CUSTOMER PURCHASE MISSION SURVEY IN A LARGE COMMERCIAL NETWORK

As the Customer expected, as part of the research cycle, answers to phenomena that are difficult to answer with ready-made analytical algorithms, we have built dedicated video analytics sets, consisting of both reputable software and specially created analytical algorithms. Thanks to this, we have obtained a combination of tools that allow you to get the right results. Then camera sets were installed in the chain of stores and measurements and tests were made. A large amount of data and their proper correlation allowed to draw conclusions from the study, how to improve the service and layout of stores, so that customers notice changes and what are the motivators and limitations of store visitors. Importantly, all data was analyzed only statistically, without the possibility of profiling specific consumers.

The study uses advanced algorithms, such as:

• Customer classification
• Strife
• Temperature-directional distributions
• Time Compressor
• Tag & Track

and other