Start-up AssetFloow provides AI behavioral analysis in stores | Jobs Recent


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About AssetFloow

  • Founders: Katya Ivanova and Ricardo Santos
  • Year of establishment: 2021
  • Employees: 5
  • Money raised: €100,000 (2021)
  • Ultimate goal: to become the European benchmark for human behavioral analysis in confined spaces.

When the layout of your favorite store suddenly changes, have you ever wondered what was the motivation for that change? Lisbon, Portugal-based start-up AssetFloow uses AI to analyze customer behavior and provide insights that help these changes potentially increase sales. The co-founder of the company, Katya Ivanova, explained the methods and secrets of AssetFloow for today’s Start-up of the Day.

Where did the idea for a start-up come from?

“Since my co-founder and I had experience in sales, we started debating how to solve one of the biggest problems in this sector, which is the analysis of consumer behavior in stores. My co-founder had a video analytics company and we tried to capitalize on that model. However, this has been shown to be unsustainable in large stores that have several branches. We then decided to combine sales data and store mapping in our analytics software to get insights and suggestions on how to increase sales.”

How was the process of creating technology for your company?

“The AssetFloow AI software focuses on behavioral analytics. It manages to analyze and optimize in-store customer tracking. It then analyzes customer behavior, gaining insights that can enrich their in-store experience and increase sales. We developed an algorithm called Behavioral AI, which is our intellectual property.”

What tools can your customers use on the platform?

“We have separate analyzes such as segmentation, customer tracking, anomaly detectors, and others. It is an easy-to-use platform with a dashboard that outlines store performance and measures which taxi to take. We also have tools such as simulations that allow the retailer to test these measures and get predictive results before implementing them in practice. And an optimizer that will suggest the best layout for that particular store.”

Can you give some examples of some aspects that behavioral AI analyzes?

“The first step is to analyze sales data and compare them with the store layout, which is essential. Based on this data, the software will classify purchasing patterns to extract specific segments based on the ratio of customers per store. Therefore, each store is treated individually, because each has its own special and unique type of customers. Once this segmentation is sorted out, we extract relevant information, such as the time it takes a customer to select a particular product.”

What problems did you have to overcome?

“Initially, one of the problems was putting together a team, which required a lot of money. Also with our technology, gaining the trust of the store owners was difficult at first. There was some reluctance when we said we could track customers without the usual camera sensors. But in the end, we won their trust.”

Was it difficult to get financial support and recognition?

“At the end of 2020, we were competing against two hundred teams that use camera sensors while we use AI. But we won. This was the first proof that our technology can compete with other companies. My experience and networks helped with the recognition process and we started attracting our first clients in Europe and even in Brazil. In October 2021, we secured the first round of investment, which allowed us to hire more technical experts.”



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