Ori Bauer, CEO of Dynamic Yield by Mastercard
The emergence of generative AI will be a game-changer in managing customer relationships.
In a recent conversation with Chain Store Age, Ori Bauer, CEO of Dynamic Yield by Mastercard, discussed his views on how leading edge artificial intelligence (AI) solutions such as generative AI are enabling the delivery of truly individualized customer service, at scale.
Will generative AI technology help retailers deliver a more personalized customer experience?
We see AI in general as allowing retailers to create more consumer-centric commerce. Generative AI enables a more natural and seamless engagement. For example, you can create a chatbot that customers can talk to in natural language to receive help through the shopping experience.
Imagine visiting an online retailer, after getting an invitation to a wedding with ‘beach formal’ dress. You probably have no clue what beach format means. In the ‘real world,’ you would go to an assistant in the store and ask what you should wear. Instead, you can tell the chatbot you’re invited to a beach wedding with a formal dress code, and it will retrieve relevant options for you.
[Read more: Mastercard applies generative AI to customer search requests]
However, retailers need to be smart about the way they implement generative AI. If you just let generative AI, or AI in general, run the show completely it may come up with the wrong answers or with things that are not what you meant it to do.
Mastercard believes in utilizing a combination of AI technologies to support customer experience but leaving the control in the marketer’s hand. Let the marketer define how a shopping chatbot would behave, set boundaries such as it can only offer products that are available in the catalog.
How is the role of algorithms changing in delivering omnichannel customer experience?
When a retailer is trying to recommend relevant products to a consumer, then there could be relevant algorithms depending on the stage in the purchase. If a customer decided to share, their location then an algorithm might serve up popular products that are relevant for that particular location. As the purchase journey progresses, other algorithms may become more relevant.
Sometimes, the marketing department might have very specific requirements or intentions, such as increasing customer awareness of a new line of clothes. Even though the default algorithm may not decide to promote those items, human control of algorithms will enable marketers to achieves the desired best results by ensuring customers see them, and we really see the ascension of humans and AI working together to achieve best results with algorithms.
Does generative AI enable retailers to be empathetic with consumers at scale?
This may sound counterintuitive, but we believe that there will be a shift towards empathetic experiences. Traditionally, retailers focused on transaction and engagement, trying to get customers to click on something or to convert and buy something.
Now, retailers can use AI to be empathetic. For example, if a shopper came to an e-commerce site through an online search for a specific item, maybe the right approach is not to bother them too much and just get them to the shopping cart so they can purchase what they want and maybe offer a few more things.
Or if a customer picks up a certain pair of jeans, a generative AI shopping assistant could be able to bring them a matching pair of shoes, which helps the shopper reach their goals faster.