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3 Novel Ways to Transform Customer Experience Using AI in Retail
3 Novel Ways to Transform Customer Experience Using AI in Retail

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There is a constant retail hunt to seek new ways to transform customer experience. With Artificial Intelligence in Retail, Augmented Reality and Machine Learning proving transformational in terms of promoting enriching customer experience, the promise of using AI in retail and most-modern technologies to ensure an ‘intelligent retail’ leads to enriching customer experiences is not lost on the retailer.

There are some areas that seek novel ways of using AI in retail – The customer waiting in a queue for his turn to bill the products purchased or the time spent waiting to enquire about a product, among other retail scenarios, set AI in perspective.

While such scenarios can blot the ‘zing thing’ from customer experience, what’s encouraging is the fact that Artificial intelligence and other modern technology components can galvanize such challenging scenarios and empower retailers to earn customer delight.

Here are 3 novel ways of transforming customer experience using AI in Retail.

AR and using AI in retail for driving personal ads

Anna walks into a retail store. Flipping her mobile, she turns to a new product variant on the shelf. As she directs the mobile-focus on the product, the object is detected initially. Then AR takes over. There is this promotional ad of a product jumping at her.

The same Anna can also go over to a display board in the store. In keeping promotional ads as the key point to drive customer engagement and interest, this display board at the store works in tandem with AR technology. As the customer scans the display board with the mobile device, out pops the 3D version of the promotional ads.

But what if Anna is a customer who has done shopping at this retail outlet?

We have her transaction data as we have her personal details to work with. Richer the data is around Anna, richer the insight we get to feed a promotional ad that can be more relevant and that can evoke a positive action on the part of Anna. There’s Wi-Fi factor that allows Anna’s identification initially, followed by the serving of the recommendation for Anna in terms of serving the best promotional ad for Anna. The analytics-rich recommendation engine powers the personalization of promotional ads depending on the customer who sets the trigger, well supported by data associated with the customer – wherein behaviors, preferences and past activities offer the feed for the recommendation engine to come up with the most relevant promotional ad for a customer.

AI in Retail, AR, and ML to give great customer experience and take customer data

Mobile device is now a surefire route to get to the customer faster. The mobile device can also serve as the retailers’ weapon to take customer experience up by a notch. This boils down to object detection and data collection.

Imagine a customer scanning a product on the shelf using his mobile – scanning to get the details of the product. Is it possible for the customer to get product related details like the MRP, Best Before, Ingredients and other details on his mobile just by making the mobile hover over a product?

We can put a trained Deep Net model for object detection only to be followed by the work of AR to put the 3D world in front of the customer, on the mobile, with all the product related details. The customer is thrilled and he has the information to make the buying decision – for one we have brought the medley of AI and AR to speed up customer decision making process.

Extending beyond the ‘Giving the customer a great customer experience’ in this scenario, retailers can also ‘take back data from the customer’. As the customer gleans product details through AR driven pop-up on the mobile, a novel feedback form using emoji or other such customer-loved communication tools can be used to collect customer-related data such as their likes or dislikes. Text analytics and behavioral analytics then guiding the retailer to know more about customers and tune their business to meet their needs.

Say for instance, the novel feedback could throw a query like this:

Did you find it easy to locate the product?

The feedback can help the retailer in many ways by collecting data from customers – across product assortment, promotions, and store layout among other things.

AI push to enable ease of payment

A long queue at the Retail POS. Customers are waiting to pay for the stuff they have picked at the store. But what if the customer is able to pay for all the products he has picked using his mobile without having to wait to pay at the POS?

A customer scans a product that he is going to buy using his mobile. Computer vision and AI are put into action for object recognition. This happens every time a product is being scanned to be purchased. AR takes over to project the product, price as well as the total number of items picked and the total amount the customer has to pay – on the customer’s mobile. Now, using online payment sources like Paytm or Phone Pay, the customer pays the bill and beats the queue. This train of events also gets recorded at the retailer’s database for the professionals at the retail store to get a gist of transaction details pertaining a customer.

AI in retail holds promise to brighten every customer experience we can think of. The unseen opportunities and the latent needs in retail only makes the role of AI even more promising in retail. Artificial intelligence in retail, with the customer at the core, with their needs, preferences and experience to be addressed, has a lot more to offer.

This blog was originally posted in saksoft.com


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