He started his career in real estate in 2007. Engaged in market analysis and development of sales reports in development companies. At that time, he began actively studying programming to solve complex mathematical forecasting problems. In 2017, he joined the M4U team as Head of Research and Development.
How did the idea of creating MAXIFY come about?
The idea of automated price management arose in 2016, when Volodymyr Danylenko, founder of M4U | co-founder of MAXIFY, and I worked in the same large development company. Volodymyr was a commercial director and I was an analyst. Sales were too fast – more than 20 apartments could be sold per day. There was a constant risk that the most liquid assortment would be sold first, and we would be left with less liquid apartments. At the same time, we felt that this pace of sales does not fully allow us to realize the commercial potential of the project. So I developed an express sales analysis solution that allowed me to analyze the sales structure quickly. Based on these data, Volodymyr was engaged in changing the price of the most popular groups of apartments.
Sales were too fast – more than 20 apartments could be sold per day. So I developed an express sales analysis solution that allowed me to analyze the sales structure quickly.
Did MAXIFY start with an analytical report?
You can say that. Initially, it was not conceived as a commercial product, but rather to solve separate tasks, one of which is the assortment analysis for making decisions about revaluation. In general, I am a staunch follower of data-driven principles, so I believe that for such an important task as price management, a subjective expert approach should not be used. First of all, the calculation process requires clear rules, consistent execution, and complex calculations.
But there is a big difference between the sales report you are talking about and the MAXIFY SaaS product as it is today. What were the most important next steps in development?
Firstly, having a lot of insights into the price behavior of customers, in a few months I developed the first version of the multifactor price calculation model. The key issue was the identification of internal factors affecting the price and the study of the nature and extent of their influence. I won’t say too much, because it is part of the know-how of the product. In the beginning, the model was quite simplified, and today it already has certain elements of machine learning. This model helped the system perform two main tasks in a semi-automated mode – calculation of initial prices for apartments in the building and revaluation at the stage of active sales.
That is if earlier using the analytical report on sales, the responsible manager had to make calculations manually, now the system did it for him?
Exactly. And it saved a lot of time and nerves. Overall, our goal was to fully automate the price management process. But it is impossible to control the price without having any reference points. That’s why I combined price calculations and monitoring of the plan-fact for the project in a separate tool. The functionality turned out to be very useful, it helped to make high-quality and fast reporting. It was the end of 2018, at that time the system was already working on Microsoft Power BI because ordinary spreadsheets could no longer cope with the calculations. It was an MVP that we launched in several pilot projects with the innovative Ukrainian developer SAGA Development. The result of the pilot was very cool, so we decided to go into the development of a full-fledged SaaS with a simple and understandable web service. The R&D team and I continued our research until finalizing the calculation model.
Our goal was to fully automate the price management process. But it is impossible to control the price without having any reference points.
What technical challenges face MAXIFY soon?
I believe that now the main challenge for MAXIFY is not in the technical plane, but in promoting among developers – our potential customers, the idea of deep digitization and data-driven decision-making. Such companies better understand the value of innovation, because they often already had some experience with other solutions. On the technical side, we focus on helping customers create automated data exchange chains between MAXIFY and their ERP or CRM to fully automate the process.
What about your challenges?
Work-life balance. Together with my wife, we are focused on raising our son, and this is an extremely interesting, responsible, and pleasant occupation. We designed our product in the first place so that our customers can leave complex calculations to the system, and focus on creative tasks, such as developing outstanding projects and creating fantastic teams.