5 Top In-Store Customer Analytics Startups Impacting Retail

5 Top In-Store Customer Analytics Startups Impacting Retail

We analyzed 193 In-store Customer Analytics startups. Decision6, Shoppermotion, Cubelizer, Signatrix and Pygmalios develop 5 top solutions to watch out for. Learn more in our Global Startup Heat Map!

Our Innovation Analysts recently looked into emerging technologies and up-and-coming startups working on solutions for the retail sector. As there is a large number of startups working on a wide variety of solutions, we decided to share our insights with you. This time, we are taking a look at 5 promising in-store customer analytics startups.

Heat Map: 5 Top In-Store Customer Analytics Startups

Using our StartUs Insights Platform, covering 1.116.000+ startups & emerging companies, we looked at innovation in the field of in-store customer analytics. For this research, we identified 193 relevant solutions and picked 5 to showcase below. These companies were chosen based on a data-driven startup scouting approach, taking into account factors such as location, founding year, and technology among others. Depending on your specific criteria, the top picks might look entirely different.

The Global Startup Heat Map below highlights 5 startups & emerging companies developing in-store customer analytics for retail. Moreover, the Heat Map reveals regions that observe a high startup activity and illustrates the geographic distribution of all 193 companies we analyzed for this specific topic.


Click to enlarge

Which startups develop the other 188 solutions?


Decision 6 – Customer Footfall Analytics

Information about the footfall of customers is being tracked by many commercial stores and public spaces. However, they do not always have the opportunity to extract insights from this data. Store traffic analytics intend to provide decision-makers with better actionable intelligence for optimizing store operations.

Brazilian startup Decision 6 is a retail analytics platform developer focused on brick and mortar stores. Their analytics solution uses artificial intelligence (AI) and deep learning to track the flow of customers into and out of a store. This information is then used to optimize single store operation and also compare the footfall data among different stores to measure their performance.

Shoppermotion – Customer Path Analytics

A customer interacts with many items or products in a store, which influences their purchasing decisions. Startups working on customer path analytics allow tracking and weave together all the points of a customer’s interaction within a store to provide better decision-making support for marketing and product placement.

The US-based startup Shoppermotion develops a customer behavior platform that provides real-time tracking of customers using proprietary indoor geo-positioning, big data, and machine learning algorithms. The platform provides marketing executives with real-time data about the behavioral patterns of their customers to enable the precise targeting of customers.

Cubelizer – Environment Analytics

In a commercial shopping environment, there are many different data points that represent a source of actionable intelligence. By quantifying analytics from various environment patterns such as footfall, customer pathing, queue times, and more, stores receive the opportunity to optimize their assets for full utilization.

Spanish startup Cubelizer develops an artificial vision system that anonymously collects data from customers. It includes customer count, paths, and interactions in a store, all in real-time. The platform translates this data into information, available for performance improvements of a store’s products and assets.

Signatrix – Point of Sale (POS) Tracking & Analytics

In large retail environments, it becomes critical for store employees to work efficiently and vigilantly to ensure that the checkout process goes smoothly and that customers have a good experience. Using analytics to track the customer and the items being billed, POS tracking platforms enable a faster check-out while reducing employee errors.

German startup Signatrix develops an AI platform that uses machine vision cameras to anonymously track customer’s items during checkout. It allows the cashier to process items faster and ensures that none of them are being missed. Signatrix’s platform also offers the feature of scanning carts at the entrance to detect goods that have not been paid for in order to alert store employees.

Pygmalios – In-Store Customer Analytics

Stores usually collect data from different types of sensors. As the number of tools and platforms required to process all these types of data increases, the cost-to-performance ratio of the technology begins to decline. Startups are developing centralized platforms that process all the data types for a store and become more efficient in making decisions.

Slovakian startup Pygmalios designs a tool that collects all types of sensor data in a store and uses them to analyze customer’s behavior in real-time. This allows companies to optimize their product placement and customer flow all within a single cloud-based app.

What About The Other 188 Solutions?

While we believe data is key to creating insights it can be easy to be overwhelmed by it. Our ambition is to create a comprehensive overview and provide actionable innovation intelligence so you can achieve your goals faster. The 5 in-store customer analytics startups showcased above are promising examples out of 193 we analyzed for this article. To identify the most relevant solutions based on your specific criteria, get in touch.

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