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EXCLUSIVE: PwC provides insight on how retailers can use AI as personalization tool

Kelly Pedersen
Kelly Pedersen, retail lead, PwC

Artificial intelligence provides a broad set of benefits to retailers that use the leading-edge technology to enhance personalization.

Chain Store Age recently spoke with Kelly Pedersen, retail lead at PwC, about how AI can serve as an effective retail personalization solution, as well as some potential obstacles for retailers to watch out for.

What advantages does AI offer retailers for personalization?

AI provides an immense time savings in collecting all a retailer’s customer data, including preferences and attributes of each individual customer. Taking that volume of data and manually creating a personalized offer or assortment would be almost impossible.

However, AI allows retailers to take all those disparate datasets and pieces of information and then personalize something to each individual person in a manner a company couldn’t do with human employees alone. Maybe if an employee were to look at an individual person, they could create something similar to what AI can create, but not at scale. 

What challenges exist to a retailer that wants to use AI for personalization?

The biggest challenge is really around the data and the data availability. Retailers don't necessarily collect all the data they need, or they may have incomplete datasets. Some of the currently available AI algorithms are getting really good at making inferences on what customers want or could want, but data is still a major issue.

From a customer perspective, some shoppers are still on the fence in terms of how personalized they want retailers to make an experience, because they find it ‘creepy’ if the customer experience gets overly personalized for them. But I think consumers are generally becoming more used to AI as it's becoming more widely adopted across the board.

How can AI enhance the online customer experience?

AI provides retailers the ability to track and synthesize customer data to do things like create an online experience personalized for a customer. That could be a tailored landing page or a product that's exclusive to a customer group.

There does need to be some human interaction there and involvement in creating what the offers could be for the consumer. Where the algorithms kick in is matching offers with the right consumer traits to create a personalized experience. 

Certainly, there is a high degree of correlation between a personalized digital experience and everything from online conversion to engagement on an e-commerce site. The more personalized an online experience is, the more digital conversion and customer engagement they see.

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How can AI enhance the in-store customer experience?

There has been a lot of investment specifically around computer vision AI hardware and software to observe consumer behavior or in many cases, identify a consumer in store. 

This doesn’t trace back to an individual customer, but computer vision will identify a person and track them through the store. You could also assign a loyalty type of program to that person and offer them something personalized. It’s cameras that that track people, what a retailer does with that tracking information becomes AI. 

AI systems can even offer automated recommendations in terms of how you may want to think about laying out your stores or even what types of products consumers are engaging with. The cameras can reveal traffic patterns in stores, and AI solutions can proactively alert retailers where to position associates based on where customers will be located. 

How do you see AI evolving in the second half of 2024?

I think there will be a wider use of generative AI, internally for productivity or being more accurate about decision making. In addition, generative AI will have a big role to play on the customer side of the business.

Generative AI chatbots and things like that have been around for a long time. Those will continue to evolve and get a lot more sophisticated. We will see more automation around customer engagement, such as within a text to a customer’s phone or replies to inquiries about product returns.

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