Date
17 August 2017
Facial-recognition technology can help retailers determine whether a person is a new or regular customer the moment he steps into a shop. Photo: Internet
Facial-recognition technology can help retailers determine whether a person is a new or regular customer the moment he steps into a shop. Photo: Internet

Big Data: How it will transform our daily life

“Big data” may sound like a fancy buzzword, but the fact is that the technology that it underscores has already begun to change, among other things, the lives of shoppers and retailers.

When a person checks out at a WalMart store, he receives some coupons along with the change and the receipt at the cashier.

By digging into its database, the US retail giant is able to tailor the coupons on offer based on the customer’s previous shopping preference.

If WalMart recognizes that you have been buying oil control shampoo for the last three years, then it won’t hand out a coupon that offers discount on dry-hair shampoo products.

Retailers can use big data to help them understand their customers better. The industry is able to leverage the statistics and be more innovative, as Che Pinjue, Alibaba’s vice president and head of the group’s Data Committee, wrote in StartupBeat, a news site belonging to the Hong Kong Economic Journal.

The evolution of big data technology is taking the industry to the next level, noted Che, who has authored a book “The Business Revolution: Big Data”.

Usually, shop assistants can only recognize regular customers. But help is on the way.

An intelligence software group in China has recently developed a face recognition technology which is said to be even more advanced than the one used by China Customs. It can tell whether the person is a new or regular customer the moment he steps into a shop.

This technology will have a big impact on the retail industry, according to Che.

With the latest facial-recognition technology installed, a shop assistant can know exactly what and when a customer bought last time. Instead of asking questions like “How can I help?”, the salesperson can now be more specific by pinpointing products that the customer is likely to be interested in based on his purchase history.

One needs to be imaginative in order to ride the data science industry, Che noted.

Here is something that may possibly happen in the future.

Say you are a coffee-lover, and every day, you would grab a cup of coffee at the street corner near your office.

In the future, when you are on the way to your office, your smartphone will send out your position through the GPS system to your favorite coffee shop, which will automatically confirm if you want to order your usual favorite by texting you. And when you arrive at the shop, a steaming-hot Latte will be waiting for you!

In case you are in a mood for something other than Latte today, you just send a message back and the café will make other recommendations for you.

Our life will certainly be different because of the use of big data. Interactions between customers and merchants hard to imagine in the past could all become part of daily lives.

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RC

EJ Insight writer

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