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Shopper Behavior Tool

Everything about the Shopper Behavior Tool


What is a Shopper Behavior Tool?

A shopper behavior tool is a people tracking technology that captures the time and location position of objects (in motion) to quantify store performance and analyze in-store (anonymous) customer behaviors. It helps answer the following questions: At what times do shoppers visit your store and in what way do they act? Plus, how does this impact sales? Retail businesses have to address such issues in order to improve the customer purchasing experience which helps in getting higher conversions. To achieve this, retailers need access to a vast array of innovations in the marketplace such as Shopping Behavior Analysis Software that gauge the consumer behavior. There are a whole host of aspects that control the manner we shop and what motivates us to carry out a purchase. To build up successful buyer marketing tactics, retailers need to understand how their customers go about making a purchase. For example, do your targeted shoppers make choices based on pack size, brand, advertising, price, claims, flavor or a grouping of these features?

How can Shopper Behavior Analysis Tool be used?

A shopper behavior analysis tool generally includes detection, recognition, and predictive analytics of objects in motion. The complexity depends on the location of objects (i.e. store or street), the dimension of objects (i.e. a person or image), and details of the image (i.e. facial recognition or facial demographics).

In the past, brick-and-mortar firms employed loyalty programs or buying receipt information to understand their shoppers and the preferences appropriately. However, data obtained from these methods can often not be compared to other relevant to other pertinent criterion known as key performance indicators (KPI). It is for this reason that customer footfall measurement and customer behavior analysis are increasingly elevated to a digital level. This is how in-store tracking, using shopper behavior analysis tools, is getting nearer to what web-based retail has already been doing for a long time.

Why Shopper Behavior Analysis Tools are important

The best way to think about shopper behavioral analysis tools is in terms of the business benefits. An example of an in-store shopper behavior analysis tool is People Counting or Object Detection. This tool help retailers “count” the number of people that either pass a virtual line or stay inside a specified zone. This lets retailers make deductions about navigation systems or store design. The same also applies to visual merchandising to analyze how store window displays or entire retail store concepts have to undergo target readjustments to achieve improvements. Common technologies include: Audience Analytics, Time of Flight, Infrared Beams, and Thermal Imaging.

In addition, such tools lend themselves to target audience and product analysis: category managers gain insights into the performance of individual sales areas or products and can thus quickly respond to a lack of interest and wrong placements but also draw conclusions on successful campaigns and promotions.

The business benefits for people counting relate to measuring the number of visitors, sales conversion, store comparison, and mall analytics.

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Technical Specifications

The table below shows how FaceMatch SDK performs on the Labelled Faces in the Wild (LFW) dataset:

FPRTPRThreshold (Inverse of distance)
0.10.99900 ±0.002130.55448
0.010.99667 ±0.005370.59791
0.0010.99367 ±0.006050.62989

FPR = False Positive Rate
TPR = True Positive Rate

These results are an indication only and are based on the specific dataset Labelled Faces in the Wild. Customers can expect similar performance, with possible variations due to hardware and the availability of annotated data.