Business and concept validation through qualitative and quantitative data

Validation is the process of gathering evidence and learning around business ideas through experimentation and user testing, in order to make faster, informed, de-risked decisions. Validation techniques are usually divided into two main categories, relating to the type of information being collected - either qualitative or quantitative. Here's how you can use them.

Quantitative research tells you whether to choose black or yellow

Quantitative research gets you numerical results. These can be graphs, percentages, or amounts. Quantitative research is used to test assumptions, and validate or invalidate them in relation to the subjects or topics they offer insights about.

Quantitative insights are usually studied, compared, and recorded through statistical outputs or close-ended questions. The goal is to reach an absolute or binary outcome. In other words, results that will tell you to choose left or right, black or yellow. 

The pro's

Powered by numbers, quantitative research can be used to reach millions of users using different types of digital validation paths, such A/B testing. Social media platforms are one of the quickest ways to gain access to many users at a relatively low cost. Facebook Ads, and 1Q are a couple of examples of tools you could use to gather quantitative data. 

The con's

We refer to quantitative research as a binary tool. This means the results you get from them are quite the rigid outcome. They’re perfect for hard-data collection, but they’re not the best way to test abstract ideas or concepts. 

Reaching a massive audience will be another challenge, depending on the industry you work in. Take healthcare for instance; if you are looking to test out a new innovation or service for oncologists, launching Facebook ads to test and validate may not be the best channel. Validation and experimentation aimed at your target segments’s preferred digital spaces is often the way to go to tackle this obstacle. You can choose to validate your ideas on the platforms or social media sites your target audience visits. Always bear in mind that hyper-specific target personas are not easy to find in larger quantities. 

the fix

Depending on what you’re looking for, this type of research might not be the right fit. But, if you can’t find a specific audience to test, you can always go through public studies and look for data correlation. Based on information association, you’ll be getting information to help you move your experiment in a certain direction or according to a pattern in particular. 

You can switch to qualitative research if quantitative insights don’t produce the results or numbers you’re looking for, or better yet, find audiences you can compare your patterns with.  For example, if it is not possible to retrieve data related to the age group you’re looking into, spotting another audience that mirrors your ideal one can replicate results based on previous research patterns. 

concept validation with Quantitative Research: Some Ground Rules

1. Consider statistical significance
Quantitative research aims at reaching an “absolute”. So, you should be taking
statistical significance into account. You want to make sure your results are likely to be replicated if the test is conducted more than once.

2. Select the right variables
Design your experiment so that it pinpoints the right variables. The variable you’re putting to the test should be the only thing that changes. For example, if you’re testing a message; with every iteration of the experiment, the message should be the only thing that varies. That means staying consistent on for example visuals, target audience, timing, location, and so on. By adding an additional complexity layer, it’s impossible to tell why a user preferred one iteration over the other.

3. Break down your experiment into smaller pieces
If you’re testing multiple things, make sure you focus on the ones that are priorities, and then proceed to test them one at a time. By doing this, you can iterate your tests based on the results. This will simplify the way you digest the final results. 

Now that you’ve got the hang of quantitative concept validation and experiments, we can start by taking a look at what the other kind looks like.

Sample output of an experiment through quantitative research

Qualitative research tells you why your users prefer black

As suggested by its name, qualitative research is related to words, conceptual insights, and consumer thoughts. The goal of this type of research is to dive deep into users’ minds and experiences. It focuses on topics that are harder to grasp and understand, given their abstract nature. Qualitative research generally looks into the reasons that drive human behavior and mindset. 

The pro's

Qualitative research goes deeper into theory and hypothesis analysis. It helps you build a storyline from ideas you’ve gathered. This is useful to narrow down what should be tested quantitatively by detecting pain points and extracting information from complex narratives.

Engaging in qualitative research opens the doors for you to be in contact with first-hand consumer experiences, expectations, and concerns. Whether you’re in the B2B or B2C industry, qualitative research helps you acquire an empathic understanding of your market, enabling you to respond directly to it.

The con's

Having one-on-one conversations with consumers can be expensive, especially when looking at a delimited target niche or people with very specific experiences. Because of the complexity and resources required to conduct qualitative research, you usually deal with a small number of users. On one side, this can pose as a benefit if this type of research is part of your entire validation process. However, you shouldn’t rely solely on a single round of qualitative tests to make critical decisions.

the fix

There are plenty of budget-friendly solutions. One of them is to start looking into your internal circles – you may have easier access to an ideal user than previously expected. If you have a budget that allows you to expand the reach of your research, platforms such as Look Look, Dovetail, and Hello Ping Pong are all excellent options to help you navigate this process. 

concept validation with qualitative research: guidelines and recommendations

1. Getting your questions right
Asking the right questions is fundamental to make the most out of qualitative research. For it, creating an interview guide will help you set the right questions in place. Remember to focus on reaching insights, so that you can avoid confirmation bias. Check out this article on 16 cognitive biases that can kill your decision making.

2. Use alternative means
Recruiting very specific profiles for interviewing is a challenge. One way to approach this is starting an expert panel. This is a way to keep tapping into industry knowledge several times as your validations and experiments move forward.


3. Dare to go beyond traditional interview handbooks
Interview guides shouldn’t begin and end with a list. Visual cues, prototypes, videos – don’t be afraid to use all tools you think might help trigger a desired behavior. This is how you’ll find ways to capture more than your segment’s attention. While you should try and go beyond the guide,
here’s an empathy interview guide to get you started.

Concept validation and testing through research

Quantitative research should be a go-to if you’re in the B2C industry or product development. If you’re unsure about your field being suitable for this type of research, you can begin by checking if you can target your target audience in the platforms you’ll be using to experiment.

Do these people use social media?

If not, which platform are they frequently on?

Is there a way for my experiment to reach that platform?

The answers to questions such as these will help you navigate your options and conduct your validations and experiments in the right place, and in the right way. Let us not forget about the role of qualitative research in this process. You see, this type of research will work wonders when combined with quantitative insights. 

In the end, this is the essence of validation and experimentation – involving milestone stops that will help you navigate tricky assumptions. Whatever your goal is, make sure you decide which experiments will work best according to your organization and your industry.

If you’re not exactly sure why experiments should be part of your innovation strategy, make sure you check out how valuable experimentation is when making decisions in the business world. 

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more on validation and experimentation

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Will your business idea work? Find out. This free guide features 24 validation experiments to help you test your hypothesis & de-risk business decisions.

Case: digital validation sprint with Ferring

Check out this story of how we ran a digital validation sprint for Ferring Pharmaceuticals, to help them prioritize the value proposition of a new digital health solution

Thanks for reading!

I’m Mina Drezner – Experiment and Prototype Lead. Spreading innovation culture is in our DNA – if you liked the read, contribute to our mission by sharing this article.

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