Talk Adobe to Me | Visitors vs. People vs. Profiles – Oh My!

This is the second post in “Talk Adobe to Me,” our continuing series where we explore interesting areas within the Adobe Experience Platform. In this article, we review the differences between “visitors,” “people,” and “profiles,” how these are counted, and the backend data that’s stitched to identify them.

Adobe identity management across tools

Identity management across Adobe tools is critical, but it can be confusing, especially if you share audiences across tools. This post breaks down identity management across the Adobe tech stack to help you understand how to take advantage of the most appropriate identity tool for your use case.

Why are identity management strategies different across Adobe tools?

Adobe Analytics is a dedicated digital analytics analysis platform designed to track website user behavior. It uses “visitors,” and it isn’t designed to integrate data across datasets, so it doesn’t need a cross-channel identifier.

On the other hand, Customer Journey Analytics is based on the same underlying technology as Adobe Analytics but is designed to be used with any time series dataset, of which website user behavior is but one example. Call center data, retail data, and other data within AEP can be pulled in with your data in CJA: It’s much better for integrating multiple datasets. To do that integration, however, you must come up with an identifier common across channels. By default, CJA uses “people” to identify users that may be more than just “visitors,” as we’ll discuss below.

Real-time CDP is not an analysis tool but a data platform for segmentation and activation. As such, its underlying design requirements are different. It works off of profile snippets, so every bit of data that comes into the CDP becomes a snippet with a “profile.” You can use multiple identifiers (e.g., ECID or HEID and more), and when two or more identifiers show up together, they’re automatically combined into a single identity.

Audiences can be shared between tools (with caveats), but segment sizes will vary for segments shared between the tools. This is expected given the different identity resolution methods but may throw some new users off at first.

Visitors in Adobe Analytics

Adobe Analytics uses the term “visitor” to describe users on their devices. These are first-party cookies on people’s machines, most often Experience Cloud IDs (ECID), formerly called Marketing Cloud IDs (MCID). Visitors suffer from all the cookie deletion technology that targets modern browsers, so they expire faster than they used to.

Visitor data is never automatically stitched with other IDs, although there are features in Adobe Analytics that allow some cross-device linking. There are edge cases where visitors are not simply ECIDs. There are redundant IDs in place as fallbacks to the ECID when it can’t be created, e.g., user agent + IP address.

Identity Management in Adobe Analytics counts visitors, usually from ECID.

People in CJA

Customer Journey Analytics uses the default term “people” to count a dimensional value of your choice within the dataset you have configured. This can be the ECID for AA data, but many CJA users leverage the Cross Channel Analytics (CCA) capability of the tool to stitch AA to other data sources like hashed email IDs (HEID) and one or multiple ECID to identify a “person” (see how a “person” is more than a “visitor”?). CJA replays data to find opportunities for stitching, and it’s highly configurable and unlikely to be configured exactly as AA.

Identity management in Customer Journey Analytics (CJA) counts "people" which can include both hashed email and ECID within stitched identities.

It’s important to note, though, that time is important in the persistence of “people” metrics. The replay feature, Cross Channel Analytics (CCA), only looks back one week. That means that if we don’t capture HEID within a week of a new ECID, people metrics from the previous weeks will not be rewritten, and one visitor will be identified as two different people.

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Profiles in RT-CDP

Real-time CDP makes profiles based on connected profile snippets (or rows of data grouped together by any number of identifiers within the data). Profile snippets are joined when two or more identities exist in a row of any snippet. These are joined in real-time when data is loaded into AEP, and profiles are continually merging into ever-larger groupings of snippets. There are no one-week replay lookbacks or forward-looking only time dependencies.

Adobe Real-time CDP manages identities by using "profiles." You can use multiple identifiers (e.g., ECID or HEID and more), and when two or more identifiers show up together, they’re automatically combined into a single identity.

Because RT-CDP identities share many-to-many relationships, it produces a wide net when joining snippets (which might include ECID, HEID, UserID, and more). It can stitch large quantities of data together.

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A note on segment size within RT-CDP: Segments contain profiles, and within those profiles, there can be many identifiers. Profiles are very configurable and may not even contain ECIDs, but in the real world of Adobe clients, they are almost certainly going to contain many ECIDs for any given profile. Therefore, RT-CDP segments shared with AA will have very different segment sizes.

Sharing Audiences

You can share audiences between the tools, but not in all directions. If you took a CJA filter (a segment of people) and shared that with CDP, you could get a wider audience made of fewer profiles (based on the increased connections that the CDP has made). From there, you can share it with Adobe Analytics, which converts it back into ECID. RT-CDP, an activation powerhouse, can also feed other tools besides Adobe Analytics, like Adobe Target.

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Getting okay with the identity management journey across tools

If the numbers don’t equal each other even though you’re sharing the same data across platforms, don’t fret. Moving from device counts to profiles to sharing audiences is a valuable process. When you understand that each tool is intended for different purposes, each audience you evaluate within each tool can inform important business needs, depending on your use case.

Your use case is really the key to which tool you select, and each tool uses specific identity management according to its functionality. AA’s visitor ID service has been an industry-leading digital analytics identity resolution solution for a long time, but it’s always been difficult to integrate outside data into AA. CJA offers AEP’s features for integrating additional data sources, but its accuracy depends on the skill of its analysts and architects. The CDP has the most flexible identity resolution solution, but it’s not an analytics tool.

Pro-tip if these numbers are completely wacky: Check for bots.

Key Takeaways

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