Modern businesses cannot do without modern technology. These days, customers, especially younger generations, expect innovative solutions, personalized offers, and the luxury of high customer comfort. This is what engages their interest and convinces them to buy. Store management, therefore, needs “hard” data on their customers, which they can then use to give them a true shopping experience. Let us take a look at T-Mobile’s approach.
Solution to a problem
T-Mobile does not just provide mobile services; the company also has over 47 branded T-Mobile outlets all around the Czech Republic. In order to manage sales effectively, the company’s leadership need reliable data on which to base their decision-making on topics such as management, direction, and growing the efficiency of individual stores as well as the sales network as a whole. In the stores piloting technology from the Internet of Things (IoT), T-Mobile managers gain information about visit rates, customer demographics, and how interest in the goods on offer changes throughout the day and on the basis of ongoing marketing campaigns.
3 stores of 47 are working with real data about their visitors thanks to people counting and face recognition.
Business description of the solution
Adastra installed selected digital scenarios in three T-Mobile stores, using the IoT (Internet of Things) technologies that were deemed most fitting and best met the client’s needs. Initially, the project comprised pilot deployments of these scenarios, which are still being used today. Specifically, these include:
- a sensor mounted above the entrance counts the number of passages through the door
- subtracting “children”
- A sensor tracks customers’ demographic parameters (gender, age and mood) when they enter the store.
- It also monitors customers’ interest in displayed items, such as cell phone accessories, and in campaigns presented on LCDs.
- based on face recognition (i.e. gender recognition and the estimated age of the customer), the content screened on the interactive display in front of the customer changes, offering products appropriate to the target audience.
Interest in products
- monitoring how cell phones are moved on the shelves makes it possible to calculate customers’ interest in each selected device (the number of times it is lifted off the shelf and the duration it is in the hands of a potential customer).
All the gathered data is stored on Adastra’s central analytics platform, which uses Microsoft Azure cloud services. T-Mobile’s store managers receive daily/weekly reports in the form of dashboards or charts created in Microsoft Power BI.
A face image of 48x48 pixels is enough to identify a person (i.e. age and gender).
Thanks to Adastra’s IoT scenarios for retail, T-Mobile now works with real data about visit rates and customer demographics in the selected locations. Among themselves, the stores can compare and analyze customer interest in individual products and actual sales in connection with ongoing marketing campaigns.
In addition, T-Mobile can:
- Improve the experience for existing and potential customers.
- Communicate with customers in a targeted, personalized and appealing way.
- Involve the customer in “communication” with an advertisement (through the interactive display).
- Make operations more effective in individual stores and across the whole sales network.
- Evaluate the effectiveness of marketing campaigns (has the store’s visit rate increased, has the appropriate target group come to the store, have sales of the promoted product increased?).
- Compare stores (do levels of interest in promoted products differ in stores in large/small towns, in standalone stores or in branches in shopping malls?).
- Customize store design, displayed products, or the number and disposition of sales and service assistants (e.g. by having more “serious”-looking assistants in branches frequented by the elderly, compared with those visited by younger generations, where there should be more shelves with products and accessories for “testing”).
is the accuracy at which T-Mobile knows how many people are currently in the store.
Face recognition technology offers many options. It’s even possible to use it to establish marketing content, so the customer is only shown the particular advertisements that are really relevant to him or her. The technology has great potential that will benefit the customer: service in the store will be extremely efficient, and the time spent there will be as pleasant as possible.
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