Why I Founded Veylinx

I often get questions about why I started Veylinx. Although I’ve shared this story many times, I’ve never gotten the chance to write about it — until now.

It all started while I was working on my Ph.D. at the University of Amsterdam. One of my fellow researchers was trying to understand why a particular product wasn’t selling that well. A large, well-known consumer electronics giant developed the product. The company spent millions on (market) research and development but once launched, the product fell completely flat. I wondered why a company of that size can’t predict in this day and age whether one of its innovations is going to be successful.

Well, predicting human behavior is a tricky business, very tricky. Even scientists, with their beautifully designed experiments, struggle to predict how people are going to behave reliably. I started to explore scientific literature related to why it’s so hard to predict what people are going to do. Specifically, I wanted to understand how to predict what people are going to buy. I quickly came to the conclusion that most researchers simply ask people about what they’re going to do in the future and take it at face value. I was honestly surprised about how widespread this practice is.

One of the core principles of behavioral economics is that you don’t ask people how they’re going to behave, but instead, you observe how they actually behave.

I spent considerable time before and during my Ph.D. studying behavioral economics, which had a substantial influence on how I view the world. One of the core principles of behavioral economics is that you don’t ask people how they’re going to behave, but instead, you observe how they actually behave. This principle is based on a large body of scientific literature that shows that what people claim doesn’t often correspond to what they do. The anomaly even has a technical name: the hypothetical bias.

The only way you can overcome this problem is by having people make real trade-offs. So, a standard survey won’t do the trick. I needed a way to measure how likely someone is to buy a product realistically. I found a small group of behavioral economists who were able to do exactly that. They used a special type of auction called the Vickrey auction. The auction was developed in the early seventies by the economist and Nobel Laureate William Vickrey. What made this auction so special was its ability to reveal how much you value a product. It involves a bit of game theory, but more importantly, participants are bidding with their own money. Precisely because it’s not hypothetical, you’re much more likely to understand what’s going to happen in the real market.

I thought I was ready to start predicting, but unfortunately, it wasn’t that simple. There was no easy-to-use online platform for running these studies with a representative sample of the population. I saw no other option but to build my own platform. Fast forward a couple of months, and I was ready to go. I started conducting study after study to finetune the platform. Remember the product that fell flat? Well, the platform showed within a day that the product had no chance of succeeding. If I can accurately tell whether an innovation is going to succeed before it hits the market, I will be able to prevent R&D waste, increase the success rate of innovations, and ensure unwanted products don’t waste people’s attention and money.

After realizing the potential of this radically different approach to market research, I set out to turn this idea into a company. I was fortunate to meet my co-founder, Rainier van Rietschoten, before founding the company. He had spent a couple of years working for Procter & Gamble and almost instantly knew that this new approach could solve a variety of fundamental innovation and marketing challenges. The company quickly grew as we seemed to be solving a real issue. Currently, we’re proud to work for clients such as Unilever, Nestlé, Reckitt Benckiser, and many other global brands to tackle their marketing and innovation questions — and we’re just getting started.