Age & Gender Recognition
Our system for the analysis of the demographic customer structure determines the age and gender as well as the number and viewing time of individuals in front of various advertising campaigns.
Professional visitor frequency measurement provides retailers with important data for analysing individual locations. This analysis then forms the basis for further location optimisation.
Nowadays, visitor frequency measurement is not limited to the number of visitors, because visitors can only be categorised accurately once demographic data such as age and gender has been collected. By understanding the age and gender structure of their visitors, retailers can draw much more detailed conclusions for location optimisation.
Gender and age detection allows you to get to know your customers better:
- Analysis of customer structure by age and gender
- Better alignment of marketing activities with target groups
- Potential increase in advertising effectiveness
- Execute actions based on recognition, e.g. display target group-specific advertising on screen
- Analysis of data in our evaluation platform
- 100% compliant with data protection regulations, no storage of personal data
Location optimisation through demographic customer profiles
Counting foot traffic and visitors has become standard practice for many innovative retailers. It gives retailers a much better understanding of visitor numbers in and around their stores. This allows them to analyse peak and off-peak visitor times and better coordinate staff deployment. They can also derive other key figures such as capture rate and conversion rate. In-store analysis, in turn, can be used to identify low- and high-traffic sales areas in order to further optimise the location.
An in-depth demographic analysis of passers-by and visitors helps retailers to understand their visitors even better. In addition to identifying gender and age, the mood of visitors can also be analysed in a manner that complies with data protection regulations. Depending on the application, it is even possible to identify children, animals, shopping baskets, bicycles or the number of people shopping together.
Retailers can use knowledge about age and gender structures in particular to further optimise their locations. On the one hand, this makes it possible to tailor advertising measures and product ranges even more closely to the demographic structure of the visitor base. On the other hand, it gives retailers the opportunity to target advertising measures and product ranges more specifically at target groups that are not yet strongly represented.
Data protection-compliant technologies for gender and age recognition
Image recognition technology has made enormous strides in recent years. This means that existing camera systems can be used for comprehensive customer analysis and supplemented with 3D sensors if necessary. Cameras with 3D sensors capture all visitors with extreme accuracy, and the technology complies with data protection regulations. This is because no images or videos are stored. The demographic characteristics are evaluated anonymously and in real time. The data collected by the sensors is then deleted. This means that no conclusions can be drawn about individual persons.
Crosscan can provide both processed raw data and implement external reporting with all data. The reporting platform also offers the option of integrating additional data and key figures to obtain a complete picture for data-driven decisions. For example, operational performance can be compared with previous periods, industry-specific benchmarks or between different locations. To ensure maximum system availability, Crosscan can optionally take over system monitoring.
Crosscan as a partner for age and gender recognition
Retailers face a variety of challenges. Competition from the internet, changing consumer preferences, urban regeneration, economic crises and declining sales are just some of the current challenges they face. Despite these challenges, a large number of retailers are successfully driving their business models forward. This is because they are doing something differently: they are not relying on gut instinct, but are laying the foundations for data-driven decisions.
The insights gained from identifying the age and gender of visitors can provide important impetus for further location optimisation. Crosscan supports you in implementing and operating the systems necessary for data collection.
More than 1.000 brands and companies
already trust in Crosscan.
Do you have any further questions about age and gender recognition and visitor frequency measurement in the context of evaluating retail analytics data?
Please feel free to contact us for further information – we look forward to hearing from you!