We talk to startups and investors, you get the value.
Michael Rumiantsau is considered as one of the most successful Belarussian startuppers. At the end of 2018, his project FriendlyData was bought by a ServiceNow corporation. Since then, he has been developing his own company builder — some kind of a “one-man accelerator”. He supports startups with his expertise and invests in early-stage projects. Startup Jedi talked with Michael about the life after exit, his interesting but untypical model of work with startups, and trends on the business intelligence (BI) market.
We talk to startups and investors, you get the value.
As a result, our product appeared to be pretty close to the one, I saw it a year or two ago. With the ServiceNow resources, we stepped over a few steps.
My main fear was that the technology would fuse inside of a large corporation — I have seen a lot of examples of such cases. Often, it happens that the buying company doesn’t have a clear vision of how to use the purchased technology, or it greatly diverges from company founders’ plans. As a result, a startup’s team switches to new products of the buyer, and their own technology loses the main priority.
However, ServiceNow top-management supported us and the integration went smooth. Soon, ServiceNow will have a new release — and FriendlyData technologies will be implemented in it.
In the framework of a company builder, I work with a startup in three directions.
First direction: classic venture investments at the pre-seed and seed stages.
Second direction: startup mentoring and advising. I help projects to enter a market and attract investments. But here, I have a more supporting role.
Third direction: executive role. These are startups, where I act as a co-founder. Such projects develop sophisticated business ideas, that have been validated by market and major clients. Precisely for these startups, I build up teams.
There are five projects in my company builder now. All those are b2b-startups, that want to improve the work of people with the help of data and AI. In the nearest time, I will take another 1 or 2 startups, and this will be my limited pool for now: however, I will continue to actively form a pipeline and communicate with founders — in the next year I will take a few more.
Startups are from different countries: two are from Belarus, one is from Ukraine, one is American, and one is Belarus-American.
I have seen more than 200 projects during 2019. I cannot strictly describe the rules according to which I choose startups — there is nothing precise in this industry. If it seems to you, that you have a definite winner, then more likely, it is late to invest in this project, as it is obvious to all investors. It is more important to find unobvious startups that are able to “make a breakthrough”. Sometimes those may be totally “insane” ideas. Even Airbnb seemed to be ridiculous, and as a result, it has become a “unicorn”.
While evaluating a startup, in the first place, I look at its founders. How they work together. How pertinacious they are in achieving their goal. How fast they learn and make progress. Before making an investment decision, I try to work with the founders for some time and watch them in action.
In any case, it is a mutually useful experience. Startups receive my expertise, I receive insights that were inaccessible to me. For example, a project works in a niche, which I don’t have enough knowledge about. Or it has clients from the countries that I have not worked with yet.
Depending on the level of my involvement and the degree of approximate evaluation, I invest from nothing to 200 thousand dollars. It is impossible to evaluate projects in the early stages, that is why, to structurize a deal, a convertible loan is usually used in such cases. In its framework, you can use various tools — SAFE (Simple Аgreement for Future Equity), KISS (Keep It Simple Security). I personally like the latter one, from 500 startups.
So to say, evaluation is a very relative thing. The investor has to focus not only on the evaluation but also on the fact whether he will receive multiple returns on investments in the nearest 7–8 years (if to enter projects in early stages). And whether the result will be better than from investing in traditional (or alternative) instruments.
Investments in startups in their early stages are mostly low-profit or hard-to-sell investments. Only top-level venture funds make out a 30% return a year. As for me, I regard investments in startups as those that I can lose. However, I try to minimize the risks: I only specialize in startups from those industries that I have competence in — enterprise-soft, data, AI.
It is very important that a startup solves a problem that is relevant to a large number of potential clients. It is desirable to have a rapidly growing market. With an average product in a growing market, it is much easier to “take off” than with a great product in a collapsing one.
The market category can be formed and grown-up to fit your product. Take any formed market — let’s say, BI. It has been developing for 40 years, there are big players. But, despite all these, approximately every 10 years new segments appear on it. If the market is big enough, it is possible to create a new category on it.
For instance, Salesforce is an undisputed CRM market leader with annual revenue of 13.3 billion dollars. Perhaps, there is a problem that Salesforce can’t solve, let’s say for 1% of their users. In the scales of Salesforce, 1% is not a work scope, that should be focused on. But for a startup, 1% of 13.3 billion is 133 million dollars. So it is a segment where you should try to settle.
That is why you can enter the existing markets if you will create a new category with your product. Otherwise, you solve the problems, to which other players do not pay attention to.
Usually, we have weekly phone calls with startup founders. If necessary — then several times a week. Mostly, those are “on-demand” interactions upon request. Despite the fact that all startups are on the same development stage, I work with them individually — each of them has their own needs.
I do not impose my views on communications, but I am always open to questions and feedback, I am ready to arrange a meeting for a startup with the right people. I am proactive about this: I think about how relevant are my new acquaintances and appearing possibilities to a project. If I see that a founder makes a mistake — I point on it. But if he wants to learn on his own mistakes — I’m for it.
I have a privilege not to plunge into operational processes now. So at this stage, I would rather risk my money than time. However, in those projects, for which I build up teams, I also do the “operationals”. Besides, I communicate with clients, conduct custdev, prepare the documents. Anyway, I am not afraid of turnovers and “rough” work, it is more about priorities and possibilities. If there is a possibility to delegate tasks, I’m on it.
It is a predictive product and complement analytics. If earlier analytics was visual and relied on reports, now technical capabilities and data have appeared to automate analytics and predict data behavior. And behind the data, there are customers and business metrics that determine cash flows. Therefore, it is important to interpret the data correctly.
One of the startups from my company builder Credible Insights company resolves precisely this question. It is an analytical platform, which generates automatic insights from the corporate data, using the algorithms for detecting anomalies in the data. This service helps “non-technical” people to find deviations in business data and react to them in seconds. For example, if an e-commerce site experienced a sharp decay in the buyer’s conversion of a particular product, the system immediately sends a notification and helps you figure out why this happened.
One of the key markets on which we are focusing on with this startup is e-commerce and retail. Any changes in data there is a consequence of processes that influence a company’s revenue. Organizations in this sector are eager to implement such innovations into their business processes because they provide an instant effect.
But it is important not just to detect an anomaly and notify about it. The main thing is to define the issue and give a hint which works tactics to choose, taking into account an insight. Long story short, answer “Why?” and “What to do next?”. We are following this direction.
In general, the business intelligence (BI) market is consolidating. Google bought Looker for 2.6 billion dollars, SalesForce — Tableau for 15.7 billion dollars, and there were a number of other significant deals. New companies just have the opportunity to enter this huge market and create new segments on it.
One of the startups I’m working with — it is a team from Ukraine, that created the Attractor product. It is an interesting tool for product analytics, and, I’m sure, that it will find clients in the niche. Nevertheless, guys do not stop on one product. They are checking new ideas, and one of their new projects is DuckDuck.io — a tool that simplifies the work with documentation in the code. I like their approach: they solve problems that they face themselves while working with clients.
Good product teams are ready to experiment, search for new solutions, and at the same time, they are ready to admit a mistake being made — and this is precious.
Startup teams should be based on persistent and, in a good way, stubborn people. Even if you do everything correctly, success is not guaranteed. Every successful person at least once was a step away from failure. Therefore, after the first failure, you do not need to stop. Usually, those are startups to win which stubbornly go towards their goals and draw conclusions from their mistakes, rather than those startups that never make mistakes.
Startups can afford to experiment and make mistakes. For a large business with the revenue, let’s say, 100 million a year, even a tiny experiment may change the revenue in a few percent both up and down. And several percents from 100 million are millions of dollars.
Thus, it is easier for a startup to try out something new to find the right strategies, tools and channels. It is vital to find them: if you do the right things, everything will work out for you. And without experiments, it is impossible to know whether they are right or not.
A simple small business, like a coffee shop, sometimes test hypotheses and conducts custdev more effectively than some startups. It’s because of the limited budget of such business and the founders know how to count money. Startups, in turn, easily attract investments in the early stages as there is a lot of free money on the market of venture investments.
If startup founders have a technical background, then, most likely, they know how to do a product but they don’t know how to make the right decision, based on business priorities and clients’ needs. And, usually, it happens, that such a company does a product of good quality but it is useless on the market.
And here is why it is better to start with a real existing problem but not with a technology or product.
Ideally, if you can solve this problem manually, without an MVP — for instance, by downloading an outturn in Excel, sending the necessary data via email and etc. The idea lays in the ability to solve the client’s pain from scratch, dealing with the problem without a cool product interface. When you can successfully solve a problem manually, and you already have a few paying clients, then you can think about automatization and MVP.
The paranoia that someone will steal your idea is the last thing that the startup needs in the early stages. The only way to conduct custdev and validate a problem is to communicate with potential clients. This is the only way to understand how your product has to work. Without it, you are most likely to do something that is useless for the market.
The idea is a piece of clay, that is shaped only during the interview with users. It is dangerous to think that your idea is a finished and self-sufficient solution. Not at all, it is just the beginning of the road.
Personally, I try to avoid founders who arrogantly think that they know everything about the market and clients. Often, their product and what the market really needs are two different things. The dialogue between startups and clients shouldn’t end after the early stages of development, ideally, this should be a continuous process.
You’d better listen to what investors say if their feedback is repeated over again. For example, all the investors with whom you speak are confused by the business model and the fact that the project is not scalable. If you regularly receive this kind of feedback, then you should stop fundraising and go a few steps back to fix the indicated problem.
A different story is when investors refuse to invest but refer to different excuses and contradict each other. In this very case, the real reason can be way different. Let’s say, they do not invest in startups whose founders are from Eastern Europe but they don’t tell it directly. That’s why you always have to focus not on investors but on clients, as you are creating business for them.
And the venture market is changing rapidly. Today, investors say, that there is no more room on the market for your product. And in a year, the same person can tell you that the market is overwhelmed, and he has already invested in a similar company.
Out of the new Belarus startups, I would like to pinpoint Altum Analytics. They solve a global problem of SaaS market — they reduce the customer outflow, increase the retention rate, stimuli upsales. Their predictive product helps businesses to pay attention to client groups, who can: a) leave; b) pay more.
In the last years, Belarus IT-community discusses potential educational reforms: a university for programmers and epidemic “IT entry”.
I don’t know what about IT-university but IT-college is a necessary thing in Belarus. In the high-tech industry, no rocket science is needed for the majority of tasks. Basic knowledge is enough to connect the API, analyze the logs and etc.
Recently, a list of the 50 largest IT-companies of Belarus was published. 45 of them are service businesses and outsourcing. To close their needs in engineers, IT-colleges would be more than suitable.
In general, programming and IT are modern basic literacy. If a person wants to be competitive, he needs to acquire new knowledge and skills demanded by the economy and the market. When electrification took place 90 years ago, electricians were urgently needed. Today, in the digital age, we need programmers. In 10–20 years, other skills will be trending. People are expected to opt for what makes them more competitive in the market. This is a natural process, there is no way to escape it.