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There is pressure for businesses to leverage digital platforms to assure brand loyalty and customer retention. AI has empowered businesses to provide a connected retail experience.

How AI is transforming retail

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In this age of Amazon and eBay, shopping is no longer a time-consuming affair that involves negotiating traffic to visit your favorite stores. We now have access to millions of brands and businesses in our smartphones. We have the option to pick and choose and compare across brands. In fact, we shop on our own terms. 

Under this new retail climate, there is more pressure than ever for businesses to leverage digital platforms in order to stay connected with their customers to assure brand loyalty and customer retention. In the past decade, AI has empowered businesses to provide a connected retail experience.

Why every retailer should adapt AI

As retail evolves, so do customer expectations. Brands can no longer rely just on brick-and-mortar stores; they need to attract customers by connecting with their customers in a holistic manner. They have to be on the channels that they frequent – social media. Today, the digital presence of a brand is its mainstay, and the stores an extension of this presence. 

Constant brand visibility is key to survival, and this calls for some first-class digital marketing. Customer demands are fickle as well as numerous. The key demand is speed: quicker information, quicker checkout process, quicker delivery. Customers want a personalized shopping experience, complete with relevant product recommendations and the best in prices. 

With millions of retailers competing to provide similar services, how do brands effectively engage and retain customers? This is where Artificial Intelligence (AI) proves essential. 

AI is what helps brands attain that level of personalization that the user expects; it is what makes him add those extra items to the cart and spend those extra dollars even though that wasn’t the original plan. The success of AI in retail is exemplified by top brands like Amazon, which provide the customer with a seamless, individualized experience.

Are you on the right channel, at the right time?

E-commerce is growing at a fast pace, but this hasn’t rendered physical retail stores redundant. It is projected that 83% of goods purchased globally in 2022 will still be bought in-store according to Euromonitor International. The store now fulfills the purpose of delivering a high-quality experience to the customer that is both sensory and memorable. 

What drives the customer to a particular store? What makes him aware of a particular brand or where it has its shops?

The answer – online presence. The greatest thing about social media is how it becomes a habit by offering a highly individualized experience to the user based on his unique tastes. Facebook, Instagram, Snapchat, Twitter, and Youtube are just a few of the many platforms frequented by audiences from across the world. And where the customers are, brands follow. Online sales are now driven by brands reaching their audiences through these channels. 

These channels provide the option of placing ads in a variety of ways to effectively pique interest. And you can have the complete shopping experience – from recommendations to payment processing – all on the same channel. 

The challenge with data

Global connectivity means data generation is happening by the nanosecond. And retail’s big challenge is bad data. Lack of accuracy and incomplete data costs US businesses $3.1T annually, according to IBM’s estimate.

Data is the key to building a personalized marketing strategy. Accurate data is necessary for optimizing, automating, and enhancing retail processes. AI technologies are essential for effective data analytics.

The rise of connected retail

Gartner defines connected retail as “Providing a customer-centric experience, based on how customers approach shopping with no limitations by channel.” 

Connected retail works because of the ability of AI to sift through any amount of retailers’ data. Based on these results, retailers can offer individualized services to customers, who avail them on their own terms, at their convenience. 

Omnichannel customer engagement brings value addition in terms of customer satisfaction and retention, with the likelihood of increased customers through recommendations from existing ones.

AI in retail

Retail is among the top industries where AI adoption has been most actionable. AI serves at all points in the retail process – front, back, and middle. Operational efficiency is augmented and risk management is enhanced with AI tools. Inventory management, cataloging, customer service, post-purchase engagement – these are important areas in which AI is making its impact felt.

10 use cases of AI in retail

Data creation and labeling 

AI creates accurate, SEO-ready metadata for every product during digitization. This boosts product discoverability on search engines. Metadata generated at each search gets indexed by search engines; this when combined with customer ratings and reviews, leads to increased sales.

Data insights 

The purpose of data analytics is to gain actionable insights for business. ML predictive and prescriptive algorithms can be used to forecast future demand trends and enable businesses to make better decisions.

Supply chain efficiency 

AI avoids leftovers and out-of-stock scenarios by keeping track of a product’s history, sales, demand, and myriad metrics. This also helps stock replenishment.

Product Discovery 

AI assures that search engine results are relevant to the user’s tastes by tailoring them to match user needs. Every click of the user serves as added data for a hyper-personal search bar.

Visual merchandising 

AI-powered on-model fashion imagery offers customers a virtual trial room experience, with models of diverse body types and ethnicities. Though still a nascent innovation, this is already reducing the cost of product visualization through photoshoots. 

Real-time personalization 

AI helps real-time personalization with every click of the user. Real-time user intent updates enable retailers to offer the best recommendations likely to end in a sale.

Curation 

Fashion brands use AI to offer styling options for customers personalized based on their search history. This curation offers customer satisfaction and increased sales for the brand.

Visual search

Visual search and Image Recognition AI help customers to upload pictures to find similar products. The Find Similar feature of Amazon and other big names are highly accurate and very useful for customers when they want to buy something similar to but cheaper than a particular product.

Cart abandonment 

AI serves to auto-send compelling cart recovery emails to those users who abandon their carts for whatever reasons. This helps brands to retain customers and ensure sales.

Customer behavior prediction

Customer behavior analysis makes brands better understand their psychology to increase purchase. AI studies the user’s responses and behavior in the past for purposes of price-setting.

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