Video analytics in retail
Video analytics in retail is used to collect the information about customers, their numbers, distinguish those according biometrical markers (sex, age, and ethnicity), put the data into the database and make the attendance records with the dividing customers into “new comers” and “repetitive goers”. This system allows you to provide the visiting statistics quickly and simply, create a target audience profile, study customers activity and correct advertising campaigns given target audience of a brand or a shopping centre.
What else the video analytics in retail is capable of
With the help of the video analytics it is possible to:
- Predict the sales depending on a day of week or time of a day;
- Evaluate the efficiency of a business and estimate the conversion rate of visitors into buyers;
- Develop data to estimate the efficiency of the advertising campaign;
- Lower personnel expenses through correcting the number of employees (given the intensity of the customer traffic);
- Analyze the behavior of clients: to define “dead corners” where almost no visitors to be seen, to map out the goods outlay given the volume of the customer traffic, to evaluate the profitability of shop-windows etc.;
- Analyze the behavior of adult customers standing in a line and coordinate the number of cashiers;
- Study the personnel activity, track the clock-in time and clock-out time, make record of a break duration;
- Evaluate a customers’ attention according to their location (what shop-windows, stand-ups, advertising billboards are found nearby) and head movements so as to identify which advertising tools are better in drawing attention.
Advantages of video analytics in retail
- The system prize is no less than ten times cheaper than alternatives with more complicated hardware solution;
- The system can be adjusted for solving virtually any problems;
- Data analysis and reports formation is automated which means that additional operational personnel is not required;
- Fast and efficient cost and marketing campaign minimization.