Demographic People Counting

In addition to traditional visitor counts Pysenses in the entrance area of a shop provide data about age and gender of the prospects visiting. By knowing which target groups visit different stores at different times, your in-store marketing can easily be adjusted to meet their needs and preferences.

Demographic Scanner Data Analytics

Pysenses installed in the check-out area allow us to combine sales data (UPC scanner data) with demographic data. We use this information to identify the most profitable customer groups and to analyze which brands they prefer and how they react differently to marketing activities. By comparing this data to demographic visitor counts from the entrance area of the shop we calculate the conversion rates for particular target groups.

Store Window Performance

Store front windows are increasingly important for presenting a company’s cooperate identity. Moreover they attract the attention of people passing by a store, stop them and finally get them to visit. Hence the window design is crucial to attract desired target groups. Pyramics measures the performance of your window design. In this process we monitor the overall traffic passing by the window, the number of observers looking at it and the number of stoppers, who examine the window design more closely. The duration and frequency of views towards the window gives further insights into the observer’s interest. Additionally we capture information about age and gender and the emotions observers show (laughing, astonishment, anger and sadness).

Advertising Effectiveness of In-Store Displays

Similar to the store window performance measurement, Pyramics measure the Advertising effectiveness of in-store displays. Our sensors distinguish between traffic, observers and stoppers and provides data about the frequency and duration of views towards the display. By matching the time stamps of this interactions with the play list of a digital display the information can be assigned to certain ads running on the display. This allows us to examine the effects of ads on different target groups by running split tests (A-B Testing). [mehr]