By requiring logins for purchases, ecommerce platforms gain access to some of the most valuable first-party data in the ecosystem. Even after a single purchase, ecommerce platforms know a lot about an individual, from where they live to what kinds of products they prefer to what brands they prefer and general inferences on the socioeconomics of households and individuals. This knowledge enables a great deal of effective loyalty and retention marketing, particularly via email and direct mail. But as it relates to a person’s larger online journey—the more than 24 hours a week that the average American spends across various connected devices, a number that more than doubles when you include connected TVs—most ecommerce platforms are failing to connect the dots.

The challenge that ecommerce platforms face in this regard is that many users stay anonymous to them as they browse on platforms while logged out. Without the ability to connect these users’ unknown profiles to their resolved and unresolved IDs, ecommerce platforms’ attribution modelling and recommendation tools are severely limited in their effectiveness.

Ecommerce platforms today need to get a better handle on the identity of their users across devices and be able to layer on intelligence about activities that occur when people are not logged into the platforms themselves. By doing so, ecommerce platforms will see drastic improvements across the following three critical functions.

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Multi-Touch Attribution

When a user logs onto an ecommerce platform and makes a purchase, that sale has real value to the brand. But if the ecommerce brand doesn’t understand how and why that user came to make that purchase—where the user encountered ads and which ones seemingly drove the user closely to final purchase—then the ability of the e-commerce platform to replicate those sales is severely diminished.

One of the biggest challenges ecommerce platforms face in proper multi-touch attribution is the fact that a single user possesses many IDs—across browsers and devices, some with and some without any historical data connected to them. To truly understand the customer path to purchase, ecommerce platforms must be able to link the many user IDs a single customer generates from their activity on mobile web, in-app, desktop, connected TVs and other devices.

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Audience Profiling

Beyond attribution, gaining a better cross-device understanding of customers will enable ecommerce platforms to forge deeper relationships with those individuals. When ecommerce platforms can tie multiple IDs to a single user, their view of users shifts dramatically. Without a cross-device understanding, an individual essentially fractures into multiple users. On one ID, an e-commerce platform might see a high-income person in the 20-29 age range. On another ID, the platform might see a man living in Amsterdam. On yet another, no information is available. Yet, all three represent a single individual. If an e-commerce platform can reconcile that identity and understand it is looking at the same high-income young man in Amsterdam across all three IDs, the user journey for that person can become infinitely more tailored—and ultimately beneficial to the retailer.

In addition, ecommerce platforms need to be able to match profiles of logged-in users with those users’ non-logged in behavior. Without this capability, the platforms miss out on the ability to properly retarget to users on sites and platforms other than their own. It also severely limits their ability to conduct proper A/B testing and fully leverage recommendation tools.

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Audience Amplification for Recommendations

Going a step beyond audience profiling, ecommerce platforms should seek to target known users with recommended products—even when those users are not logged into their platforms. If the ecommerce brand is able to resolve the identity of individuals across platforms, whether or not they are not logged, they can tailor recommendations to the person’s previous searches or on-platform browsing behaviors derived from their deterministic, logged-in profiles. These recommendations are a key requirement for effectively driving repeat purchases.

Although ecommerce platforms retain a wealth of first-party data on their customers, they must go beyond that knowledge to acquire a full-cross device understanding of those valued individuals. Only in doing so can they hope to reap the benefits of effective multi-touch attribution, as well as comprehensive retargeting and product recommendations across the entire customer journey.

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