How machine learning can create a more relevant, profitable e-commerce experience

In today's fast-paced and highly competitive e-commerce landscape, it's not enough to simply personalize the shopping experience for customers. Instead, it's essential to focus on relevancy to truly stand out and meet customer expectations. Relevancy, which goes beyond personalization by adding context and predictive analytics, is the key to creating a truly customer-centric e-commerce shopping experience. Despite the clear value of relevance, most e-commerce brands miss the mark. By rethinking the customer journey and delivering relevant experiences tailored to each individual customer, e-commerce brands can create new profit streams that improve their bottom line without hurting their core business. With U.S. e-commerce sales expected to reach around 23.6% of total retail sales by 2025, failing to align with customer expectations and purchasing behavior is more than just a misstep—it can be a threat to the brand’s bottom line. Consider that shoppers today are constantly bombarded with irrelevant ads, offers and messages throughout the entire e-commerce journey, and as a result have grown accustomed to tuning out content. In order to recapture a consumer’s attention and make a message resonate with shoppers who are primed to ignore it, brands must prioritize relevancy for customers on a one-to-one basis. With machine learning, e-commerce brands can harness their first-party data to identify and present the right ad message or offer to the right customer at the right time, ultimately delivering more value to each customer across a more seamless shopping experience. Leveraging first party data for incremental profit It’s been well-reported that third-party cookies will soon be a thing of the past. E-commerce brands are already shifting strategies to rely more heavily on the first-party data that they’ve been collecting all along. By using the data available to them, brands will be able to accurately optimize the shopping experience, delight their customers and create better business outcomes. In addition to enhancing the customer experience, combining first party data with advanced machine learning can also help brands monetize their existing site inventory, especially during the transaction moment, with upsells, cross-sells and payment offers deployed in cart, on the payment page and order confirmation page. For example, traditionally paying fees for financial services has always been seen as a necessary expense for most e-commerce businesses. Rokt’s Payments Marketplace allows e-commerce brands to generate revenue on the payments page, transforming the page from a cost center to a profit center. It converts static, fixed-display inventory into a flexible experience and utilizes one-to-one targeting that is tailored to each individual based on the payment message they’re most likely to be interested in. It’s a win-win for the payment provider, the e-commerce brand and the end customer. The e-commerce purchase flow is a frequently untapped opportunity for brands to deliver added value to customers, but by unlocking the potential of that flow, businesses can double the profitability of each transaction. During this phase, brands have a distinct advantage of customer attention and data. Customers are highly focused on completing their purchase, enabling businesses to gather valuable information about their behavior and preferences. Tailoring upsell, payment and cross-sell offers across the transaction journey not only positively impacts profitability, but also significantly increases customer stickiness and retention. By leveraging first-party data to deliver relevant offers to customers at a critical moment in the buying journey—when the credit card is out—e-commerce brands can tap into new opportunities to generate value. The paradox of choice Once a brand has identified its shoppers, not only does it have to provide the most relevant offers to them but also understand that sometimes more is just too much—especially in the e-commerce space. An abundance of options requires more effort to choose and can leave consumers in a state of “analysis paralysis.” By overloading the customer with messages and offers, e-commerce sites create disjointed and confusing customer experiences. Sometimes the most powerful thing is to show nothing, because irrelevant messages tend to distract customers and lead to cart abandonment. Rather than overwhelming customers with randomly selected offers, products and services, e-commerce brands can overcome the paradox of choice by focusing on relevancy. By allowing advanced machine learning technology to intelligently gather data and manage objectives, brands can ensure that customers are only exposed to messages that are most relevant to them, when they are most likely to convert. E-commerce brands that are truly focused on the customer experience will not simply present their customers with standard ad messages or irrelevant products and services, but will personalize these messages on an individual basis, resulting in higher engagement, and deeper customer satisfaction and loyalty. About Rokt Rokt is the global leader in e-commerce, enabling companies to unlock value by making each transaction relevant at the moment that matters most—when customers are buying.

How machine learning can create a more relevant, profitable e-commerce experience

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