How Can Artificial Intelligence Transform The Retail Industry
How Can Artificial Intelligence Transform The Retail Industry

A quick search on your phone is no longer a one-way communication. From leading you to your nearby store to helping the retailers understand the consumer behavior, Artificial Intelligence (AI) is finding its strong foot in retail landscape. Soon, you may no longer have to remember what you like or what you wish to buy.

From visiting a mall to shopping on e-commerce sites, preferences of the millennials are changing and so are the shopping trends. While new tech trends have been the only constant, the latest buzz in the retail landscape is the presence of Artificial Intelligence (AI). From retailers to e-tailers, the consumers for AI are available in plenty.

According to reports, the latest tech giant to join this bandwagon is Flipkart, which is experimenting with AI to help customers get easy access to product reviews.  Highlighting that thousands of user reviews are now available online for any product ranging from electronics to apparel, Vice-President (Product) of Flipkart, Ram Papatla has maintained it was impossible for users to consume all the information that was available on the marketplace. 

Flipkart, which is working towards improving the customer experience by assisting them with what matters to them, will offer a quick reference search for the users to compare various products. While its rival Amazon has gone ahead and introduced BLINK, a video commerce option for customers to watch and buy, it’s yet to venture into other trends.  

However, noticing this upward trend in retail tech space, homegrown commerce platform company Capillary Technologies has launched VisitorMetrix, an AI-based, machine learning-powered visitor counter for retail stores to analyze customer behavior on the shop floor.

According to its makers, VisitorMetrix will provide valuable insights through its real-time dashboard and trend analysis engine, which will offer to help brands and shopping malls understand the ‘power hours’ of their stores.

The AI embedded in VisitorMetrix is fed with over 3 Million images in order to train it to accurately identify between human and non-human objects and between individual and group walk-ins.

With the ability to study trends in footfalls across hourly, weekly, and monthly time periods, in addition to analyzing the frequency of visitor trends, brands will have the information to more efficiently allocate manpower resources according to the specific demands of their retail locations.

Commenting about the product, Capillary Technologies COO Ganesh Lakshminarayanan, said, VisitorMetrix enables brands to analyze store traffic patterns to determine staffing requirements and can also give immediate responsive data to changes, including studying the impact of promotional campaigns. Brands can use this information to strategize their operations and marketing campaigns.”

He added that the benefits of the product was not restricted to brand stores, but extended to shopping malls as well.

“It will assist shopping malls in analyzing their layout effectiveness and understanding their circulation better. This would strengthen their strategy in improving square feet productivity, creating the right ecosystem for both brands and consumers for a great retail experience,” he said.

VF Brands, which has some popular lifestyle brands in its kitty including Vans, Wrangler, and Lee, has deployed VisitorMetrix across 6 cities and has signed up to roll it out across 70% of its stores in India.

Commenting about the benefits of VisitorMetrix, Pankaj Agarwal, Retail Director of VF Brands said the goal was to optimize their resources to enhance the value for the consumer at the store.

“Being the innovation leaders in the denim space, at VF Brands we wanted to enhance the performance of our stores through technology. We will be using VisitorMetrix’s real-time analytics capability at 70% of our brand stores across India. This will help us measure the store KPIs accurately, giving us a strategic edge in enhancing our ability to influence the store performance as well as to feed in analysis required in product and backend to support the stores effectively,” he said. 

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