Brands use emotion AI to improve customer in-store experience

For Pizza Hut, the mechanics for potential consumers are simple. Simply stand in front of your device, look at the screen, and let the detector adjust your mood before receiving pizza recommendations.

The device uses statistical models that examine facial expressions by analyzing eye movements, smiles, and frowns captured by cameras. These patterns are compared against a database of publicly available images to ensure accurate recommendations, explains Anandita Dutta, Chief Marketing Officer of Pizza Hut India.

“Through the development of our AI mood detector, we have mainly focused on creating a seamless and safe experience. The AI ​​system stores facial patterns as numerical data and does not hold images in any form. Therefore, protecting your privacy is our top priority.We have worked with Ebullient Gaming India to develop this AI tool,” added Datta.

She explains that the tool allows for a fair degree of customization to accommodate different tastes based on the customer’s mood.

With different moods to choose from, including happy, sad, and angry, the device offers recommendations among 10 new pizzas the chain has launched. It’s still early days, but Pizza Hut says it’s getting an enthusiastic response, especially from younger customers.

Meanwhile, Reliance Retail introduced a “Fragrance Finder” to its omnichannel beauty store, Tira, in April. AI devices can help consumers find the scent that most closely matches their taste, allowing them to choose a scent based on a range of machine-recommended perfumes.

Similarly, the outlets of Reliance’s fashion and lifestyle brand Azorte have introduced technological interventions, including smart trial rooms. A touchscreen tablet is installed to display the entire inventory available at the store. Click on the clothes you like and the staff will bring them to the fitting room.

Tablets let you choose color, price, and size. If you want to know how to match clothes, the digital catalog uses AI to provide suggestions. The algorithm recognizes designer-chosen pairings and learns what customers want after inputting data collected through weekly billing. Designer recommendations that do not match the buying pattern then disappear from the offer to the relevant customer.

BCG partner Rajat Mathur points out that the consumer industry is putting a lot of effort into leveraging AI.

Banks, for example, are leveraging hyper-personalized nudges supported by customer DNA of over 2,000 behavioral variables. “These are curated specifically for private customers through AI and data. Traditional analytics doesn’t do that.”

Second, Mathur says that in the retail industry, properly pricing inventory units that serve a business purpose (profit or revenue maximization) can only be achieved through AI algorithms. And third, he can also leverage external data sources, such as social media trends, at a very granular level to support new product development so sellers never run out of stock.

Additionally, image or computer vision and video analytics provide real-time recommendations to help brands engage customers with more targeted conversations.

Ranjan Kumar, founder and CEO of Entropic Technologies, a seven-year-old emotional AI company, said the coronavirus pandemic has forced companies to sell more products online. The use of AI assistance for customer engagement has increased during the pandemic, he notes.

Historically, brands have understood their consumers through two approaches. Some are based on questionnaires in which respondents rate their products, others are through direct interviews and focused discussions in his groups, Kumar says. “The problem with both is that they are stated responses and are usually biased.

Entropik is focused on enabling a deeper understanding of the irrational and subconscious side of consumers. During his first three years, he built technology for face coding, eye tracking, and voice AI. “Faces, voices and eyes are his three main sources of information for us to better understand our consumers,” Kumar says.

Entropik seeks to help its clients (P&G, Tata, Mondelez, Unilever, ITC, Reckitt, etc.) understand their consumers better using multimodal emotion AI technology.

Kumar said examples such as Pizza Hut’s mood detector show brands are experimenting with AI on live users to understand consumer perceptions. It has been.

For apparel brands and jewelry brands like Tanishk, the trial mirrors have embedded cameras that track facial expressions and provide recommendations to customers based on that, Kumar said. “These are some of the more actively emerging application areas for AI in the retail environment. Although the technology has matured, large-scale applications in live scenarios are still limited. We use cameras to track consumer reactions and can only do so with their consent.”

After the pandemic, Kumar observes, people have become more open to granting access to cameras to get product experiences. “It’s the same people who didn’t make sales calls on Zoom before. Now it’s perfectly fine to make business calls on Zoom with consent to be recorded,” he said, noting that the threshold was crossed. , noted that more brands are likely to adopt the technology in the future.

Different industries are at different stages of AI adoption. Sectors involved in the sale of high-value assets are more readily receptive to emotional AI, Kumar said. For example, luxury automobiles, jewelery, and luxury brands are more likely to adopt it than retail hypermarkets, where purchasing is functional rather than aspirational, emotional, or impulsive.