Market research 2.0 — The Test it way of proving concept.

How we conduct Market research

When starting a new business or launching a new product or service, you need to validate a series of assumptions in order to convince yourself and/or investors to help you build your solution. For example: If the problem you’re trying to solve exists, if the audience you’re trying to provide a solution to really exist, if that audience is willing to pay for your solution and if your solution is really gonna work, how much money you have to spend to acquire a new customer, just to name a few.

We aim to find an answer to those assumptions as quickly as possible by testing these assumptions on the market with real buying customers in a low-risk environment. We call it ‘the Test it process’.

Let’s break it down by using one of our recent Test it cases as an example:

LaverVert is a 100% ecological laundry detergent entirely made in Belgium. Great! But how do we know if this solves a real problem? And how do we prove people want to pay the product? How much marketing do we have to spend to sell one bottle of detergent?

To find the answers to those questions we start by sitting down with the entrepreneur/ company in question to really get an insight on what they think the problem they’re trying to solve looks like and what solution they have for it.

In the LaverVert Case, these were the questions we really wanted answered:

  • What’s a good price for our product?
  • What packaging sells best? (Box or Bottle?)
  • Who’s our target audience?
  • Age range? Gender? Location?
  • What’s the best placement for our ads? (Desktop? Mobile? Instagram? Messenger? Google?)
  • What’s our Customer Acquisition Cost (CAC)?

Here is how we found out:

After we sat down with the entrepreneur or company, in what we call, the Kick-off meeting, we start with some preparational work. Step one is to build the main testing tool. It looks like a one-page website, but it’s really a carefully crafted landing page optimized for tracking and assumption-proving.

The Test it will be carried out on 3 one-week sprints. In each sprint, we prioritize what assumptions are most important and what assumptions we should test first. Between sprints, we measure all results and set priorities for the next.

A visual of the test scenario: The Facebook or Google ads (to draw people in), The landing page (to give people more information), and the Conversion (objective of the scenario).


Yaas!!! We’re ready to get started. Now that we built our testing tools, it is time to test our pre-determined assumptions. We do that by making dozens of Facebook/Google ads who are carefully crafted to prove one assumption at the time, keeping in mind the order in which we can prove all our assumptions. For example in our LaverVert case, we tested 4 main assumptions in V1:

  • PROBLEM 1: High price
    Fed up with laundry products that cost a fortune? Discover LaverVert !
  • PROBLEM 2: Chemical products
    Fed up with laundry products filled with chemicals? ⚗Discover LaverVert !
  • PROBLEM 3: Skin reaction
    Fed up with laundry that causes skin reactions? Discover LaverVert !
  • PROBLEM 4: Manufacturing difficulty
    You want to make your laundry yourself but you find it too complicated? Discover LaverVert !

Now the creative/experience part of the operation kicks in. Our team has to create 4 evenly appealing pieces of text, images and descriptions to get a fair reading of how many people click on the ad because they designate with the problem. Here’s an example of what the LaverVert ads looked like and a description of their components.

We analyze our results using different metrics, most importantly, our CTR (Click Through Rate), the CPC (Cost Per Click), the CAC (Customer Acquisition Cost), and our general audience insights (where they live, age, interests, etc.).

Conclusion V1

So what do these number mean? Well, by looking at the CTR (Click Through Rate) and the CPC (Cost per Click) we can see that both audiences are responsive to our ads. Usually, a good campaign has a CTR from 1,6% and up. So in this case, having a 3,39% and 3,55% is exceptional so we will definitely keep testing both audiences. We can also see that our CPC (Cost per Click) is very low. It only costs us €0,17 to get someone to visit our website. In this case, because the conversion is low, that’s something we can’t analyze yet.


After completing V1, we can convert our hypotheses into a real action plan based on real numbers. Now we can start to optimize our strategy to target people most interested in our laundry detergent. In this case, we’ll again test 4 different hypotheses:

  • PROBLEM 1: Composition of laundry products
    Fed up with laundry products whose composition is unclear? Discover LaverVert !
  • PROBLEM 2: Chemical products
    Fed up with laundry products filled with chemicals? ⚗Discover LaverVert !
  • PROBLEM 3: Skin reactions
    Tired of laundry products that cause skin reactions? Discover LaverVert !
  • PROBLEM 4: Respect the environment
    Tired of using laundry products that do not respect the environment? Discover LaverVert !

We basically repeat what we’ve done on V1, but optimized to its results. By targeting people with the lowest CPC (Cost per Click) or highest conversions. In the LaverVert case, we also tested what products people were more likely to buy. Bottles or Crates of Laundry detergent. These metrics can be found on the landing page, by measuring how many people buy product A/B or even how many click on both products. We found out that the boxes sold slightly better than the bottles (just FYI 😉).

V3 — Conclusion

Remember those assumptions we made in the very beginning? In just 3 weeks, we found:

  • A good price for our product (€5,30/L)
  • What packaging sells best (Bag-in-Box)
  • Our target audience (Age range, Gender, Location)
  • The best placement for our ads (Desktop ads, Mobile ads, Google)
  • Our Customer Acquisition Cost (€7,76)

…All by testing every assumption in a very-close-to-real-market scenario.

If you want to learn more about our ‘Test it’ methodology, you can view some use cases HERE or go to our website:

Thanks for reading!

What is Make It?

We build Startups. Since 2014, we’ve successfully developed what we describe as ‘a machine’ to test, launch and/or grow startups by working with over 200+ entrepreneurs and building our own. We strongly believe in the ‘Test It’ mentality: test fast, fail cheap, and try again.

Are you ready to Make it happen? 
Let’s see how we can help!