The Future is Now: Combining psychology and machine learning to solve problems, with Igor Volzhanin and Fotis Georgiadis

I had the pleasure of interviewing Igor Volzhanin, the CEO and Founder of DataSine, a London-based startup, which is using AI and psychology to empower companies to personalize their customer communication at scale. Inspired by his PhD in Computer Science and Psychology, he established the company in 2015 with the belief that it is only […]

I had the pleasure of interviewing Igor Volzhanin, the CEO and Founder of DataSine, a London-based startup, which is using AI and psychology to empower companies to personalize their customer communication at scale. Inspired by his PhD in Computer Science and Psychology, he established the company in 2015 with the belief that it is only through bringing the power of face-to-face communication into the digital world that businesses can deliver the most value and ultimately fulfil their objectives. Before founding DataSine Igor spent five years working in international development and lived in New York, Frankfurt, Tirana and New Delhi. A relentless innovator, he is passionate about bringing his research to life and helping companies build meaningful relationships with their customers.

Thank you so much for doing this with us! Can you tell us a story about what brought you to this specific career path?

I wouldn’t call what I do a career. It’s something that happened to me and it’s not something that I ever looked for. About four years ago, I moved to London to do a PhD in psychology. Prior to that, I worked in international development. Actually, my first education, my first degree is in history and politics. I did a master’s in public administration. I was trained to be a performance auditor.

I traveled a lot. I got to live in the US, France. I lived in Frankfurt, India, Albania. About four years ago, I decided that’s not actually something that I was enjoying doing. I thought “Well, what is one thing that I would really love to do in life?” That one thing ended up being a PhD in psychology. I looked around different programs in different countries and I settled on London to do my PhD in. I moved there four years ago to do that. Six months later, I decided to start DataSine.

At that time, I had a desire to start something. And I didn’t really care necessarily what it was, which is maybe weird to say, but I just wanted to start a business. I knew that I had to have a co-founder. I found another student, much older than me. And we matched. That’s how I ended up becoming involved in startups and ended up on this path.

What we do today is not what we thought we’d be doing four years ago. What the company is today, helping businesses personalize communication to their customers, that’s something that has evolved over the last four years. Maybe the initial crux of that, of combining psychology and machine learning to solve problems, that was something that we talked about with the original co-founder, but it certainly isn’t all we do today. I think any good entrepreneur and any good startup evolves with what the customers want and what the market wants.

Can you share the most interesting story that happened to you since you began your career?

There’re a few life changing stories that impacted me and changed my mindset. There was a tipping point five years ago when I was still in Frankfurt — I realized I was stuck in the office working for somebody and I felt like I was heading nowhere. That particular realisation made me really reevaluate the way I relate to the world. In the last four years, I would say that there were a couple of super powerful situations.

Prior to DataSine, I knew nothing about business. I had to google what a start-up is. I didn’t know what accelerators are, what investors are, what business models are and so on. This is very much my first startup, and being in a city where I knew nobody, I would say we really started at the very, very beginning with zero support.

Raising the seed round was definitely the hardest thing I’ve ever done in my life. We actually ended up running out of money for a bit. That experience has really changed me: the fact that we survived and succeeded was a miracle, but also mentally it was very hard to keep everything together. That had a huge impact.

Parting ways with my original co-founder was hard and also changed me. Actually, I would say that was the first big moment of personal growth. There was a day where I realized that I had to actually become a CEO not just in title but as an individual. The reason I was looking for a co-founder initially is because I didn’t feel like I could do this by myself. This was the point when I realised that it was time to grow out of that feeling.

Can you tell us about the “Bleeding edge” technological breakthroughs that you are working on? How do you think that will help people?

What we do is we enable a business to personalize the way they communicate with customers by tailoring content to make it more appealing to the personality of the customer. That requires doing two things. On one hand, we use first-party data. We use data that a business already has on the customer to build a personality profile. That could be previous campaign’s emails that they’ve sent out, and the clicks of those, reactions to those campaigns. It could be spending data.

Using only first-party data, we don’t go to LinkedIn or Facebook and try to gather more data. On the other hand, we have a platform which enables a marketer to tailor content. It gives recommendations for changing color, text, images of an email to make it more appealing to different personalities. You could have an extraverted version of your email, an introverted version of your email, an agreeable version and so on.

We use machine learning extensively in multiple ways to solve multiple puzzles within this field. I would say, at its core, it’s a mixture of psychology and machine learning, which is quite a unique blend.

We get a lot of frameworks that we use. For profiling, we use the big five, which is the standard psychometric framework. We also use the concept of mirroring, which basically says that an individual likes content that they themselves produce. In other words, the way you speak, you want to be spoken to as well. Human beings do that naturally, but in the digital world, it’s quite hard to do.

Then there’s machine learning. We use a lot of frameworks. We use a lot of open source libraries to solve the problem of text generation, to solve the problem of image recognition, to solve the problems of profiling and so on.

How do you think this might change the world? What do you need to lead this technology to widespread adoption?

What we’re really trying to do is replicate the very best salesman and the very best sales experience you can get in a physical store. When you go into a store, a sales person will smile at you. They will try to understand who you are, based on how you’re behaving, how you’re speaking and they’ll try to adjust to that. They’re trying to mirror your behavior back to you. We’re trying to take that concept and the familiarity of trust that gets built and move into the digital world where more and more commerce is happening. We are trying to make messages more personalized, more relevant and more understandable to each customer.

We spent a lot of time localizing our product because we take psychology and we try to bring elements of trust and warmth of social interactions into the digital world. We spend a lot of time and we do a lot of research locally to figure out: what would extraverts and introverts like in the UK? What are they like in Russia? What are they like in France? And in the US? Etc.

On a broader level — is more data and more data analytics making us better or worse? I think it really depends on the different use cases, how and who is using it and for what. There’s the rise of social score in China. Sounds like it’s something that they want, and the social cohesion is much more important to them. They might see it as good use of data — everybody has a score and everybody has an incentive to behave better. Maybe it will lead to a better society as well?

But here in the West, we see that as leading towards a more homogenized, more kind of ‘Big brother’ society where your decisions are monitored and you’re penalized or rewarded accordingly. For me, I think, it’s going to depend. I don’t think we’re going to get to the Black Mirror world.

I don’t think we’re going to necessarily get to a really great world where data has solved all of our problems either. There’re a lot of advances happening not just in digital communication but in healthcare, in transportation where the world is becoming better due to data analytics and AI work.

Keeping “Black Mirror” in mind can you see any potential drawbacks about this technology that people should think more deeply about?

I think it’s innate in human nature to be afraid of things new and old and unknown. There’s a couple of things that we have to prevent these things [‘Black mirror scenarios’]. We have a very strong ethics framework.

When we started working with banks initially, we asked ourselves: if I walk into a bank branch and all of the DataSine analytics is on the screen in front of the teller, would they feel comfortable turning the screen around and showing that to me?

If there was anything that we were producing while thinking “well, probably not, we wouldn’t want to show a customer this”, we weren’t doing that. That’s one of the tests that we continue to use today, which I think is a very good one.

Then finally, especially after Cambridge Analytica case — the focus for us became much more on first-party data. We want to make sure that the institutions, the businesses we work with have permission to use the data that they have, that we’re analyzing for the purposes that we’re using it. They explain to their customers what the data is used for and provide better services as a result. I think that businesses should be forthcoming and open about how they use data with the customers that are generating this data.

As someone who studied politics, now working on his PhD in computer science and psychology- do you think from your own perspective that those who now study and work in computer science ought to have some psychological education as well, because they work with a lot of personal data?

A lot of people who go into computer science don’t necessarily realize that a lot of concepts in machine learning come from psychology, which itself comes from philosophy.

My opinion is that we as humanity have to understand things on a philosophical level first. We can then understand on a human level, psychologically, and then only after that, can we actually build the machine to replicate that.

Do I think that somebody who is in computer science has to learn psychology? Probably not, unless they want to really understand the underpinnings of what they do.

Whether it’s stuff that comes from your smartwatch or purchasing data, just looking at it as a set of data is probably insufficient if you want to get the full information out of it. You have to understand how human beings behave and why they’re doing certain things.

Was there a “tipping point” that led you to this breakthrough? Can you tell us that story?

The tipping point for creating DataSine was my last job. I had this moment of realization. After two years, I was discussing getting a permanent contract, which in Germany basically means a lifetime contract. I was 26 at the time. To me, a lifetime seemed like a very long time and then almost seemed like a big negative calling a contract a lifetime contract.

I was sitting on the chair that day and I thought, “In five years, they could wheel out the chair and just put it outside and I’m sitting on it, no one would notice that I’m gone, and I myself wouldn’t even notice that I’m gone.” Mentally, I wasn’t being really challenged. I needed more. When I came to do my interview to get into the PhD program, my brain started thinking again for the first time in two years. I think it was really the realization that at my present job where I was, it wasn’t going to end well if I didn’t change something.

What have you been doing to publicize DataSine’s idea? Have you been using any innovative marketing strategies?

We ourselves are providers of special personalized marketing algorithms. One of the things that we’ve started doing relatively recently is using our own technology in our own marketing campaigns. We immediately saw an increase. Even just having changed an image in a newsletter, we saw something like 70% increase in clicks and engagement between two newsletters.

We also use use our approach for social media ads. Personality-targeted Linkedin campaigns, for instance, demonstrate significant increase in conversions: we constantly test different groups and content which could be best suited for them. These learnings also help to shape our algorithms.

None of us are able to achieve success without some help along the way. Is there a particular person who you are grateful towards who helped get you to where you are? Can you share a story about that?

I learned a lot through the company. In terms of mentors in business, we had advisors at DataSine, Ben and Chris. I was very happy with them and they came from very different backgrounds. One was very much on the tactical level. He had gone through building a start-up, he knew how to put together a pitch deck, he knew some investors we could speak to, he could give us advice on what accelerator to apply for and then more on day-to-day things.

The other person was a bit older and came from a more of a corporate background. He had also built a company, but a very different type of a company. He was much more about the strategy. How are you going to make money? What is your business model? Is it sustainable? How do you test it?

The two of them really opened up my mind and exposed me to different areas. That was really helpful in the early days.

On the personal level… I never really had somebody who was telling me how to behave or how to be more mindful or anything like that. I was very interested in self-development. I meditate, I try to be reflexive about the way I behave, the way I interact, and the way I feel about things.

At the very beginning, I knew nothing about the business, I knew little about myself. On this path people came to complement the areas where I really, really, really struggled and not the areas where I just struggled.

As an individual I changed more as a result of the company. The PhD in psychology initially provided the base and also the awareness that I can do anything that I put my mind to. It gave me that confidence. It said, “You’ve never studied psychology. You’re engaging with the materials that you’ve never learned before, and you’re fine with it.”

It gave me the curiosity to go to learn about machine learning and other things. That’s what the PhD really gave me. And the company gave me a lot more in terms of actually changing me as an individual.

What are your “5 Things I Wish Someone Told Me Before I Started” and why?

1 — I wish somebody told me it would be this hard. People always tell you it’s hard but not THIS hard. You will break up with co-founders, run out of money, fail projects.

2 — The immense importance of luck in everything. The longer you keep going the more likely something good is to happen to you.

3 — Know exactly WHY you’re doing this, it will save you. When things get really hard, you are going to ask yourself this question: “Why am I doing this?” You better have a very good reason to yourself. In my case it was: “I don’t want to do anything else in life”. So it was easy. Perseverance is key.

4 — I wish someone had told me that a company is all about people. I wish I knew how important people are to a business.

5 — I wish somebody had told me that small red flags in the beginning always grow. Those little nagging voices at the very beginning don’t disappear, but with time, they only grow stronger. If for example, initial salary negotiations are very difficult, it is not likely to get easier down the road.

Is there anything else you’d love to pursue?

I think I am lucky enough that I’m doing what I love and I’m doing exactly the thing that I want to be doing, there isn’t anything else. If there is something else, I’m going to do that. I don’t think there’s anything impossible either. If I felt like I wanted to go and do something else, I’ll just go and do that.

If I wanted to take up photography and become the world-famous photographer, I would just go into that. That’s what I learned from the last four years. If I can do PhD in computer science and psychology, I can do anything.

Can you please give us your favorite “Life Lesson Quote”? Can you share how that was relevant to you in your life?

I guess the one that drives me the most is: “Create the world you want to live in.” And I think this is also what we at DataSine (and I personally) trying to do. Creating is very important. Don’t let the world come to you, create it.

If you had 60 seconds to make a pitch to a VC, what would you say?

My advice: don’t ever pitch investors! I think every entrepreneur has to understand something that if you’re in a situation where you’re pitching your company and you’re asking for money, you are at a huge disadvantage.

Your mindset has to be: “I am building something that is going to be very valuable and I need certain resources to make that happen. You — as an investor — have some of the resources (money) that I need, but the understanding here is that you’re not doing me a favor and I’m not doing you a favor. I’m not pitching you my company. What I’m really looking for is a mutually beneficial relationship where you have to deploy money, because that’s your business, and I need money to make my dream come true”.

If you pitch, have a discussion instead, a conversation that could potentially lead to something. Don’t ever make it 60 seconds because if you have to sell yourself in 60 seconds to somebody — you are at a huge disadvantage, it’s never going to happen, waste of time. Put yourself in a situation where you have at least half an hour meeting.

How can our readers follow you on social media?

You can find us on Twitter: @datasine

Thank you so much for joining us. This was very inspirational

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