In the era of big data, offline stores are increasingly using technology to track the purchasing habits of their customers and boost sales revenues. The retailers believe new technologies will help serve the customers better and enhance the value and profit from every transaction.
The first step is to monitor the buying habits of customers. For example, some fashion stores have installed cameras behind tailors’ dummies to collect information about the age, sex and race of their customers.
Also, some retailers have used sensors, cameras, wi-fi and bluetooth technology at the entrances or hallways to collect data and present them in the form of a heat map, which would help the retailer to adjust its sales staff and pick the best spot on the shelf or even attract new customers with promotions.
Retailers are enabled to analyze the data of passers-by, store traffic, duration of stay, and how many actually buy something. These data would help them adjust the business hours and sales techniques, arrange shifts of staff and layout or design to increase revenue.
A couple of years ago, an Italian dummy manufacturer installed facial recognition devices in their dummies. With the device, one shop found that a large number of Asian customers passed one entrance of their store at around 5 pm, so the store stationed their Asian employee at that entrance during the period. And theirs sales went up by 12 percent.
Another store found most passers-by and customers were teenagers, and decided to add teenage products to the offerings, which now account for 11 percent of the outlet’s revenue.
In addition, data could help stores unleash huge potential. According to the US Mobile Application Market Report in 2014, people spent 7 minutes on applications out of every 8 minutes used on mobile devices. Customers expect shops to customize the products, services and shopping experience with the help of real-time data. For example, some applications can help the store find what song a target customer is listening to on his/her mobile. The shop can then play the same song when the customer appears.
Supermarket customers usually care about their experience at the cashier. Therefore, an app can combine facial recognition technology and the customer’s historical purchase data to provide tailor-made promotion message via text messages, email or mobile apps.
And some food companies have launched “smart shelf” with facial recognition technology. The “smart shelf” will recognize the seven emotions of the customer, namely anger, sadness, fear, disgust, contempt, surprise and joy. If an angry customer is in sight, the store will arrange more staff or make other arrangements.
However, privacy is a key issue when retailers collect customer behavior data, which can easily become the target of hackers. Also, some customers are uncomfortable in letting shops use their data or track their behavior.
This article appeared in the Hong Kong Economic Journal on Jan. 21.
Translation by Julie Zhu
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