How AI is Making E-Commerce Personalization Possible for Brands of Any Size

The ability to offer personalized shopping experiences has long been a cornerstone of digital marketing success. Brands often target specific segments within their ideal market demographics when executing digital ad buying and customer relationship activities like email and SMS marketing. So why don't brands also create segmented versions of their digital storefront(s)?

The practical challenges of achieving this (especially in an environment where most interactions are with first-time visitors) have historically been almost impossible for three reasons. First, logged-in shoppers only account for 1 percent to 2 percent of total traffic, making one-to-one personalization extremely challenging as you don’t really know who is shopping on your website. Second, existing personalization platforms are old, bulky and difficult to use. And third, having the systems and tools to deliver personalized experiences doesn't mean companies have the actual resources to create enough content for those experiences. 

First, let’s look at the technical hurdle: crafting personalized experiences for unidentified visitors requires a sophisticated understanding of anonymous user behavior and preferences, a task that traditional personalization platforms, with their bulky, monolithic architectures, have struggled to accomplish efficiently. On the other hand, there’s the operational challenge: even if the technology were capable, the sheer volume of content and experiences needed to personalize the shopping journey for diverse customer segments genuinely would overwhelm most digital teams. Creating 10, 20 or 30 different website versions (one for each segment) is far too labor-intensive. It's challenging enough for merchandisers to keep up with their default digital shopping experience!

Enter the advancements in artificial intelligence and machine learning. These technologies are transforming the landscape of digital commerce personalization by offering scalable, efficient solutions to both challenges. AI-driven platforms can now analyze vast datasets — e.g., content interactions, product catalog dynamics, order history, and customer engagement metrics — to infer preferences and predict behaviors of unidentified users. The practical application of personalization in 2024 also extends to new customer acquisition strategies. With the deprecation of third-party cookies and the increasing emphasis on privacy, digital marketers are finding innovative ways to segment and target potential customers. Advanced AI tools enable brands to leverage first-party data and contextual signals to build rich customer profiles, even without traditional identifiers. This approach respects user privacy and enhances the relevance and effectiveness of digital marketing campaigns, driving engagement and conversion through personalized messaging that resonates with each segment’s unique interests and needs.

This transformation equips digital teams with a powerful co-pilot in the form of AI, which can also suggest content ideas based on segments. The team can review, adjust or approve these suggestions, streamlining the personalization process while ensuring human oversight and creativity remain at the core. This collaborative approach between AI and digital teams facilitates the efficient and practical generation of segmented content at scale, marrying technology with human insight to create more personalized and engaging shopping experiences. 

As we navigate the complexities of e-commerce in 2024, personalization stands out as a critical, achievable goal for retail companies. In my opinion, if brands don’t have a practical personalization strategy over the next three years to five years, they'll be entirely left behind by their competitors. Personalization strategies that are thoughtfully implemented reflect a broader shift towards more intelligent, efficient and respectful consumer engagement. With the tools now available for almost instant personalization, companies face the challenge of leveraging these capabilities to create more meaningful, personalized shopping experiences that delight customers, drive loyalty, and set their brands apart in a crowded digital marketplace.

Brian Anderson is the founder CEO of Nacelle, a commerce platform.