Home PublicationsData Innovators 5 Q’s for Bill Barton, Chief Product and Engineering Officer of Rokt

5 Q’s for Bill Barton, Chief Product and Engineering Officer of Rokt

by Becca Trate

The Center for Data Innovation spoke with Bill Barton, Chief Product and Engineering Officer at Rokt. Rokt uses data personalization and machine learning to curate ads and offers during e-commerce transactions. 

Becca Trate: What is data personalization, and what challenges does Rokt solve with it?

Bill Barton: Data personalization is how retailers leverage the wealth of knowledge available to them about their customers, such as purchase history, gender, location, age, and other factors, in order to customize a transaction. Rokt’s solutions go beyond personalization to deliver relevancy.

That means that while one company might use its customer data to provide a personalized experience, such as greeting a customer by name when they purchase concert tickets on a site they’ve used in the past, Rokt uses machine learning to create a truly relevant experience, allowing retailers to present the kinds of additional messages that are highly likely to appeal to the customer as they transact online. Providing relevancy might mean presenting that customer who’s just bought concert tickets with an offer for discounted parking near the venue or an offer to pay for those tickets in installments through a particular payment provider.

Consumers are also often bombarded by multiple messages during the shopping journey, which can leave them in a state of analysis paralysis. The best and most effective way to engage with the shopper is to limit each individual to receiving three of the most relevant offers.

Rokt also creates an avenue for brands looking to acquire new customers and diversify their marketing portfolio by bringing a company’s relevant content to the right customers throughout their shopping journey. Rokt’s technology paints a full picture of each customer, humanizing their online presence to provide them with messages, offers and experiences that they are most likely to actually want to see, not just those that a brand thinks they ought to see. Rokt’s data capabilities ensure ecommerce businesses can present the optimal marketing offer to each individual customer in the way that is likely to generate the highest revenue and maximize conversion and loyalty.

Trate: How can relevancy be used to improve the customer experience?

Barton: Most shoppers have encountered a complicated checkout experience at some point and understand the feeling of being bombarded with multiple ads, upsells, and marketing messages they’re not interested in, not to mention recurring offers they’ve already rejected time and again. This kind of friction irritates consumers and makes them want to steer clear of certain sites. But retailers that avoid these tactics and use technology to ensure every single interaction is relevant and seamless can improve the overall experience and deepen their relationships with current and potential customers, ultimately driving higher conversion, loyalty, and lifetime value.

Rokt ensures relevancy by leveraging sophisticated AI and machine learning, which will power more than 2.5 billion transactions in 2023, to present ecommerce shoppers with only the top messages that are most likely to resonate with and appeal to them in that moment, making the online experience more human and relevant and ensuring shoppers aren’t overwhelmed by too many offers. Sometimes, Rokt’s AI determines the best course of action is to show nothing at all. The technology enables retailers to better curate the shopping journey for individual customers, as well as reach new customers.

Trate: What is the “transaction moment,” and how does AI optimize individual offerings?

Barton: The transaction moment is the point in the ecommerce journey when a shopper is already making a purchase and is therefore most receptive to, and most likely to engage with, relevant additional offers. Customers who are completing a purchase typically experience positive feelings about their shopping journey and it’s the moment when retailers have a customer’s undivided attention, so they’re primed to further engage with relevant offers.

Retailers can maximize the value of each transaction moment by cross-selling and upselling complementary products and services on transaction and confirmation pages, presenting relevant messages that have a high likelihood of leading to an additional purchase, a loyalty program signup, an app download, a payment choice or another desired action.

To zero in on the kinds of offers that an individual shopper will find relevant and compelling, machine learning is applied to consumer transactions and contextual data in real time. Rokt technology provides retailers with the agility they need to present not only the offer expected to realize the highest value, based on value of each offer and customer likelihood to engage, but also to present it in the optimal way, rationalizing every element, from imagery to headline to pricing for each transaction

Trate: What data sources does Rokt use to provide relevancy?

Barton: Rokt applies machine learning to customer demographic, contextual and behavioral data to deliver relevancy, while fully protecting consumer and retailer privacy and security. This may include ecommerce transaction data contained within the retailer’s ecosystem, like a customer’s name, zip code and cart value, as well as customer profile data, like whether the person is a first-time shopper or a member of the retailer’s loyalty program.

A customer’s behavior in previous visits, derived data, is used to ensure relevant creative rotation, so customers who never engage with a certain upsell offer don’t see it again and again. For example, a customer who is presented with an offer to download an app but doesn’t click the offer won’t be continually presented with that message because Rokt technology will learn from the customer’s action, or lack thereof, that the offer isn’t currently relevant to that person.

The optimizations any particular retailer chooses to deliver are based on its customers’ actions, transaction information and preferences without ever passing the data to the other side of the marketplace, with Rokt as the secure, trusted intermediary connecting two businesses. Each retailer retains complete control of the data it chooses to use to achieve its business goals.

Trate: What is the future for customer-first data personalization and relevancy?

Barton: Customer acquisition costs are on the rise, ecommerce margins are under pressure and businesses are looking for incremental value from every customer across each transaction. Therefore, we expect to see more companies double down on using their first-party data to maximize their relationships with their existing customers. We’ll see retailers increasingly leverage analytics and machine-learning technology to enrich the shopping and checkout experience by moving beyond mere personalization, to true relevancy, simplify the shopping and checkout experience, and diversify their inventory and product assortments.

We’ll see retailers increasingly leverage analytics and machine-learning technology to enrich the shopping and checkout experience by moving beyond mere personalization to true relevancy.

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