Case Studies

How to test a product idea? The MVP of a marketing strategy and a sequence of experiments

jak testować pomysł na produkt


a manufacturing company in the home & living industry


development of an idea for a product that appeals to the target group

Problem to solve

how to increase the chances of the product’s success on the market?

Number of sprints

12, including 7 sprints of experiments (described in this case study)

Number of people in the project

2-5 depending on the period


Project background

In the fall of 2021, we met a home & living brand with a passion for circular economy* and a lean way of working. Its team was keen to create physical products that support the idea of zero waste and closed cycles.

The company has its machine park, so it doesn’t need much time from developing an idea to launching production. It was crucial for them not to design and produce something that would not meet with a positive response from users or something that can’t be reused and at least partially recycled.

Therefore, they decided to experiment and test their ideas in a three-way collaboration with us and an industrial design and strategic consulting studio.

Together we planned over a dozen sprints for research, ideation, and validation. Preparations for product design are in progress.

In this case study, you will read about the third phase of the project – validating the product idea with an MVP of the marketing strategy and experiments.

The circular economy, or closed-loop economy, is a model in which products and materials they are made of circulate for as long as possible. You can read more about the circular economy on

Starting point: the idea(s)

During the experimentation phase, i.e., from the 6th sprint onwards, we were validating one specific idea for a set of furniture and accessories available in a subscription model for a certain demanding target group*.

Before this happened, we went through the stage of ideas generation and subsequent expansion and narrowing the pool of ideas based on the Double Diamond model.

You can read more about the model and its application in the Product Discovery process in the article Product Discovery Process – how to discover user needs.

On the one hand, we relied on the brand creators’ business knowledge as well as current and forecast production capabilities estimated in the circularity audit conducted by our partner. On the other hand, we drew on netnography and desk research conducted by both teams. However, this is a topic for a separate case study.

Importantly, the idea to be tested was selected from a pool of 3 with the highest chance of success. It is worth mentioning that the selection was made based on the research on the target group potential and our client’s production capabilities. For this purpose, we used the prioritization method worked out by Project: People and our partner.

* We skip the details because the work on the product is still in progress 🙂

Why test the product idea before it is manufactured?

First, the cost of the research process is lower than designing, making, and distributing products. It can be done efficiently in a different way: create a prototype and check how it sells to the target group. Our client had conduct was not among the brand’s customers. Therefore, “in production” and “sales” tests could yield distorted results.

Secondly, we planned an innovative sales model in the context of furniture, namely subscription. We needed to check the readiness of the target group for such an offer. We also wanted to understand their needs, which might influence the shape of the model and inspire some changes.

Finally, we wanted to secure the possibility of a swift pivot without having to recalibrate the production. And this, in turn, required us to validate the entire business model. We assumed that a new brand could be created under the umbrella of the client company. It required us to validate the entire business model.

What test the product idea with users?

On the one hand, we needed a specific product concept, the principles of operation, or rough sketches (which is very important – they were not final visualizations). We wanted to check how the group would react to the possible form of the product, its functions, applications, etc., before spending money on the design, production, and distribution.

On the other hand, we needed at least a preliminary version of a marketing strategy, i.e., strategy MVP. MVP is a way to check whether how we talk about the product and the value it provides appeal to users in terms of form, content, or channel.  It was vital to assess whether the product had the potential of being useful and popular before spending the budget on a full-scale marketing campaign. 

We were working on the strategy MVP, and our partner on the product concept. This division was improvisational and referred to the scope of work (our partner – design, Project: People – communication) as the teams collaborated and communicated all the time.

What is the MVP of a marketing strategy?

The Minimum Viable Product of a marketing strategy, or the Minimum Viable Strategy, allows you to achieve the same goals as with a full-blown strategy – to reach your audience with your story about the product. 

We introduced it at Project: People when we started approaching marketing strategies for innovative products the way we approach products themselves – that is, we assumed testing. 

The elements of a marketing strategy in the MVP version are not elaborate or fully validated. They are a set of assumptions (based on, for example, desk research or competitive analysis) regarding what the final strategy should look like. 

In the course of work on the strategy, analyses, and subsequent research with users, we check how particular strategy elements correspond with reality. If necessary, we update it. This approach works especially well for new initiatives, products, or services entering the market.

The MVP of the strategy in this project included, among others:

  • target group details, descriptions of persons and their problems (developed based on desk research and netnography), 
  • dependencies within the problem-solution fit, 
  • unique value proposition and arguments that would convince potential customers to purchase the products, 
  • communication channels and activities in a marketing funnel (I will return to the topic of a funnel because it had a considerable influence on the sequence of experiments),
  • basic branding elements such as tone of voice, logo, slogan, and visual identity (importantly, these elements were created for the test brand with the assumption that the final branding would be different – it was important for the client to remain anonymous and to prevent the competition from stealing the idea).
The first version of the marketing funnel with channel prioritization. The abbreviated version of the funnel (green cards) served as the basis for determining a sequence of experiments in the next stage.
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You could say we tested the product narrative before it was even created. Our goal was to check whether the language of benefits we assumed for this product appealed to the audience. On the other hand – we wanted to create a real solution to the users’ problems, so we invited them to share their experiences and influence the final shape of the product. 

We openly informed that the product was at the concept stage. On a landing page where the research participants could learn the details, we added a form to sign-up for a waiting list. 

The landing page and the ads campaign served as a link between the marketing funnel and the lean UX experiments we conducted. You will read more on that below.

What experiments did we plan to test the product idea?

We planned a series of sequenced tests to validate the product idea visualized and described in the form of a marketing strategy MVP. We based it on the previously built marketing funnel.

In short: we wanted to attract the audience’s attention with a paid social media campaign. The ads contained sketches of products and text on the value proposition. From the ads, we directed users to a landing page where they could sign up for a waiting list to be informed about the sales launch. They automatically subscribed to a newsletter with news related to the product. It was also a way to distribute a survey and select people for an in-depth study in the form of an interview.

Why such an approach? It allowed us to simulate the natural experience of getting to know the product – from the stage of building awareness of the product to the purchase intent. It was to help us see how users would react to the product if it were already on sale.

The sequence was as follows:

  • Attract, as in the marketing funnel, it was the first touch point with the brand. We planned activities such as Facebook Ads and Instagram Ads campaigns, to name a few. At this stage, we also conducted A/B targeting tests in Ads,  A/B tests of the most effective advertising channel, and an analysis of web search trends.
  • Show value was the stage where the audience learned more about the value proposition. We presented it along with product sketches on a dedicated landing page. Users could sign up for a waiting list to be informed about the product launch. At this stage, after A/B testing in the previous phase, we ran an A/B test of the landing page design (created in Webflow) using Google Optimize.
  • Show proof & build trust is the stage in the marketing funnel meant to increase credibility. Finally, we set up basic social media channels (Facebook, Instagram). On the one hand, they served us to launch the campaign, and on the other hand, they allowed the audience to get acquainted with the brand in an additional channel.

Experiments sequence with objectives and metrics based on the marketing funnel 
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  1. The loop – establishing regular contact with the target audience through a newsletter, which they received after signing up for the sales launch waiting list. We assumed the newsletter would include content about the product and tips related to the target audience’s interests. At this stage, using Mailchimp, we planned to analyze the open rate, unsubscribes, and clicks on links in emails.
  2. Ask for feedback – in this phase, we planned to send out a survey to the newsletter subscribers asking for feedback on the product. It meant introducing an additional quantitative survey apart from the A/B test and website traffic analysis. 
  3. Meet them in person – that is, qualitative research in the form of in-depth interviews, also with the newsletter recipients.

This way, users were to move from their first contact with the product online, through the subsequent stages of the funnel, to direct contact with the creators (in this case, the researchers). In the buying process, this would be the contact with customer service.

What is important, except for the interviews, the experiments in the funnel (e.g., various A/B tests) weren’t simultaneous because that would impair their credibility. We would not know what factors influenced specific results.

We described the results of the experiments in Miro (below).
The client had access to it in real time.

Example of documentation and analysis on the experiment cards
[Get access to the experiment card template on our Miro]

All right, but what was the point of all this? What was effect of all experiments in the sequence?

Each step in the sequence of experiments was measured (see the visualization below for details) and gave us specific information.

Measuring the sequence of experiments
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At the Attract stage, we studied:

  • value proposition, claim,
  • cost-effectiveness of the channels.

The Show value stage gave us information about:

  • interest in the solution,
  • information needs (based on the behavior on the website),
  • the best version of the offer, attractiveness of the solution to the target group.

At the Loop stage, we studied:

  • the target group’s readiness to interact with us,
  • feedback on the idea,
  • the target group’s problems and needs.

And at the Ask for feedback and Meet them in person stages:

  • feedback on the idea,
  • the target group’s language, the way they express themselves,
  • alternative solutions.

In addition, each stage added to our knowledge about channels for communicating with the target group, its demographics, and interests.

What surprised us about this project?

It would be unusual if the research process did not surprise us with anything. Once again, for certain reasons, we had to reverse the order of experiments and start with in-depth interviews. We recruited subjects not through the developed funnel, but in forums and social media groups using the snowball method.

We launched the Ads campaign directing to the landing page and the newsletter a few weeks later. It also forced us to make changes when it came to distributing the survey. Because of changes in the order of the experiments, we did not manage to build a big enough base of newsletter recipients that would have enabled us to collect binding results in the survey. Therefore, in the end, we used the Survey Monkey tool.

What did our process give Product Owners?

  1. Validation of the product and subscription service and the information about which decisions are a good direction and which need a pivot
  2. Information about which areas are worth deepening and refining
  3. Insights on the target group’s habits (both in terms of purchasing and using the product) that influence the business model and product design
  4. Information on the problems and needs of the target group
  5. Validation of the product’s value proposition
  6. Additional possible directions for development

What did we learn?

First – it’s worth being ready to improvise and reverse the plan – as we did with the sequence of experiments.

Second – in such a multi-phase, long, and complex process, in addition to a full research report, it is worth preparing an Executive Summary for key stakeholders (especially if they are not in the process every day). 

Tools (to name a few):

  • Facebook Ads
  • Instagram Ads
  • Miro
  • Webflow
  • SurveyMonkey
  • Experiments card
  • Hotjar
  • Google Analytics
  • Mailchimp
  • Figma

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