3 Priceless Case Studies by Admitad Startups that Prove: It’s Okay to Build Cheap MVPs

Three entrepreneurs from Admitad Startups shared their experience of creating Minimum Viable Products. Check these case studies and see how you can save on developing your own MVP

MVP, or Minimum Viable Product, is a vital concept for startup development. It’s a reduced version of a product that is used to validate a hypothesis (or prove its non-viability). By building an MVP, a startup can

• predict the future demand for its product,
• determine the most needed functions,
• test a pricing strategy, and much more.

The concept of MVP comes from the Lean Startup methodology. Just as other components of this movement, MVP is aimed at reducing costs of creating a sustainable business. If you want to learn more about Minimum Viable Products, check this step-by-step guide that we published in our blog.

This article is a rundown of our conversations with three entrepreneurs from Admitad Startups who described their experience of creating MVPs:

• Kristina Shtaudínger, the head of online marketing of Admitad Startups
• Vadim Lopukhov, product manager of CashBro
• Daria Malinina, product manager of Collabica

They confirmed that even the most primitive types of MVP (e.g. a group in a social network) can still deliver results perfectly. The main thing is to test a hypothesis as quickly and cheaply as possible while also achieving first sales.

Kristina Shtaudínger: validation through social media groups

Currently, Kristina works as the head of online marketing. But before that, one of the stages of her career was the position of a product manager in Admitad Startups’ incubator. In this article, Kristina shares how she was testing a product hypothesis in the cosmetic industry.

Admitad Startups was long interested in the promising growth of the beauty sphere, so it was searching for ways to launch a business in the market. One day, Kristina received an assignment to check whether there was any demand for a Vivino-like application to evaluate and search for cosmetic products. It was planned that the app would search for the cheapest deals on the Internet and earn money from referral links.

“We wanted to validate whether consumers had any need to browse the Internet before buying cosmetics,” Kristina explained. “So I had to build an MVP to confirm or refute this hypothesis.”

Building an MVP for a cosmetics searcher

Kristina created a community in VKontakte — a popular East European social network. In the description, she clarified that her team was developing a searcher app for cosmetics. The community members were encouraged to send her their makeup requests. She was ready to help them for free since their involvement would allow her to determine the next steps for her team.

Here’s how it worked. Kristina invited users to send her product names of cosmetic items they looked for (certain mascaras, perfumes, lipsticks, etc). In return, Kristina provided them with 5 links to the most lucrative offers on the Internet. She conducted the research manually, mostly referring customers to Admitad’s affiliate partner stores. This way, she would receive bonuses for each time her leads made a purchase.

Here’s a step-by-step process of how this MVP worked.

1. A consumer sent a product request (for example, “I need a L’Oreal Paris Color Riche Collection Privee lipstick”).
2. Kristina found the cheapest offers on Google.
3. Then she added referral links to stores affiliated with Admitad’s CPA network.
4. A consumer received 5 links to the cheapest options.
5. If they bought an item using a referral link, Kristina received a commission fee from Admitad’s affiliate partners.

Results delivered by this MVP

In a week, Kristina earned $2000+ on CPA links. Technically, her MVP validated the hypothesis that there was demand in the market for a cosmetics price searcher. Moreover, it brought her first customers and some money.

But when Kristina started to conduct CustDev interviews with community members, she realized that her success was more of an accident than a truly confirmed pattern. Chat after chat, consumers shared that buying cosmetics was more of an entertainment for them or a way to relieve stress.

Among the consumers who made a purchase, every single one of them said that before they stumbled into Kristina’s group in VKontakte, they had actually visited a brick-and-mortar store to find the cosmetics they needed. However, they hesitated to buy these items or could not decide between several options. So they came home and browsed the Internet for cheaper prices. That was exactly how they found Kristina.

There were other cases when consumers received links from Kristina, but instead of ordering items online, they decided to visit the brick-and-mortar store and manually buy the product they needed. It was because this way, they were able to pick up something else at the same time (for example, a make-up sponge, a cosmetic bag, etc).

Project shutdown

Kristina presented her findings to the investment committee, and its members praised her success. They even voiced their willingness to allocate money to the development of Kristina’s cosmetics price searcher. However, Kristina refused to proceed with this project. After her CustDev interviews, she was convinced that consumers preferred to buy cosmetic items in offline stores and rarely turned to ecommerce. 

There are, of course, exceptions to this rule. For example, when a consumer has been using the same foundation for 5 years, they already know how it feels on their skin. So they don’t need to test its shade, coverage, and texture, and purchasing this foundation online would be more convenient for them. In all other cases, customers might prefer hunting for cosmetic products in stores. It enables them to see how these products function in real time.

“Maybe I’m wrong, and in a year or two, a similar app will be all over the market. But I don’t believe that it works. And if I don’t believe in it, then I don’t want to put my time and effort into it,” Kristina says. 

Takeaways from Kristina’s case 

Kristina’s story confirms that even the simplest MVP that was cobbled together in less than a day can validate a product hypothesis (or prove that a business idea is not viable). In her case, a community in social media with manual price research was enough to earn some money, convince the committee, and even get the first investment.

Vadim Lopukhov: validation through SDK

Today, Vadim is a product manager of Cashbro — a mobile browser with cashback for each user session. This project was coined when Admitad Startups’ incubator came up with an idea to increase user engagement by embedding a cashback browser in apps. Vadim was tasked with testing these two hypotheses:

• The built-in browser might increase user retention in apps.
• The app engagement of browser users might grow.

The parameters of retention and engagement were chosen because they directly affect how often and how long users interact with apps. In turn, it has an effect on how these applications monetize their audiences. The more time users spend in an app, the more often it can push them towards making a purchase:

• Send notifications
• Offer appealing discounts
• Announce new offers
• Show pop-ups, and so on.

Vadim needed to validate the cashback browser’s effect on certain KPIs in the quickest, cheapest way. However, some of the easiest MVPs — landing pages, social media groups, etc. — were not applicable to his assignment. So his team decided to whip up a primitive SDK to check how an embedded browser would change the retention and engagement metrics of other apps.

Building an MVP for a cashback browser

The cashback browser SDK was supposed to integrate into various apps. Vadim decided to partner up with online stores, games, cashback services — pretty much anything that had its own bonus system or loyalty program. So when users checked apps with embedded CashBro, they saw a call-to-action that said, “Start earning more!”. Those who clicked on it were redirected to an onboarding page which introduced them to how the cashback browser worked. 

The idea behind CashBro MVP was simple: 

• By using it to surf the Internet, a user could get up to $20 in cashback each month ($0.00050 per minute).
• At the bottom of the browser, there was a tab ‘You earned…’, and users could see how many bonuses they received. 
• The MVP had an automated count that showed how much time a user spent in CashBro. 
• However, the bonus accrual was not automated, and Vadim’s colleagues had to pay out the cashback manually to each user. 

This pilot version didn’t require much time and money to develop. Within a month, Vadim’s team had built an MVP that proved effective in capturing KPIs and could be shown to potential customers despite its primitivity.

Results delivered by this MVP

Vadim’s team integrated their cashback browser into the CheckScan service. It had a MAU of 150,000 visitors at the time, but the test was carried out with 10,000 users and lasted for 4 weeks — this was enough to get relevant data. 

Out of 10,000 test participants, a little over 6,000 started using the cashback browser. Despite the very small number of push notifications sent out to CheckScan users (only 2 notifications for the entire month of testing), 60% of users tried to see how the browser worked. 

Here are some other findings:

• CheckScan’s user retention increased ×2.4 — from 12% before CashBro’s integration to 31% at the end of it.
• On the 20th day of using the app, user retention grew ×3 — from 7.4% to 24.7%. 
• The weekly app usage has increased from 11 minutes to 80 minutes.

Another integration was with Skrepka — a cashback service with 18,000 MAU. 11,000 users were taken as a sample, and the test period also lasted for 4 weeks. After push notifications, 83% (9,000 users) updated their app versions to start using CashBro. 

Here are the test results:

• Skrepka’s user retention increased by 18%.
• In 3 weeks of CashBro integration, 34.2% of users returned to Skrepka’s app compared to 27.6% before the test.
• The cashback browser boosted the number of sessions ×2.7, whereas session time (in minutes) grew ×14.

MVP challenges that CashBro faced 

When testing their MVP, the team of CashBro turned to applications that were already making money and had a loyal audience. Vadim explained, “These companies are afraid of losing their users in case they embed buggy software.” So he identified three main challenges of developing an MVP:

1. You have to be persuasive and confident with potential partners because it makes them believe in your product.
2. MVP must operate flawlessly. Stability is more important than having many different features.
3. MVP should reach your goal. Therefore, you need to articulate clearly how you are going to validate a particular hypothesis and/or what metrics will be used for KPIs.

Takeaways from Vadim’s case

The main idea of Vadim’s MVP was to make a browser SDK on WebView using native Android tools and insert a simple time counter into it. The development was budget-friendly, and the costs turned out to be several times lower than when hypotheses were tested in other ways.

As soon as all the tests are completed, the team can polish CashBro’s MVP, bringing it to a more salable look, and start searching for new partners to accelerate the project’s growth.

Daria Malinina: validation through manual CSV import

Daria is a product manager of Collabica. It’s a cross-store application that allows Shopify vendors to expand their product selection by importing catalogs from other suppliers. Thanks to Collabica, retailers earn commission fees each time they sell their partners’ products, whereas suppliers find new distribution channels.

Building an MVP for a cross-selling solution

Daria needed to build an MVP app, but she knew it would take a long time. So while the pilot version of Collabica was in development, Daria tested her product hypothesis by manually embedding CSV files into Shopify storefronts.

Here’s how it worked:

• There were two roles for testers: they could join in as suppliers and as retailers.
• The Collabica team asked supplier participants to submit their product catalogs as CSV files.
• Then, Collabica uploaded these files through the admin panel to the retailers’ storefronts.
• Suppliers’ products were added to retailers’ stores. Retailers could set their prices and sell these items as their own.
• When a retailer made a sale of an embedded product, they sent the order details to the Collabica team. Collabica then forwarded them to the supplier.

“In fact, we assembled these CSV catalogs manually, uploaded them to retailers’ stores, and then processed the orders ourselves,” Daria says.

Communication with suppliers and retailers

To match stores with each other, Daria needed to understand their target audience, average metrics, and overall policies. She quickly discovered that not all brands were ready to collaborate — sometimes they had certain requirements that their partners needed to meet. For example, some retailers only needed ethical suppliers, and vice versa — some suppliers only agreed to partner with vegan brands.

When a test participant chose to be a retailer, Daria’s team asked a list of questions, such as:

• “What types of goods would you like to add to your store?”
• “What brands on Shopify do you want to partner with?”
• “How do you feel about certain commission rates?”, etc.

After that, Collabica searched suppliers that fit the requirements and sent their product catalogs to retailers. In turn, they embedded them in their Shopify storefronts and started selling new items.

When a test participant chose to be a supplier, Daria’s team clarified

• their retailer requirements,
• delivery terms and rates,
• commission fees they were willing to charge, etc.

After completing this survey, Collabica could start matching suppliers and retailers with each other.

Takeaways from Daria’s case

Even though most of this MVP was manual labor, Daria’s team found several dozen stores that agreed to participate in testing. Each of them picked a role as supplier or retailer. Daria also got first sales of embedded products.

As soon as the pilot version of Collabica gets finished, Daria plans to start promoting it on Shopify’s app store. But when it comes to hypothesis validation, her manual CSV import confirmed that there was enough demand on the market to keep pushing in this direction.

Final thoughts

In this article, we observed two case studies that confirmed: MVPs don’t have to be expensive. In fact, you can build an extremely simple version of your product and still get first sales, impressing investors and potential customers with your initial results.

• Kristina was testing a price searcher app for cosmetic products. To validate the hypothesis that consumers would look for beneficial deals on the Internet, she created a social media group and invited users to send her requests for particular make-up products. This type of MVP was enough to confirm the demand for cheaper beauty offers. The project was greenlit, even though Kristina refused to take the investors’ money since she decided to shut it down.
• It was somewhat harder to validate the hypothesis that Vadim’s cashback browser was able to increase any app’s retention and engagement metrics. His team developed an SDK that would integrate easily with any app. Half of the processes in this MVP, including cashback payouts, were operated manually. This fairly primitive solution helped Vadim save up on the budget and confirmed that the whole project was viable.
• While the main MVP for Daria’s cross-store solution was in development, she came up with a way to manually confirm her product hypothesis. Her team created a network of retailers and suppliers and helped the former to embed CSV files with product catalogs in their Shopify stores. This cheap MVP was enough to bring in potential customers and get Daria her first sales.

Here’s the key secret behind all these MVPs’ sustainability. All three entrepreneurs took their current tasks as a point of departure and searched for solutions in alignment with their objectives.