

How it started
Back in 2011, artificial intelligence was not a hot subject. There was no talk of it. I was a marketing director at that time. The challenges of growth and competition were the same as ever. The anxiety of uncertainty was even worse.
Like every other marketing executive, I put endless hours of unproductive work into making sense of marketing research reports. Surveys and polls were not enough to solve a marketing challenge. It was not enough in 2011, it is not enough today too. You had to develop a winning strategy allocating marketing resources optimally. The grand question was where to focus strategically.
The epiphany
My personal epiphany came when I asked myself whether it is possible to simulate the market to find out what to do in marketing. Eventually, the simulation idea took a left turn and fused with neuroscience. I came to the realisation that the key to the understanding of the market is the individual. This was the moment when I parted ways with traditional statistics. To make statistics to tell you something about the market, you had to ignore the individual. You needed crowds in statistics or a very long observation of behaviour. An individual was a mystery lost in regression equations.
How to understand the causality in the decision making of an individual? This was my question to uncover the mystery. It took 4 years to answer this question. My crusade was to develop an algorithm which can explain the causality of an individual's decision. During that time, I taught myself artificial intelligence concepts and technology. Eventually, I had to innovate my way to solve the challenges.
It was not all easy
I had two big problems to solve. The first and the most important of all, data are scarce. I had to come up with an algorithm which does not need lots of data The second challenge was to define the data type that I need to feed into the algorithm. In practice, the discovery of the data type made the algorithm work. In 2014, I came to the realisation that only biological data can solve this riddle. Neuroscience saved the day for me.
Combined with the biological data, my version of the neural networks algorithm becomes an extraordinary tool. Around 2015, I was ready to solve one of the most intriguing questions of our times. How to explain a decision.
The simulation and the simulated
I used my artificial intelligence technology to build a simulated person: A virtual customer who can autonomously take purchase decisions. When you increase the number of simulated customers, the market emerges.
I built a virtual market environment where all the simulated customers are situated and mid-2015, I completed all the pieces of the puzzle. I had a strategy lab in the form of a virtual market where virtual customers are making purchase decisions. The first time in marketing, we could observe the outcome of our what-if questions.
The business side of things
At the end of 2015, first Renault, then Beko became my clients. At the end of 2018, I started to work with Unilever. My first office was a tiny shared space in Istanbul, now I extended my reach to Poland and France. The company went through partnership changes. In 2018, I founded 100% owned Divera.
What is next from now on? I enjoy cracking the impossible. I love seeing Divera prevail where conventional marketing solutions fail. I predict a revolution in marketing and I want Divera to be a part of it.