The case of a failed startup: Let’s break it down

Media is packed with stories of innovative projects and their success, but what about the flip side? Let’s analyze a startup that’s got some problems.

This article is based on a podcast series with Avatarika project manager, Yuri Levanov.

History of the Project

The concept of Avatarika was taken from the backlog of Admitad Projects which contains all new ideas and promising concepts that did not take off the first time. Initially, the project was aiming at the market for robotization, automation, communication, and so on. Avatarika tried to test it through call centers, but this format turned out to be unprofitable.

Still, it was a large and ever-growing market with an emerging pool of robotization tech, speech synthesis, and chatbots with active niche cases. Overall, it seemed to be quite a promising direction, so Yuri decided to restart the idea.

The name of Avatarika arose from an analogy with the user’s virtual embodiment in a robotic form. Avatarika began its tests while pressuring customers who planned to make a purchase but didn’t. At first, the project chose to develop in a budget-friendly segment, but it soon became clear that there would be no profits or scaling. That is how Avatarika was transferred to the segment of B2B.

Which B2B Problems Avatarika Solved

The startup was useful for manufacturers and suppliers with large partner networks. Typically, such customers have more communication with potential customers compared to regular B2B companies. You can direct a larger audience to your website, for example, using Google Ads, but the conversion rate won’t be high. The problem of returning users to their abandoned purchases is exactly what Avatarika solves.

Technology, Theory, and Practice

Avatarika combines several products and technologies that previously existed in the market. The company purchased a network of contacts and connected them to the current client base. Having received customer data from the employer, the startup identified at least 15% of the leads that abandoned their purchase. Then, Avatarika analyzed if they consented to process their personal data. If yes, the robot called the customers and offered them a deal, motivating them to finish the purchase.

How It Worked in Reality. Why the Startup Failed

The main problem was the market’s stubborn refusal to try out the new format. The primary representative sampling turned out to be slightly off, therefore the number of clients was smaller than expected.

The second factor was the question of monetization. A strategic mistake in the pricing of the service was at fault. It was necessary to calculate the prime cost, consider all possible hiccups, and add something like a 30% margin for the service. But this calculation was carried out in a very approximate estimation, which led to the current state of affairs: every coin from a lead was spent on serving them, sometimes dragging the company into the red. As a result, the startup received customers with marginality in the range of +120 to -400%. At the same time, the project kept growing. Its first sales were 50, 200, 500, and 600 thousand rubles worth.

The third problem turned out to be even more serious. When trying to scale, Avatarika ran into technical issues which had to be corrected as you go. Often, the reasons were on the customer’s side.

Example. The client entered into an agreement and paid the money, but in fact, they had no database. The website traffic was 500 people per month, and their data was not collected or processed in any way. Naturally, Avatarika failed to get a cure-all out of thin air; no man can make a good coat with bad cloth.

Communication between Employees and Customers

There was another issue that required attention. Apart from the head, the startup employed 14 people, including programmers, accountants, and salespeople. The IT department was constantly introducing some technical updates. Information had to be communicated to all current customers, but not everyone was happy about it as the updates seemed too difficult. In general, this led to backsliding and refunds. Although the startup received support from the Admitad Projects’ own tracker, it developed a tough emotional situation, so it was necessary to look for new solutions.

Support from the Startup Studio. The Current Pivot

Over time, the situation got worse. The project was moving in the wrong direction, although showing clear growth. But the numbers and workload were incomparable. Yuri followed the advice of Maxim Volokhov, head of ADP, and decided it was time to pivot.

It all started with disbanding the team. But people did not end up on the street. Thanks to the capabilities of the startup studio, they were simply distributed among different projects within Admitad Projects. It became possible due to a special studio’s laboratory where it keeps projects at different stages of development. 

The next stage was communication with current customers. Avatarika proceeded with refunds, offering to continue cooperation after the pivot. Almost everyone met halfway, which allowed Avatarika to preserve its reputation, as well as opportunities for further work.

After all these actions, the project began searching for a new focus. The emphasis was still on the market of communication and robotization. There was a lot— I mean, a lot of communication with sakes managers, commercial directors, and companies working with CRM. Avatarika was searching for the pain points. As a result, the startup’s new aim was the social CRM market with sales through Facebook, Instagram, and other social networks. This is the direction that prevails to this day.

Results. Main Hiccups of the Project Founder

As the founder said, the main problem was too much responsibility to the investors, employees, and clients. In times of challenge and stress, it creates a strong moral discomfort, which hinders the effective development of startups. This problem was partially solved by working with the Admitad Projects’ tracker. Of course, the management of the studio provided great support as well.

The second problem was the lack of repeat sales due to the imperfect startup model. Selling for the first time is actually not that difficult. But you can sell again only if the customer really appreciated the product and saw its real value (instead of an advertised one). In the case of Avatarika, it caused some obstacles: something worked, something didn’t. But the turning point was when the client called the company and asked to extend a contract. We could put it that way: it doesn’t matter how much you sold for the first time, even when it’s in millions. The only thing that matters is repeatability.

The third problem was personnel or rather its quantity. Too sharp a start was taken. The euphoria of the first large sales led to some unnecessary scaling. Even though the startup was still operating on MVP, the founders thought, “If that’s what we have now, the future will be even cooler!” And, of course, the previously mentioned communication problems were also relevant. It’s crucial to solve them immediately as they appear while intervening strongly in these processes.

You should always aim for gradual development. At the same time, be ready to skyrocket at each stage, for instance, increasing sales exponentially. Finally, you also need to be careful and prepare for all the consequences.

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