence tools

With business intelligence tools like Tableau , Looker or Sisense , you can connect to any data source to perform data cleaning, statistical operations, and data visualization. They are designed to allow you to glean insights into your data, and communicate effectively with your stakeholders. It’s like SQL combined with R, but you don’t need coding skills and you get a user-friendly interface.

Because these tools are overflowing with functionality and because they are usually pricey, they are overkill for small companies with basic market research needs. Often you will find that the tool that you are already using for your research method comes with some data analysis and visualization functions. And if not, you can always import your data to Excel or Google Docs and use Google Data Studio for a shareable interactive presentation.

Other noteworthy tools and services

• Think with Google
• Living Facts

Final thoughts

Market research is no easy feat. If you feel intimidated by it, you’re not the only one. But don’t shy away from it. The benefits of conducting even sporadic market research can have benefits for your business you simply can’t ignore. You won’t turn into a market research pro overnight, but the good news is you don’t have to. You can go the agile way (like Ahrefs), use affordable self-service online tools and resources, or you can even outsource your research. As long as you base your marketing game plan on valid data, you dramatically improve your chances for success.

Got questions? Ping me on Twitter .

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Reliability vs. Validity in Research: Types & Examples

When it comes to research, getting things right is crucial. That’s where the concepts of “Reliability vs Validity in Research” come in. 

Imagine it like a balancing act – making sure your measurements are consistent and accurate at the same time. This is where test-retest reliability, having different researchers check things, and keeping things consistent within your research plays a big role. 

As we dive into this topic, we’ll uncover the differences between reliability and validity, see how they work together, and learn how to use them effectively.

Understanding Reliability vs. Validity in Research

When it comes to collecting data and conducting research, two crucial concepts stand out: reliability and validity. 

These pillars uphold the integrity of research findings, ensuring that the data collected and the conclusions drawn are both meaningful and trustworthy. Let’s dive into the heart of the concepts, reliability, and validity, to comprehend their significance in the realm of research truly.

What is reliability?

Reliability refers to the consistency and dependability of the data collection process. It’s like having a steady hand that produces the same result each time it reaches for a task. 

In the research context, reliability is all about ensuring that if you were to repeat the same study using the same reliable measurement technique, you’d end up with the same results. It’s like having multiple researchers independently conduct the same experiment and getting outcomes that align perfectly.

Imagine you’re using a thermometer to measure the temperature of the water. You have a reliable measurement if you dip the thermometer into the water multiple times and get the same reading each time. This tells you that your method and measurement technique consistently produce the same results, whether it’s you or another researcher performing the measurement.

What is validity?

On the other hand, validity refers to the accuracy and meaningfulness of your data. It’s like ensuring that the puzzle pieces you’re putting together actually form the intended picture. When you have validity, you know that your method and measurement technique are consistent and capable of producing results aligned with reality.

Think of it this way; Imagine you’re conducting a test that claims to measure a specific trait, like problem-solving ability. If the test consistently produces results that accurately reflect participants’ problem-solving skills, then the test has high validity. In this case, the test produces accurate results that truly correspond to the trait it aims to measure.

In essence, while reliability assures you that your data collection process is like a well-oiled machine producing the same results, validity steps in to ensure that these results are not only consistent but also relevantly accurate. 

Together, these concepts provide researchers with the tools to conduct research that stands on a solid foundation of dependable methods and meaningful insights.

Types of Reliability

Let’s explore the various types of reliability that researchers consider to ensure their work stands on solid ground.

High test-retest reliability

Test-retest reliability involves assessing the consistency of measurements over time. It’s like taking the same measurement or test twice – once and then again after a certain period. If the results align closely, it indicates that the measurement is reliable over time. Think of it as capturing the essence of stability. 

Inter-rater reliability

When multiple researchers or observers are part of the equation, interrater reliability comes into play. This type of reliability assesses the level of agreement between different observers when evaluating the same phenomenon. It’s like ensuring that different pairs of eyes perceive things in a similar way. 

Internal reliability

Internal consistency dives into the harmony among different items within a measurement tool aiming to assess the same concept. This often comes into play in surveys or questionnaires, where participants respond to various items related to a single construct. If the responses to these items consistently reflect the same underlying concept, the measurement is said to have high internal consistency. 

Types of validity

Let’s explore the various types of validity that researchers consider to ensure their work stands on solid ground.

Content validity

It delves into whether a measurement truly captures all dimensions of the concept it intends to measure. It’s about making sure your measurement tool covers all relevant aspects comprehensively. 

Imagine designing a test to assess students’ understanding of a history chapter. It exhibits high content validity if the test includes questions about key events, dates, and causes. However, if it focuses solely on dates and omits causation, its content validity might be questionable.

Construct validity

It assesses how well a measurement aligns with established theories and concepts. It’s like ensuring that your measurement is a true representation of the abstract construct you’re trying to capture. 

Criterion validity

Criterion validity examines how well your measurement corresponds to other established measurements of the same concept. It’s about making sure your measurement accurately predicts or correlates with external criteria.

Differences between reliability and validity in research

Let’s delve into the differences between reliability and validity in research.

While both reliability and validity contribute to trustworthy research, they address distinct aspects. Reliability ensures consistent results, while validity ensures accurate and relevant results that reflect the true nature of the measured concept.

Example of Reliability and Validity in Research

In this section, we’ll explore instances that highlight the differences between reliability and validity and how they play a crucial role in ensuring the credibility of research findings.

Example of reliability

Imagine you are studying the reliability of a smartphone’s battery life measurement. To collect data, you fully charge the phone and measure the battery life three times in the same controlled environment—same apps running, same brightness level, and same usage patterns. 

If the measurements consistently show a similar battery life duration each time you repeat the test, it indicates that your measurement method is reliable. The consistent results under the same conditions assure you that the battery life measurement can be trusted to provide dependable information about the phone’s performance.

Example of validity

Researchers collect data from a group of participants in a study aiming to assess the validity of a newly developed stress questionnaire. To ensure validity, they compare the scores obtained from the stress questionnaire with the participants’ actual stress levels measured using physiological indicators such as heart rate variability and cortisol levels. 

If participants’ scores correlate strongly with their physiological stress levels, the questionnaire is valid. This means the questionnaire accurately measures participants’ stress levels, and its results correspond to real variations in their physiological responses to stress. 

Validity assessed through the correlation between questionnaire scores and physiological measures ensures that the questionnaire is effectively measuring what it claims to measure participants’ stress levels.

In the world of research, differentiating between reliability and validity is crucial. Reliability ensures consistent results, while validity confirms accurate measurements. Using tools like QuestionPro enhances data collection for both reliability and validity. For instance, measuring self-esteem over time showcases reliability, and aligning questions with theories demonstrates validity. 

QuestionPro empowers researchers to achieve reliable and valid results through its robust features, facilitating credible research outcomes. Contact QuestionPro to create a free account or learn more!

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• Reliability vs Validity in Research | Differences, Types & Examples

Reliability vs Validity in Research | Differences, Types & Examples

Published on 3 May 2022 by Fiona Middleton . Revised on 10 October 2022.

Reliability and validity are concepts used to evaluate the quality of research. They indicate how well a method , technique, or test measures something. Reliability is about the consistency of a measure, and validity is about the accuracy of a measure.

It’s important to consider reliability and validity when you are creating your research design , planning your methods, and writing up your results, especially in quantitative research .

Table of contents

Understanding reliability vs validity, how are reliability and validity assessed, how to ensure validity and reliability in your research, where to write about reliability and validity in a thesis.

Reliability and validity are closely related, but they mean different things. A measurement can be reliable without being valid. However, if a measurement is valid, it is usually also reliable.

What is reliability?

Reliability refers to how consistently a method measures something. If the same result can be consistently achieved by using the same methods under the same circumstances, the measurement is considered reliable.

What is validity?

Validity refers to how accurately a method measures what it is intended to measure. If research has high validity, that means it produces results that correspond to real properties, characteristics, and variations in the physical or social world.

High reliability is one indicator that a measurement is valid. If a method is not reliable, it probably isn’t valid.

However, reliability on its own is not enough to ensure validity. Even if a test is reliable, it may not accurately reflect the real situation.

Validity is harder to assess than reliability, but it is even more important. To obtain useful results, the methods you use to collect your data must be valid: the research must be measuring what it claims to measure. This ensures that your discussion of the data and the conclusions you draw are also valid.

Prevent plagiarism, run a free check.

Reliability can be estimated by comparing different versions of the same measurement. Validity is harder to assess, but it can be estimated by comparing the results to other relevant data or theory. Methods of estimating reliability and validity are usually split up into different types.

Types of reliability

Different types of reliability can be estimated through various statistical methods.

Types of validity

The validity of a measurement can be estimated based on three main types of evidence. Each type can be evaluated through expert judgement or statistical methods.

To assess the validity of a cause-and-effect relationship, you also need to consider internal validity (the design of the experiment ) and external validity (the generalisability of the results).

The reliability and validity of your results depends on creating a strong research design , choosing appropriate methods and samples, and conducting the research carefully and consistently.

Ensuring validity

If you use scores or ratings to measure variations in something (such as psychological traits, levels of ability, or physical properties), it’s important that your results reflect the real variations as accurately as possible. Validity should be considered in the very earliest stages of your research, when you decide how you will collect your data .

• Choose appropriate methods of measurement

Ensure that your method and measurement technique are of high quality and targeted to measure exactly what you want to know. They should be thoroughly researched and based on existing knowledge.

For example, to collect data on a personality trait, you could use a standardised questionnaire that is considered reliable and valid. If you develop your own questionnaire, it should be based on established theory or the findings of previous studies, and the questions should be carefully and precisely worded.

• Use appropriate sampling methods to select your subjects

To produce valid generalisable results, clearly define the population you are researching (e.g., people from a specific age range, geographical location, or profession). Ensure that you have enough participants and that they are representative of the population.

Ensuring reliability

Reliability should be considered throughout the data collection process. When you use a tool or technique to collect data, it’s important that the results are precise, stable, and reproducible.

• Apply your methods consistently

Plan your method carefully to make sure you carry out the same steps in the same way for each measurement. This is especially important if multiple researchers are involved.

For example, if you are conducting interviews or observations, clearly define how specific behaviours or responses will be counted, and make sure questions are phrased the same way each time.

• Standardise the conditions of your research

When you collect your data, keep the circumstances as consistent as possible to reduce the influence of external factors that might create variation in the results.

For example, in an experimental setup, make sure all participants are given the same information and tested under the same conditions.

It’s appropriate to discuss reliability and validity in various sections of your thesis or dissertation or research paper. Showing that you have taken them into account in planning your research and interpreting the results makes your work more credible and trustworthy.

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How to Perform Market Validation: A Step-by-Step Guide

It's essential to validate product ideas before investing time and money. Learn how to perform market validation and the user research methods that make it work.

How does that saying go, something like  If wishes were business ideas, we would all have a few Fortune 500 companies under our belt ? Okay, perhaps I made that up, but maybe it should be a saying. After all, how often have you come up with an idea and thought it wasn't practicable, only to see it come to market some months later from somebody else? Or you don't know if your great idea is feasible, so you move on and forget about it? Or someone else thinks it's pie-in-the-sky, so you scuttle your idea off to the Dead Ideas folder on your computer?

Yet some ideas are clear winners. How can you tell which brilliant idea for a new product or feature is worth pursuing and which might not be as valuable or need more tweaking? Market validation research is a vital step between ideation and creation that can answer that question before you invest too much time or resources into it. 

Let's take a deeper look at what exactly market validation is, why it's essential for companies before investing in ideas, when and how to conduct  market validation research , and the methodologies that can help you get the market validation your idea or product needs to succeed. 

What is market validation research?

Market validation is the process of testing a new product idea for viability to determine whether a product or feature is needed in your target market. Simply put, does the public have an appetite for your product? It is a crucial step to take between product concept ideation and product creation. 

By testing the practicality and feasibility of a new product with the target market before investing time and resources into its development,  you will have a better sense of what your users' needs are  and whether and confidence in whether (or not) your product will fulfill those needs. 

Market validation research can also help garner buy-in for your product or idea. Early validation will allow stakeholders—internal team members or external funders—to be confident in bringing your concept to market. Further, market validation research can allow you to tweak and hone your idea to better address any unmet needs or pain points your users may have.

Market validation is generally accomplished by identifying the buyers or users of your product in your target market and then interviewing or surveying them for direct feedback about their needs and pain points. 

Why is market validation a vital early step in the development process?

Having what feels like a wholly intuitive and ingenious idea can often motivate moving fast to push it into development. However, anyone who's worked in product management has probably had the unfortunate experience of discovering that what sounded terrific in a product dev meeting doesn't stand up under real-world scrutiny.  Why?

• Perhaps your target market would like your idea but not enough to pay for it 
• Maybe it's not as big of a problem for your market base as your team supposes
• Maybe your target users would love your idea, but their companies don't find it to be a value add for their budgets 
• Perhaps your users have already figured out an easy way to resolve the issue your product is addressing

By conducting market validation research before investing in the development of a new product, your company can help justify buy-in and funding for the product while avoiding the waste of a product failing to meet expectations. 

The real-world value of market validation research is that it will help you uncover the blind spots you or your team may have when evaluating your ideas, unearth pain points for your target market that you might have glanced over, and help to finetune your thinking before an idea moves into development. After all, running market validation research and finding out your idea is a clunker is much less expensive than developing and marketing an idea that underperforms expectations.

What research methodologies are used in market validation?

Many methodologies can be employed for market validation research, each representing advantages and disadvantages. Some lean towards quantitative data to provide a high-level understanding of the market, while others are more qualitative and can give you an idea of what users in your target market feel and think about the product. When choosing which methodologies might be best for your product, the goal is to employ multiple methods to give you a richer and more complex view of the market. First, let's look at the most common methods.

Surveys, focus groups, and interviews

Depending on whether the  questions you ask your subjects  are open or close-ended, surveys, focus groups, and in-depth interviews can give you both qualitative and quantitative data directly from your target market of users. 

Additionally, each method provides the flexibility to learn in-depth feedback directly from interview subjects and gather data that can give valuable direction to your project. Surveys offer the opportunity to collect large amounts of data at one time. Focus groups and interviews can allow you to drill down quickly when you discover specific pain points your target users experience.  

Observational research

In observational research, you have your testers interact directly with your product and take note of their actions, behaviors, frustrations, holdups, habits, and pain points, often without giving them much direction. This is often helpful information for products with a less tech-savvy market base. It can also be beneficial if you've run alpha and beta testing and find disparate data from your two user groups.  

Usability testing

Which leads us to  usability testing . Like observational research, usability testing requires observing how users interact with your product following a determined set of steps while you watch and record their reactions and issues. 

When users can directly interact with and comment on your product in an observational setting, you can assess how easy to use your product is, how useful the functionality might be, and how receptive your test market is to changes you've made. 

Building out a minimum viable product (MVP)

Developing the minimum viable product (MVP) would be one of the last steps of market validation you and your team might take. That's because an MVP is your product's basic, physical version that can still offer usefulness to your users. However, producing one can represent a significant outlay of resources and costs—both in time and financial investments—so not every project or company will find building an MVP practical.

If you are working on a first product, rather than a new feature, say, it could be sensible to produce an MVP early. Not only will this allow you to have a basic version of your product to market validate with test consumers, but you can also begin making revenue from an early version while fine tuning your product. 

A/B Testing

One way to evaluate how much value a new feature for an existing product might add is by running A/B testing ads designed to test how many click-throughs you get for one idea compared to another. For example, suppose we were thinking about adding a feature to our  verified research participant database  that offered AI to complement traditional surveys. In that case, we could set up an SEM test with a campaign that offers "Verified research participants tailored to your needs" and compare it to another campaign offering "Verified research participant recruiting powered by AI insights." 

By comparing the number of click-throughs each ad garners, we could have constructive insights into whether there's a desire or value in adding AI to our product. You can also tailor the landing page the ads take a user to garner even more validation of a product's potential value based on clicks, impressions, and conversions to compare results from each.

Prototype testing

Prototype testing can be a valuable tool in your market validation toolbelt for allowing test users the means to have meaningful interactions with your product. For usability testing, having a prototype available for users to interact with can give you keen insight into how the product works in real-life settings, possible UX/UI issues, timely feedback on design issues before full development, and a better understanding of how your users interact with your product. 

Utilizing SEO results and Google Trends 

One of the simplest ways to begin market validation is to use free/low-cost tools your organization likely already has access to. Just like you'd check your SEO results frequently after you launch a new project, you can also utilize them before building your product to gauge what your user base's interests, needs, and pain points are by using Google Trends and SEO tools like  Semrush ,  MOZ Pro , or  Ahrefs . 

By investigating how often particular keywords and terms associated with your product are being searched, you can get an easy view of what your user base needs and where your product does or doesn't meet those needs and monitor growth in interest over time and location. 

The market validation step-by-step guide

Step 1 – define goals, assumptions, hypotheses, and target customer.

• Define your goals clearly
• Identify your target market
• Highlight any untested assumptions
• Identify unmet needs your customer base may have
• Define your unique value props
• Develop your hypotheses

The first step is to identify your goals for your product. Having a clear view of what you expect to accomplish, you can then clarify any plans that may still be assumptions that need to be verified.

Next, clearly define your target market for yourself. This will help you move on to the next step, which is documenting your hypotheses about the function of your product, how you will produce it, the pricing model, and so on. 

Once you have a handle on your target consumers, define your unique value propositions, what makes your product useful, necessary, or unique, and how it meets your users' unmet needs. When you have a keen understanding of these things, you'll clearly understand what you will need to test with market validation research.

Step 2 - Assess the market size and share/competitive landscape

Next, get a fuller idea of your market size, the share that you think you could reasonably capture with your idea, and who your competitors in the market are. 

Start broadly by researching the industry, its annual spending, and how your unique value props may disrupt that.

Utilize SEO search volume tools to better understand the demand for your product and how you can best capitalize on that demand to make your product stand out against competitors. 

Step 3 - Perform customer validation research

Your next step involves getting into the nitty gritty and performing customer validation research that will give you actionable insights into what your target market segment needs–their pain points- and how your product can potentially alleviate these needs. 

This will often involve conducting interviews with your target market by  finding research participants  to conduct interviews, holding focus groups, or gathering data via online surveys. You're looking to answer a few basic questions at this stage. That is:

• What are the pain points or unserved needs your market segment is encountering?
• What are their motivations and preferences?
• How are your competitors' products leaving these needs unmet?
• What are the workarounds they've developed to try to meet these needs themselves?
• Are they able to solve this/these problems?
• What is their level of satisfaction with the products they currently use?
• Would your product be useful as a solution?
• Are there any assumptions or hypotheses you originally created that need user feedback?
• Is there a feasible monetization of your solution for their needs?

When beginning this kind of research, you'll also need to look at what success means for your product by clearly defining your success criteria. First, understand what user responses will define success for your product or idea. Do this by looking at what percentage of respondents experience specific pain points, what percentage find your product idea to be a viable solution for their particular problem or problems, and what percentage would realistically pay for your product to solve their problems. 

Next, analyze the data that you've gathered. Go back to the list of hypotheses and assumptions you created. You may need to revise your original assumptions. This could also be where you realize there isn't realistically a market for your product or idea, and that's okay, too. Ask yourself, if this isn't the solution our market base is looking for, what is? Work to improve what you have to offer, and then you can revisit test market validation again.

Step 4 – Test your product

Once you have a reasonably strong idea that your idea could be a solution, you can move forward in market validation testing and research that takes more investment, such as prototyping or creating an MVP. After that, you'll want to move on to testing your product. 

First, test your product with focus groups or interviewees who can give you granular data about how the product works and what might need to be finetuned. Utilize test groups who will realistically be real-world users to get a fair and representative idea of how your product will function in the marketplace. Then, utilize these insights to tweak and adjust your product as necessary.

Next, it often makes sense to conduct alpha testing for your product with internal employees in a controlled setting that will allow you to check for issues, identify bugs or quirks, and address them before making your product public. 

Finally, you can perform beta testing by releasing your product to a small, limited set of external users, with the goal being to identify problems, glitches, or UX issues before a wider release. 

Ultimately, don't we all just need a little validation?

We all understand the value of having our ideas validated in our personal lives. With new products and features, validation is a meaningful way of proving market value, gaining buy-in, and providing a bridge between ideation and development. 

The goal for market validation is about more than building a Fortune 500 company overnight, unfortunately. However, if that's a vision you have for your future, taking the proper steps when taking a new product, startup, or feature to market is a small step toward achieving that. Instead, market validation research is a process that can help you make the best use of your resources and determine whether your product or idea is ready to push into development so that your company continues to produce the best version of every product it offers. 

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Validity & Reliability In Research

A Plain-Language Explanation (With Examples)

By: Derek Jansen (MBA) | Expert Reviewer: Kerryn Warren (PhD) | September 2023

Validity and reliability are two related but distinctly different concepts within research. Understanding what they are and how to achieve them is critically important to any research project. In this post, we’ll unpack these two concepts as simply as possible.

This post is based on our popular online course, Research Methodology Bootcamp . In the course, we unpack the basics of methodology  using straightfoward language and loads of examples. If you’re new to academic research, you definitely want to use this link to get 50% off the course (limited-time offer).

Overview: Validity & Reliability

• The big picture
• Validity 101
• Reliability 101 
• Key takeaways

First, The Basics…

First, let’s start with a big-picture view and then we can zoom in to the finer details.

Validity and reliability are two incredibly important concepts in research, especially within the social sciences. Both validity and reliability have to do with the measurement of variables and/or constructs – for example, job satisfaction, intelligence, productivity, etc. When undertaking research, you’ll often want to measure these types of constructs and variables and, at the simplest level, validity and reliability are about ensuring the quality and accuracy of those measurements .

As you can probably imagine, if your measurements aren’t accurate or there are quality issues at play when you’re collecting your data, your entire study will be at risk. Therefore, validity and reliability are very important concepts to understand (and to get right). So, let’s unpack each of them.

What Is Validity?

In simple terms, validity (also called “construct validity”) is all about whether a research instrument accurately measures what it’s supposed to measure .

For example, let’s say you have a set of Likert scales that are supposed to quantify someone’s level of overall job satisfaction. If this set of scales focused purely on only one dimension of job satisfaction, say pay satisfaction, this would not be a valid measurement, as it only captures one aspect of the multidimensional construct. In other words, pay satisfaction alone is only one contributing factor toward overall job satisfaction, and therefore it’s not a valid way to measure someone’s job satisfaction.

Oftentimes in quantitative studies, the way in which the researcher or survey designer interprets a question or statement can differ from how the study participants interpret it . Given that respondents don’t have the opportunity to ask clarifying questions when taking a survey, it’s easy for these sorts of misunderstandings to crop up. Naturally, if the respondents are interpreting the question in the wrong way, the data they provide will be pretty useless . Therefore, ensuring that a study’s measurement instruments are valid – in other words, that they are measuring what they intend to measure – is incredibly important.

There are various types of validity and we’re not going to go down that rabbit hole in this post, but it’s worth quickly highlighting the importance of making sure that your research instrument is tightly aligned with the theoretical construct you’re trying to measure .  In other words, you need to pay careful attention to how the key theories within your study define the thing you’re trying to measure – and then make sure that your survey presents it in the same way.

For example, sticking with the “job satisfaction” construct we looked at earlier, you’d need to clearly define what you mean by job satisfaction within your study (and this definition would of course need to be underpinned by the relevant theory). You’d then need to make sure that your chosen definition is reflected in the types of questions or scales you’re using in your survey . Simply put, you need to make sure that your survey respondents are perceiving your key constructs in the same way you are. Or, even if they’re not, that your measurement instrument is capturing the necessary information that reflects your definition of the construct at hand.

If all of this talk about constructs sounds a bit fluffy, be sure to check out Research Methodology Bootcamp , which will provide you with a rock-solid foundational understanding of all things methodology-related. Remember, you can take advantage of our 60% discount offer using this link.

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What Is Reliability?

As with validity, reliability is an attribute of a measurement instrument – for example, a survey, a weight scale or even a blood pressure monitor. But while validity is concerned with whether the instrument is measuring the “thing” it’s supposed to be measuring, reliability is concerned with consistency and stability . In other words, reliability reflects the degree to which a measurement instrument produces consistent results when applied repeatedly to the same phenomenon , under the same conditions .

As you can probably imagine, a measurement instrument that achieves a high level of consistency is naturally more dependable (or reliable) than one that doesn’t – in other words, it can be trusted to provide consistent measurements . And that, of course, is what you want when undertaking empirical research. If you think about it within a more domestic context, just imagine if you found that your bathroom scale gave you a different number every time you hopped on and off of it – you wouldn’t feel too confident in its ability to measure the variable that is your body weight 🙂

It’s worth mentioning that reliability also extends to the person using the measurement instrument . For example, if two researchers use the same instrument (let’s say a measuring tape) and they get different measurements, there’s likely an issue in terms of how one (or both) of them are using the measuring tape. So, when you think about reliability, consider both the instrument and the researcher as part of the equation.

As with validity, there are various types of reliability and various tests that can be used to assess the reliability of an instrument. A popular one that you’ll likely come across for survey instruments is Cronbach’s alpha , which is a statistical measure that quantifies the degree to which items within an instrument (for example, a set of Likert scales) measure the same underlying construct . In other words, Cronbach’s alpha indicates how closely related the items are and whether they consistently capture the same concept . 

Recap: Key Takeaways

Alright, let’s quickly recap to cement your understanding of validity and reliability:

• Validity is concerned with whether an instrument (e.g., a set of Likert scales) is measuring what it’s supposed to measure
• Reliability is concerned with whether that measurement is consistent and stable when measuring the same phenomenon under the same conditions.

In short, validity and reliability are both essential to ensuring that your data collection efforts deliver high-quality, accurate data that help you answer your research questions . So, be sure to always pay careful attention to the validity and reliability of your measurement instruments when collecting and analysing data. As the adage goes, “rubbish in, rubbish out” – make sure that your data inputs are rock-solid.

Psst… there’s more!

This post is an extract from our bestselling short course, Methodology Bootcamp . If you want to work smart, you don't want to miss this .

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• What is reliability?

Reliability indicates the extent to which the results of an experiment can be replicated when it is performed multiple times. Effective research and experiments should produce similar results over time when performed by other people, as long as instructions and conditions (methodology) are followed correctly or in the same manner each time. 

Experiments that generate unusually large differences in results should be questioned. Just because an experiment can be reproduced correctly doesn’t make the results or outcomes reliable. 

• What is validity?

Validity indicates the extent to which your research usefully and accurately measures what you are trying to measure and how that stacks up with other established concepts.  Validity can be harder to determine than reliability, but a high level of reliability assists in proving that your research is valid.  

Reliability and validity provide slightly different indications about the overall quality of your research and whether the data you obtain can accurately be used in service of your reason for doing the experiment. It is possible for an experiment to be reliable but not valid, or valid but not reliable, but the most accurate experiments produce strong, consistent results in both categories. 

• Why is this difference important?

Experiments that cannot be replicated with similar results and those that do not adequately address the question they were designed to solve produce results that should not be used for further research or as a basis for important decisions and/or policies. Since reliability and validity are different, quality research should reflect both of these principles.

• How are reliability and validity assessed?

Several types of assessments can be used to determine whether the information you gather is reliable and valid. Here are some of the most common tests used to assess the reliability and validity of research.

• Types of reliability

Test-retest reliability, internal reliability, and inter-rater reliability are among the most common types of reliability assessment. Each option can be used to help you determine the overall accuracy and consistency of your research. External reliability, parallel forms reliability, or other assessment options may also be appropriate, depending on the nature of the research you are conducting.

Each of these reliability types looks at a different factor that may affect the outcome of your research. This means that it is generally a good idea to use a combination of tests to create the most complete picture of the reliability of your data. 

Internal reliability

Many complex experiments include two or more components that are intended to measure the same type of data. This technique, which is known as internal reliability, assesses whether elements that are supposed to produce the same results do so consistently. Strong internal reliability increases the overall confidence that your data is accurate, consistent, and replicable. 

External reliability

External reliability indicates how consistent a type of measure is over a period of time or with different types of survey conditions, such as different individuals, and how successfully this can be generalized. Reliability can be determined if standard operating procedures (SOPs) are used to manage the way research is conducted so it can be reproduced. 

Test-retest reliability

Test-retest reliability measures how well tests produce similar results over time. This type of assessment provides insights into whether your experiment yields stable, consistent data when it is repeated multiple times externally, including at a later date. 

Inter-rater reliability

Well-designed tests should produce similar results regardless of who is performing them. Tests that result in vastly different data when different types of individuals are used in an experiment, for example, can indicate that there is too much variation in the equipment or tools the researchers are using. Other possibilities are that the instructions are not clear enough to be followed exactly how the experiment's designers intended them to be.

• Types of validity

Likewise, there are several types of validity assessments that can be combined to better understand how well your data represents what you want it to represent. 

Some types of validity that may be used include: 

Convergent 

Concurrent  

Construct  

Criterion  

Predictive 

• How to ensure reliability and validity in your research

Ensuring reliability and validity is a crucial step in knowing that the information your research provides is accurate, consistent, and valuable. Making sure that methods are applied consistently and taking steps to conduct research in conditions that are as similar as possible can help ensure your research is reliable.

In addition, choosing appropriate sampling, measurement tools, and methods can help make sure your research is valid. Being vigilant about ensuring reliability and validity in your research from the beginning can help you get the most out of the time, money, and other resources that are used to conduct it. 

• Can something be reliable but not valid or valid but not reliable?

It is possible for your research to fit into one category but not the other. Your data may show consistent results for something other than the question you are actually studying, or inconsistent results that do address your question but indicate that another issue is skewing your data.

Information you gain from research that is only reliable or only valid can form a helpful starting point in continuing to develop your research, but it should not be used as your final results.

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How Might You Improve the Validity of Market Research Methods?

Improving the validity of your market research can increase the effectiveness of your marketing strategies. When you know what members of your target market are doing and what they want, you can design marketing approaches that cater to their needs. Valid market research methods deliver information that is internally consistent and can be extended to cover all members of your target market. When you design your questions carefully and ensure your samples are representative, you can improve the validity of your research methods.

Ask Specific and Objective Questions

The goals of your market research influence your objectivity. Rather than proving something or showing that your approach is correct, your surveys and research activities should be aimed at finding out information and gathering data in a neutral but specific fashion. For example, a survey to show customers will pay more for higher quality might ask, "Will you pay more for better quality?" The survey may get a high percentage of positive replies but is not valid because it is neither neutral nor specific. As a result, it doesn't deliver the information you need to develop an effective strategy. It is more neutral and specific to ask, "How much more will you pay for leather instead of plastic?"

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Relationship between market research & market segmentation, what is the difference between the target population & the experimentally accessible population, focus group disadvantages, types of business research methods, how to write focus group objectives, make the sample match the target.

The people you survey should represent a cross-section of your target group. You can extend the results to the whole group as long as your sample is representative. Key factors in this matching process are sampling time and number of people surveyed. For example, if you run a coffee shop and your average customer comes in every day or two, a survey running a week should catch a good cross-section. If the average customer in a retail business orders once a month and you have many types of customers, you need at least three months to survey a representative sample.

Avoid Self-selection

Valid samples with a representative cross-section of your target group are based on random selection. If you allow survey respondents to decide whether to answer a survey, you can't be sure the respondents represent a random sample. You have to pick survey respondents at random and classify those who don't answer the questions as "did not respond." If the non-responsive group is substantial, reducing it by adding people who volunteer adds self-selection bias to the result because the volunteers are likely to share characteristics not representative of your whole target group. You may have to change how you conduct the survey to get enough samples from a random selection.

Use Screening to Make Your Sample Representative

Often a random sampling technique introduces responses from people who are not members of your target group. You can include screening questions that block those respondents from participating, or you can collect all responses and discard those from people who don't meet your selection criteria. For example, if you are surveying frequent customers, a question asking how often someone has purchased from you in the past month allows you to screen respondents. If you are surveying pensioners, an age cut-off lets you block or screen younger respondents. Screening increases the validity of your results when your research is aimed at specific groups with identifiable characteristics.

• Relevant Insights: Validity and Reliability in Surveys
• American Association for Public Opinion Research: Opt-In Surveys and Margin of Error
• Marketing Research Association: The Principles of Marketing Research

Bert Markgraf is a freelance writer with a strong science and engineering background. He started writing technical papers while working as an engineer in the 1980s. More recently, after starting his own business in IT, he helped organize an online community for which he wrote and edited articles as managing editor, business and economics. He holds a Bachelor of Science degree from McGill University.

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Validity and Reliability in Surveys

Summary: validity is about measurement accuracy. reliability is about the measurement of internal consistency. to achieve both, good survey design is a must..

4 minutes to read. By author Michaela Mora on February 21, 2011 Topics: Analysis Techniques , Market Research , Sample Size , Survey Design

We expect validity and reliability in surveys, but a lot of work is required to achieve both.

We need to consider many things in order to write surveys that gather high-quality data . These include, among others:

• Data collection method
• Respondent effort
• Questions’ wording, order, format, structure, and visual layout
• Measured behaviors
• Accuracy of the elicited information

Although all these issues are important, at the end of the day, what we want is to create surveys that yield results that are valid and reliable.

Discussions about validity and reliability are common in the field of psychometrics, but not so much in market research. Nonetheless, we assume they are present. 

Validity is concerned with the accuracy of our measurement. Although often discussed in the context of sample representativeness , we know that survey design also affects validity. In other words, it depends on asking questions that measure what we want to measure.

Most surveys often have what is called face validity , which is a matter of appearances. The questions seem like a reasonable way to obtain the information we are looking for, but are they really?

There are other types of validity survey writers should strive for.

Content Validity

This is related to our ability to create questions that reflect the issue we are researching and make sure that key related subjects are not excluded.

For example, we may want to learn how consumers use hair styling products and only ask how they used them in the past week. In this case, we are likely to miss information about product usage under different weather conditions (given that humidity can give you a bad hair day in a blink of an eye). Consequently, we may end up with an incomplete picture of consumers’ behavior in this category.

Internal Validity

This asks whether the questions we pose can really explain the outcome we want to research. In our hair styling product example, we need to ask questions that help us identify factors that influence the selection of hair styling products.

Here we are looking for a relationship between independent variables (e.g., hair type, hairstyle, etc.) and the dependent variable (e.g., likelihood to buy the hair styling products).

External Validity

This refers to the extent to which the results can be generalized to the target population the survey sample is representing. As we all know, the way we ask questions will determine the answer we get.

In other words, the questions should represent how the target population talks and think about the issue under research, which often calls for the need to conduct exploratory qualitative research.

In our example, assume we want to estimate the share of preference of our product in the hairstyling product category. To achieve this, we need to include other brands that represent this category, otherwise, we can’t extrapolate the results to the category as a whole.

Reliability

Reliability , on the other hand, is concerned with the consistency of our measurement. This is the degree to which the questions elicit the same type of information each time we use them, under the same conditions.

This is particularly important in satisfaction and brand tracking studies because changes in question wording and structure are likely to elicit different responses.

Reliability is also related to internal consistency , which refers to how different questions or statements measure the same characteristic.

Market segmentation studies provide a practical application of this concept. Many of these studies try to capture psychographics and construct behavioral or satisfaction segments. We do it often by asking respondents to rate a list of statements using different rating scales (e.g., agreement/disagreement; likes/dislikes; excellent/poor, etc.).

In our example, if we want to identify “lovers of styling products,” we should use statements to describe such consumers in a consistent way. We can test it with the help correlation analysis, split-sample comparisons, or methods such as Cronbach’s Alpha.

Validity and reliability are not always aligned. Reliability is needed, but not sufficient to establish validity.

We can get high reliability and low validity. This would happen when we ask the wrong questions over and over again, consistently yielding bad information. 

Also, if the results show large variability, they may be valid, but not reliable.

In short, don’t assume reliability and validity, unless you design surveys that really measure what you want and do it consistently.

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Quality Criteria of a Survey for Market Research

Appinio Research · 20.10.2022 · 7min read

Market research is a critical aspect of a company's decision-making process, providing essential insights that can inform various strategic plans, including product designs , advertising campaigns , and brand logos .

The goal of this research is to ensure that survey results align with reality.

For instance, if customers prefer slogan A over others in an advertising study, this should accurately reflect their genuine opinion.

To achieve this, the methods used to gather data must meet specific quality criteria that ensure accuracy and reliability.

This guide will provide a comprehensive overview of the most important quality criteria when conducting research, namely objectivity , reliability , and validity .

What are Quality Criteria in market research?

Quality criteria play a crucial role in determining the accuracy of measuring instruments like questionnaires.

When companies commission such studies, they do so with the goal of obtaining accurate insights into consumer behavior.

This means that reliable survey methods that are tailored to the specific project, such as design tests or pricing analyses using the Van Westendorp method , are necessary.

Most surveys involve questionnaires designed to measure specific variables, which is why it is essential to meet certain quality criteria such as

Objectivity

Reliability.

These quality criteria are indispensable in ensuring the collection of high-quality data from market research surveys.

Maintaining objectivity is critical to ensure that research results are free from bias and independent of the conditions under which the survey was conducted.

It is only by achieving this that different respondents' answers can be compared.

Objectivity in market research can be classified into three types:

• Data collection
• Interpretation

Objectivity in data collection

Objectivity in data collection demands that the survey's target group 's responses should not depend on the who conducts the survey or interviews them.

Standardization of survey conditions is crucial to achieve this. The interviewer must not influence the results in any way.

Objectivity in evaluation

Objectivity in evaluation requires that different researchers arrive at the same results when evaluating the collected data. This means adhering to pre-defined rules and ensuring that there is no scope for subjective interpretation.

Open-ended questions should be evaluated based on predetermined criteria. However, multiple-choice and single-choice questions can be evaluated objectively.

Objectivity in interpretation

Objectivity in interpretation entails ensuring that all individuals involved in the evaluation of the survey results come to the same conclusion. This requires following the same rules and avoiding subjective interpretation.

An automatic digital evaluation can provide objectivity in data collection and evaluation, but a clear procedure must be established for interpreting the results.

Reliability is a crucial quality criterion in market research as it determines the consistency and accuracy of the survey results. To achieve high reliability, a questionnaire must be designed in a way that allows for consistent measurement.

This means that if a consumer completes the questionnaire under the same conditions at different times, the results should be the same.

To test for reliability, researchers often use retest-reliability, which evaluates the relationship between two surveys presented to the same person at two different times.

Objectivity is a fundamental requirement for a reliable survey as it ensures that the results are independent of who conducts, evaluates, or interprets the test. By achieving objectivity, a researcher can ensure the consistency of the results, which in turn ensures reliability.

Therefore, reliability is a prerequisite for validity , the third and most important criterion for a successful study.

A valid questionnaire measures exactly what a company wants to know.

However, for a questionnaire to be considered valid, it must first satisfy the prerequisites of objectivity and reliability .

For instance, if a company wants to know whether consumers would be willing to buy a particular product at a specific price, then the questionnaire should measure exactly that and not any other unrelated factors.

There are two critical types of validity, namely internal and external :

Internal validity

Internal validity of a questionnaire measures the effect of an independent variable (e.g., product design) on a dependent variable (e.g., purchase intention).

The questionnaire has high internal validity i f the change in the dependent variable can be attributed solely to the modification in the independent variable. This means that there should be minimal disruptive factors during the survey.

For instance, if a company wants to test the packaging for a yogurt and shows consumers various designs, the change in respondents' attitude towards the yogurt design should result from the design differences and not because the respondents were distracted.

External validity

External validity measures the generalizability and representativeness of the survey results.

It shows how much the statements made by respondents in the survey can be applied to their actual behavior and to what extent this also applies to other people outside the sample surveyed.

For example, if a company wants to know whether consumers want to buy milk at their next purchase, the response given by the participants should reflect their real behavior.

Therefore, what respondents say in surveys should accurately represent their actual behavior.

To ensure high-quality data from surveys, certain quality criteria must be met, including objectivity, reliability, and validity.

Objectivity ensures that the results are independent of the market researchers who conduct, evaluate, and interpret the survey.

Reliability ensures that a survey measures reliably and that repeated surveys with the same questionnaire produce consistent results.

Validity ensures that a questionnaire asks exactly what is intended to be measured through the survey.

By meeting these criteria, surveys can produce accurate and valuable data for companies and researchers alike.

Interested in running your own study?

In our dashboard, you will find questionnaire templates that you can customize and get the insights you need to bring your brand to the next level.

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What is Convenience Sampling? Definition, Method, Examples

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5 Steps to Validate Your Business Idea

• 18 Aug 2020

You’ve come up with an innovative business idea, raised initial funding , and believe you have what it takes to be an entrepreneur . What’s next?

It’s time to validate your offering’s market potential.

What Is Market Validation?

Market validation is the process of determining if there’s a need for your product in your target market. Validating your business idea can enable you to reasonably predict whether people will buy your product or service, and whether your business will be profitable.

It’s important to validate your idea early in the entrepreneurial process to ensure you don’t waste time and resources creating a product that isn’t a good fit. Securing market validation can also instill confidence among investors, crowdfunders, and banks that are considering funding your startup.

By going through the process of validating your business idea, you can gain a deeper understanding of how your product does or doesn’t meet your target customers’ pain points. The insights you gain can help you create an offering that not only addresses your market segment’s needs, but earns you your first paying customers.

Here are five steps to determine the market validity of your venture.

Access your free e-book today.

5 Steps to Determine Market Validation

1. write down goals, assumptions, and hypotheses.

Writing down the goals of your business is the first step in market validation. The process of articulating your vision can illuminate any assumptions you have and provide an end goal.

Ask yourself:

• What’s the value of my product ?
• Who’s the target audience, and what assumptions have I made about them?
• What differentiates my product from existing ones?
• What hypotheses do I have about my product, pricing, and business model?

Answering these questions can help you communicate the value and differentiating factors of your product, and illuminate assumptions and hypotheses you’ve made that are yet to be tested and verified.

Related: How to Come Up With an Innovative Business Idea

2. Assess Market Size and Share

Before moving forward with your venture, estimate the size of your target market and the share of it you could potentially capture. By doing so, you can gauge your business’s potential and justify its launch.

In the online course Entrepreneurship Essentials , Harvard Business School Professor William Sahlman uses mattress retailer Casper to illustrate this idea. In 2014, Casper’s founders assessed the market size for their product by comparing its differentiating factors against the larger market. For Casper, these differentiating factors included its online business model, 100-day return window, and the viscoelastic foam material used in its mattresses.

Based on statistics for the mattress market at the time—including units sold per year, the percentage of the market owned by foam mattresses, and the number of mattress retailers that were e-commerce brands—Casper’s founders narrowed down which segments they should target, and determined they could own a few percentage points of the total mattress market share.

Do this exercise for your target market. For products similar to yours, research sales data, the number and share of current manufacturers, and what percentage of the total market your segment holds. Determine where your product fits into the market and assess how much of it your business could own.

3. Research Search Volume of Related Terms

Another way to gauge the market validity of your business idea is to research the monthly search volume of terms related to your product or mission. When consumers need a product or service, they often use a search engine to see what the market has to offer.

You can use a host of resources to look up monthly search volumes, such as Moz . In the case of Casper, a related search term might be “foam mattress.” According to Moz, the term garners more than 11,500 monthly searches, indicating a demand for the product.

If there’s not a lot of search volume surrounding your product, use terms that express customer intent. For instance, if you design a mattress made from a new, extra supportive material, you could look up how many people search for “best mattress for lower back pain sufferers.” Moz data indicates that the query yields 240 monthly searches.

This type of search volume for a longer, specific query isn’t negligible. In fact, it can be used to bolster your hypothesis that there’s a need for your product.

4. Conduct Customer Validation Interviews

Conducting interviews with your target market segment can be an effective way to learn about your product’s potential. This initiative might include hiring a market research company to conduct focus groups, sending out an online survey, or simply requesting a conversation with someone.

Ask potential customers about their motivations, preferences, needs, and the products they currently use. Circle back to the list you created in the first step of the market validation process, and frame any assumptions or hypotheses you made as questions to your interviewees. Be open to the feedback you receive and record it for future use.

The feedback may reflect that your product doesn’t have strong market validity, in which case, you can use it to improve your offering and repeat the market validation process.

Related: 7 Questions to Ask for an Insightful User Interview

5. Test Your Product or Service

Once you’ve determined there’s space for your product in the market, ensure you’re putting the most useful, intuitive version of it into the world. You can achieve this through alpha and beta testing.

• Alpha testing is when internal employees test a product in a staged setting. The purpose of alpha testing is to eliminate any bugs, issues, or idiosyncrasies in the product before it’s available to outside users.
• Beta testing is when a product is tested by a limited group of real, external users who are specifically told to identify problems. In the case of a software or app, beta testing might be open to the public with a notice letting users know the version they’re testing is unfinished.

Testing your product with real users can prove invaluable when assessing market validity. If there’s a need in the market, but your product is faulty, complex, or difficult to use, customers may opt for a competitor’s offering. The feedback you get from beta testers can help you better leverage and meet customer needs .

Turning Feedback Into Action

In Entrepreneurship Essentials , entrepreneurship is described as a “process of discovery.” To determine whether your product is a market fit, you must seek feedback to validate the beliefs you hold about your product offering.

Entrepreneurship requires flexibility and hard work. If you put in the time to outline your goals and assumptions, assess the market, interview potential customers, and conduct tests, you can gather the information you need to build the best version of your product.

Are you looking to turn your idea into a viable venture? Explore our four-week online course Entrepreneurship Essentials and our other entrepreneurship and innovation courses to learn to speak the language of the startup world. If you aren't sure which course is the right fit, download our free course flowchart to determine which best aligns with your goals.

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Market Validation

What is market validation.

Market validation is the process of presenting a concept for a product to its target market and learn from those prospective buyers whether or not the idea is worth pursuing.

This process typically takes place early-on in the conception stage, before any significant investment has been made in developing the product.

The two most common approaches to market validation are:

• Interview people in the target market, such as the buyer and user personas.
• Send out surveys to these personas.

The key is that market validation research must include direct contact and feedback from people in the product’s intended market.

Why is Market Validation so Important?

There are many reasons why an organization conducts market validation before committing to the development of a new product or service. Here are some of the key benefits:

It helps secure funding and resources.

For an existing organization, the product management team would need to present its executive staff with evidence of market validation before execs green light the project and allow the product manager to begin assigning a budget, development time, marketing tasks, etc.

For an entrepreneur seeking funding for a new product idea, venture capitalists and other types of investors required evidence of market validation before agreeing to fund the entrepreneur’s company.

Beyond its ability to help teams secure resources to bring their product concept to reality, it’s an inexpensive way to uncover problems with your product idea.

When an organization comes up with an idea internally for a new feature or an entirely new product, the idea might at first seem viable, even ingenious.

But until that product team subjects its idea to a true test—for example, conducting customer validation interviews to learn whether or not they would be interested in the product—the team could be missing the following major flaws in the idea:

• Target users don’t need a standalone solution to solve the problem your product concept addresses and they’ve already discovered a simple and inexpensive workaround that they’re satisfied with.
• The consensus is while they like the idea, they don’t think it’s important enough to pay for.
• The companies in your target industries don’t allow enough budget for your solution.

For these reasons, even a good idea can fail to achieve the all-important objective of product-market fit . The more development work your team has done before you discover whether your product will fail in the market, the more expensive that failure will be.

The value of market validation is that your organization can uncover those problems before committing any significant time or resources to a product concept. That makes this the most inexpensive way to learn that an idea isn’t worth pursuing.

How do you Conduct One-on-One Interviews for Market Validation?

The market validation process varies by company. It’ll also vary by industry and the type of user persona the product team is seeking feedback from. Different demographics will have their own preferred methods of communication.

Here is an outline of the broad steps you will want to take:

1. Prepare a clear and simple explanation of your product concept.

Develop a straightforward and easy-to-grasp description of the product concept that you can quickly share in your customer interviews.

Part of this step will also include thinking through some key details such as:

• Who are your customers
• What specific problem you believe they have
• How the product would solve that problem.

Answering these questions will also help you with the next step, which is figuring out which people to interview.

2. Find your ideal interview subjects.

Now it’s time to build a list of people to interview. If you know people in the target market for your product concept, you can start with them. That’s a quick way to begin compiling feedback.The downside to this approach is that these interview subjects will be more subjective and biased than you need from your interview subjects.

As you broaden your search for target personas to interview, it’s important to communicate let what the target persona will gain in exchange for giving you their time.

For example, explain that if they agree to speak with you about your product concept, you’ll either invite them to be among the beta-testers of the product or they’ll receive the product for free for an extended period of time after the launch.

3. Create your interview questions.

This is an important step because the way you frame your questions can have a strong influence on how your target users perceive your product concept.

We recommend you focus your questions not on your product but on the problems facing your target users and how they currently deal with those problems today. Use open-ended questions. They let your interview subjects answer the topics in their own words.

For more guidance on interviewing, read our blog post on how to create customer interview questions .

4. Conduct the interviews.

You can generate viable market-validation findings from only a handful of in-depth interviews, assuming you have identified the right people to speak with. The more interviews, the greater the sample size, the better. That way you can see the broad patterns or even discover new problems for these personas that you hadn’t considered.

We recommend a single product manager lead these interviews because typically the product manager will have the deepest knowledge in the organization about the target persona, the market, and other important strategic details. But if you have lined up too many interviews for a single person to conduct—a high-quality problem to have—you can also share the responsibility with another product manager or even a product marketing manager.

It is very important, though, to make sure everyone running a market validation interview starts with the same questions. Then eventually each conversation will take its own path. That’s okay. But you need to make sure that each interview also yields answers to the same questions, so your team can intelligently analyze the data.

5. Make sense of the data.

After you’ve conducted all of your interviews, pull together the details of each to help you answer the key question:

Did the market validate my product concept as viable and worth investing in?

Look for patterns in the answers, such as:

• Your product solves a large enough problem that the market would pay to resolve it.
• Your target users haven’t found another solution yet to this problem.
• The industries you are targeting with this product concept do indeed have a budget to spend on addressing such issues.

If you find a trend of answers like these, congratulations, you might have a market-validated product concept! At this point, you’ll want to summarize this data in an easy-to-understand format. This can help you earn approval and enthusiasm from your executive team, your company’s other stakeholders across departments, and investors.

Market validation: no product development should begin without it

Many organizations are so enthusiastic about their revolutionary product idea that, in their rush to bring it to market before another company beats them to it, they skip the market validation process and jump straight into product development.

However, there might be a good reason that a competitor hasn’t already developed a similar concept. It might not have a large enough total addressable market. Perhaps most target users view the product as a “nice to have” but not worth paying for. Those users might already have another solution to the problem—one that doesn’t require any product. Or maybe the market has seen several failed solutions and is now unwilling to give a new product a try.

Your organization shouldn’t spend a significant amount of time or money developing a product that would fail. To ensure this doesn’t happen, you should always conduct market-validation research early-on in the concept stage of any new product. Uncover any problems before they become costly development mistakes!

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Tomsk State University

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Established in 1878, the Tomsk State University is a non-profit public higher education institution located in the urban setting of the large city of Tomsk (population range of 500,000-1,000,000 inhabitants), Tomsk Oblast. Officially recognized by the Ministry of Science and Higher Education of the Russian Federation, Tomsk State University (TSU) is a large-sized (uniRank enrollment range: 10,000-14,999 students) coeducational Russian higher education institution. Tomsk State University (TSU) offers courses and programs leading to officially recognized higher education degrees such as pre-bachelor's degrees (i.e. certificates, diplomas, associate or foundation), bachelor's degrees, master's degrees and doctorate degrees in several areas of study. See the uniRank degree levels and areas of study table below for further details. This 146-year-old Russian higher-education institution has a selective admission policy based on entrance examinations. International applicants are eligible to apply for enrollment. TSU also provides several academic and non-academic facilities and services to students including a library, sports facilities, study abroad and exchange programs, online courses and distance learning opportunities, as well as administrative services.

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What is the difference between comprehensive/generalist and specialized universities in terms of the range of fields of study they offer, degree levels available and academic and carreer paths pros and cons? Read our guide article about generalist and specialized universities to learn more.

Fields of Study and Degree Levels Matrix

The following Tomsk State University's Fields of Study/Degree Levels Matrix is divided into 6 main fields of study and 4 levels of degrees, from the lowest undergraduate degree to the highest postgraduate degree. This matrix aims to help quickly identify Tomsk State University's academic range and degree level offering.

This University offers courses in at least one of the following subjects:

• Applied Arts
• Museum Studies
• Performing Arts
• Religion and Theology
• Visual Arts
• Other Arts & Humanities Studies
• Accounting / Finance
• Anthropology / Archaeology
• Business / Commerce / Management
• Communication and Media Studies
• Development Studies
• Library and Information Science
• Physical Education / Sport Science
• Political and International Studies
• Social Policy / Public Administration
• Social Work
• Sociology / Psychology
• Tourism / Hospitality
• Other Business & Social Science Studies
• Aboriginal / Indigenous People Studies
• African Studies
• American & Caribbean Studies
• Ancient and Modern Languages
• Asian Studies
• English Studies
• European Studies
• French Studies
• Germanic Studies
• Indian / South Asian Studies
• Italian Studies
• Middle Eastern Studies
• Portuguese Studies
• Russian / Eastern European Studies
• Spanish Studies
• Other Language & Cultural Studies
• Anaesthesia
• Biomedical Science
• Dermatology
• Medicine / Surgery
• Natural / Alternative Medicine
• Obstetrics / Gynaecology
• Optometry / Ophthalmology
• Orthopaedics
• Otorhinolaryngology
• Radiography
• Speech / Rehabilitation / Physiotherapy
• Other Medical & Health Studies
• Aeronautical Engineering
• Agricultural Engineering
• Architectural Engineering
• Biomedical Engineering
• Chemical Engineering
• Civil and Environmental Engineering
• Computer and IT Engineering
• Electronic and Electrical Engineering
• General Engineering
• Geological Engineering
• Industrial Engineering
• Mechanical / Manufacturing Engineering
• Mining and Metallurgical Engineering
• Other Engineering Studies
• Agriculture / Forestry / Botany
• Aquaculture / Marine Science
• Architecture
• Biology / Biochemistry / Microbiology
• Computer / Information Technology
• Energy / Environmental Studies
• Food Science
• Mathematics / Statistics
• Neuroscience
• Pharmacy / Pharmacology
• Textiles and Fibre Science
• Zoology / Veterinary Science
• Other Science & Technology Studies

Notice : please contact or visit the university website for detailed information on Tomsk State University's areas of study and degree levels currently offered; the above matrix may not be complete or up-to-date.

Programs and Courses

Courses and programs.

Click here to explore a list of Tomsk State University courses and programs or, if not available yet, search for them with our Search Engine powered by Google. We are constantly adding university courses and programs worldwide with the cooperation of university representatives.

You can also explore our new A-Z Guide to 8,100 University Programs, Courses and Degrees to learn more about study outlines and typical duration, tuition ranges, career prospects, salary expectations of each course/program/degree.

Tuition Fees

Yearly tuition fees refers to the amount of money that a student is charged by a University for one academic year of full-time study. Read our guide article about tuition fees and financial aid options to learn more.

Yearly Tuition Fees Range Matrix

Tip: search for Tomsk State University's tuition fees with the uniRank Search Engine

Notice : please contact the university's Admission Office for detailed information on Tomsk State University's yearly tuition fees which apply to your specific situation and study interest; tuition fees may vary by program, citizenship/residency, study mode (i.e. face to face or online, part time or full time), as well as other factors. The above matrix is indicative only and may not be up-to-date.

Applying for admission is the first step towards achieving students' academic and career goals and accessing the many opportunities and resources that a university has to offer. Read our " Introduction to University Admissions " article to learn more.

Admission Information

uniRank publishes below some basic Tomsk State University's admission information.

Gender Admission

This institution admits Men and Women (coed).

Admission Selection

Has Tomsk State University a selective admission policy? Yes, based on entrance examinations.

Admission Rate

Tomsk State University's acceptance rate range is not reported.

International Students Admission

International students are welcome to apply for admission at this institution.

Admission Office

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Notice : admission policy and acceptance rate may vary by areas of study, degree level, student nationality or residence and other criteria. Please contact Tomsk State University's Admission Office for detailed information on their admission selection policy and acceptance rate; the above information may not be complete or up-to-date.

Size and Profile

University size and profile can be important factors to consider when choosing a university. Here are some potential reasons why University size and profile can affect students when choosing a university .

uniRank publishes below some major size and profile indicators for Tomsk State University.

Student Enrollment

Tomsk State University has an enrollment range of 10,000-14,999 students making it a large-sized institution.

Academic Staff

This institution has a range of 1,000-1,499 academic employees (Faculty).

Control Type

Tomsk State University is a public higher education institution.

Entity Type

Tomsk State University is a non-profit higher education institution.

Campus Setting

This institution's main campus is located in a Urban setting.

Academic Calendar

This institution adopts a Semesters type of academic calendar.

Religious Affiliation

Tomsk State University does not have any religious affiliation.

Facilities and Services

What are the most common University facilities and services? Read our two guide articles about University Facilities and University Services to learn more.

University Facilities

uniRank provides below an overview of Tomsk State University's main facilities:

University Library

University housing.

Not reported

Sport Facilities/Activities

This institution features sporting facilities and organizes sports activities for its students.

University Services

uniRank provides below an overview of Tomsk State University's main services:

Financial Aid

Study abroad.

This institution offers study abroad and exchange program opportunities for its students.

Distance Learning

This institution provides a distance learning mode for certain programs or courses.

Academic Counseling

Career services.

Notice : please contact or visit the university website for detailed information on Tomsk State University's facilities and services; the information above is indicative only and may not be complete or up-to-date.

Recognition and Accreditation

There are different types of legal recognition and quality assessment of higher education institutions around the world, depending on the country and its legal and higher education system... read our article about university accreditation and recognition to learn more.

Institutional Recognition or Accreditation

Tomsk State University is legally recognized and/or institutionally accredited by: Ministry of Science and Higher Education of the Russian Federation

Specialized or Programmatic Accreditations

Not available; please use the Feedback/Error report form at the end of this page to submit a list of Tomsk State University's official programmatic or specialized accreditations. If you are an official representative of this university you can also claim and update this entire university profile free of charge (UPDATE ALL).

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Important : the above section is intended to include only those reputable organizations (e.g. Ministries or Departments of Higher Education) that have the legal authority to officially charter, license, register or, more generally, recognize Tomsk State University as a whole (institutional legal recognition), accredit the institution as a whole (institutional accreditation) or accredit its specific programs/courses (programmatic accreditation).

Memberships and Affiliations

University memberships and affiliations to external organizations can be important for several reasons... read our article about university affiliations and memberships to learn more.

Affiliations and Memberships

uniRank publishes the following list of the most important Tomsk State University's affiliations and memberships; feel free to submit any relevant missing higher education-related organizations this university is affiliated with.

• European University Association (EUA)

Academic Structure

Academic divisions can provide valuable insights into the range of fields of study and disciplines a University focuses on and the institution's level of specialization. Comprehensive or Generalist Universities typically offer a wide range of academic programs and have many academic divisions and subdivisions across different disciplines, while Specialized Universities tend to focus on a narrower range of programs within a specific field or industry and have fewer academic divisions and a simplified organizational structure. Read our guide article " Understanding Academic Divisions in Universities - Colleges, Faculties, Schools " to learn more about academic divisions and typical university organizational structures.

uniRank shows a structural diagram of the first-level academic divisions of the Tomsk State University 's organizational structure; feel free to submit any relevant missing division.

Social Media

Social media can be a powerful tool for Universities to communicate with current students, alumni, faculty, staff and the wider community. But how can social media be important for prospective students? Read our article about the importance of Social Media for universities and prospective students to learn more.

uniRank publishes brief reviews, rankings and metrics of some Tomsk State University's social media channels as a starting point for comparison and an additional selection tool for potential applicants.

X (Twitter)

Tomsk State University's main LinkedIn profile

Free Online Courses

Open education global.

This higher education institution is not a member of the Open Education Global (OEGlobal) organization that is developing, implementing and supporting free open education and free online courses. View a list of Open Education Global members by country .

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Tomsk State University's Wikipedia article

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Feedback, Errors and Update

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Site last updated: Wednesday, 28 August 2024

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A pilot screening of prevalence of atopic states and opisthorchosis and their relationship in people of Tomsk Oblast

2007, Parasitology Research

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Maria Prisco

Izabela Kupryś-Lipińska

Introduction: A dramatic increase in the prevalence of atopic diseases can be observed. The reasons for this phenomenon remain unclear. Aim: To compare the prevalence of atopic diseases in subjects living in the city centre and a rural area. Material and methods: The study was done on a randomly chosen group of inhabitants of Lodz province, aged 3 to 80 years, living in two different areas: the city centre and a rural area. Demographic data and the anamnesis were collected on the basis of standardised questionnaires. Additionally, skin prick tests and screening spirometries were performed. Results: The complete data from 482 subjects living in the city centre and 469 in the rural area were included in the analysis. Asthma prevalence in the city centre was estimated at 13.2% in adults and 18.4% in children compared to 4.2 and 6.0% respectively in the rural area. The prevalence of seasonal allergic rhinitis in the city centre was 13.2% in adults and 16.1% in children, in comparison to...

Online journal of biological sciences

Alexandra Tegza

Clinical & Experimental Allergy

Silver Siiak

Journal of Parasitic Diseases

Amin Ahmadi

PLoS Neglected Tropical Diseases

Hafizatul Zan

Suez Canal Veterinary Medical Journal. SCVMJ

Eman Youssef

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