How Brands Can Use Machine Learning to Complement Retail Media Network Strategies

Stephen Rivera, Senior Director of Customer Success, Rokt,

Ecommerce crossed $ 1 trillion dollars for the first time in 2022 in the US alone, marking a major milestone for retailers and their online customers. As consumer anxiety, inventory challenges, and the third-party cookie debate continues, monetizing the transaction moment represents an accelerated path to new revenue growth in 2023 and a significant opportunity to drive consumer loyalty through the post purchase experience.

While Retail Media Networks (RMNs) added $50 billion to retailers’ topline last year, that revenue was primarily driven across the pre-checkout shopper journey. RMN strategies drive revenue by helping brands influence purchasing behavior before checkout and are built to allow endemic brands to influence what’s being added to carts. However, once the customer reaches the payments page, a retail media network’s influence stops. As a result, ecommerce retailers are potentially leaving millions of dollars in untapped revenue on the table.

Retailers can monetize the customer journey through post-purchase by deploying Advanced Machine Learning (AML) technology on the payments and order confirmation pages to deliver highly relevant, non-endemic offers that are tailored to each individual customer. Extending relevancy and customer value to in-transaction and post-transaction inventory can deliver a significant uplift in the value generated with each transaction.

Here are four ways that AML can enable ecommerce retailers to maximize untapped revenue in 2023:

Leveraging first-party customer data to reveal the next best action: With the tightening of data privacy laws and third-party cookies on their way out, the ability to harness first-party data to optimize, personalize, and monetize the customer experience is essential. AML enables brands to leverage their first-party data to deliver 1:1 customer relevancy – without anyone needing to share their first-party data with anyone else. This enables retailers to present the right non-endemic offer, to the right customer, at the right moment and unlock additional profit with every transaction.
Unlocking unique, onsite inventory on the confirmation page: Historically, retailers have overlooked the order confirmation page as a potential revenue source. By leveraging AML to deliver non-endemic offers to customers after checkout, retailers are able to unlock powerful new onsite inventory and generate incremental spend from brands. The result is a new profit channel that complements their retail media program – without any upfront investment or disruption to the customer experience.
Relevancy is key to increasing the Lifetime Value of a Customer: Online shoppers are often overwhelmed by the number of competing offers that ecommerce retailers display onsite, resulting in a disjointed customer experience and negative impact to purchase rate. AML combats this “paradox of choice” by crunching the numbers to show only the most relevant content to each customer, creating a seamless, rewarding customer experience that fosters efficient decision making and a reduction in abandonment rates. Ultimately, optimizing for relevancy through post-purchase is key to unlocking incremental revenue and increasing the Lifetime Value (LTV) of the consumer.
Delivering exclusive, non-endemic offers: Retailers can complement their retail media programs by leveraging AML to deliver premium, non-endemic offers during the transaction moment – specifically in-cart and on the confirmation page. This enables businesses to unlock the value in their first-party data to deliver native, relevant experiences during and post transaction and scale the take-rate of non-endemic offers..

Because Retail Media Networks are primarily focused on pre-purchase touchpoints, there is an untapped opportunity to optimize and monetize the customer experience through post-purchase. Advanced machine learning enables retailers to take advantage of this opportunity and unlock more seamless, personalized and profitable experiences across the full customer transaction journey.

Stephen Rivera is a Senior Director of Customer Success at Rokt, where he leads Rokt’s retail and travel verticals. Stephen has helped propel Rokt’s Customer Success organization forward over the last 5 years, building key relationships with brands such as Kohl’s, Wayfair, and JCPenney. He graduated from New York University in 2014 with a degree in Hotel & Tourism Management & Marketing.