You have mathematically described my whole business! Sergey Shopik, Head of Customer Experience Laboratory 25.03.2019
You have mathematically described my whole business! Sergey Shopik, Head of Customer Experience Laboratory

Efficient marketing is almost impossible in the future without artificial intelligence. This is the opinion of Sergey Shopik, a moderator of AI Conference.

Sergey is a data-driven marketing expert with 10 years of experience. He is the Head of Customer Experience Laboratory that integrates IT solutions for marketing automation. We talked to him and discovered how data could improve marketing, who would benefit from it, and how difficult was to integrate similar IT products.

Interviewer: AI Conference Moscow (AIC).
Respondent: Sergey Shopik (SS).

AIC: How did you get acquainted with AI technologies? How did you start applying them in your work?

SS: Curiously enough, everything started with computer games. I wondered how an unalive opponent interacted with me and even won. I wanted to find out what accounted for that miracle. It turned out that such a phenomenon was not so much miracle as mathematics.

I explored business intelligence tools in 2012. Back then, I participated in a project on integrating a customer analysis app for the filling station chain along with QlikView in Belarus. I was a client in the project. I felt like I finally would be able to work with data deeply and to show everyone the concept in the right manner. I remember my fear: here is a project and here are data, but there are more and more questions.

AIC: What was your most complicated and most successful data analysis projects? Tell us about their concept and goal.

SS: Any project aims to increase the business efficiency. Frequently, the most complex project is not always most successful.

The complexity of data analysis projects is related not only to calculations, but to data preparation. Sometimes, projects intended to last one or two months stretch out for half a year or more.

The most successful project gave the following outcome: 12% of lost clients returned in three weeks. By the way, the company long worked with this segment without result.

AIC: How did you come up with the idea of Customer Experience Laboratory? What encouraged you to establish it?

SS: Earlier, I held managerial positions at marketing departments of retail companies. I’ve been always seeing a lot of potential in data analysis. The majority of enterprises generally shift this area on the back burner. But I wanted to develop it.

At a certain point, I realized the necessity to assist companies in dealing with their data: to adjust point and system operations, to integrate the data-driven marketing concept.

Besides, I mentioned a gap between IT and real economy. One party understood how to implement this concept, while another comprehended the reasons. Both parties hardly ever arrived at a consensus. We decided to help them.

AIC: In what sector is data analytics most efficient based on your experience?

SS: Thoughtful intelligent data operations will have a positive impact on companies of any size and any areas. Conventionally, they include retail, telecommunications, banking sector, e-commerce, and GameDev. The given sectors are in a single list because of arranging large data volumes. Moreover, they feature severe competition and growth potential.

AIC: Is there a difference in implementing consulting projects for retail and for e-commerce. What is it?

SS: If you ask company representatives, they will answer “yes”. However, there is almost no difference. In both cases, one has data on sales, client, financial performance, and sales staff work.

E-commerce may sometimes seem more transparent. Customer’s digital footprint is huge enough: it can be tracked using the response to a certain ad, behavior on the website, goods delivery, and repeat purchasing.

AIC: Which of your own BI systems do you apply? What are their unique features?

SS: We have several solutions developed specially for clients’ projects. One of them is an algorithm calculating the purchasing cyclicality of certain goods. We use it to arrange the work with cyclic consumption products. Put simply, we remind people of goods they need to buy in addition at proper time. The algorithm is not unique, but it has proven to be efficient in our projects.

One more example is an automatic calculation for the RFM analysis. The greatest appreciation was a feedback by one of our customers: “You have mathematically described my whole business! This is the way my clients buy things!” It was an incredible pleasure.

AIC: How many customers does your Laboratory have? How much has companies’ interest in AI technologies in marketing increased over recent years?

SS: I don’t think that a certain figure will clear things up. We cooperate with major food and non-food retailers from Russia and Belarus.

I can say that there is the interest in technologies. But there is also a lack of understanding regarding their application. This is somehow thanks to IT representatives and vendors: they create unhealthy rush of one topic and complicate simple things.

AIC: Is it possible to provide efficient marketing in the future without AI technologies?

SS: It is possible, but its efficiency will consistently decrease. Fruitful marketing without AI can be organized by a company that realizes its expenses, growing points, and can build point customer relations. If one conducts carpet bombing instead of point relations, it will be hard to arrange marketing. By all means, it will be almost impossible without modern technologies.

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