There’s a lot to learn about the Adobe Experience Platform. This post gives you some easy-to-understand basics to help ground your team and begin to inform your migration to AEP.
The Adobe Experience Platform provides integrated functionality for businesses wishing to provide optimal, data-informed customer experience across channels. It’s an open, extensible system that works in real-time to build robust customer profiles that a business can then act on.
It’s also an enterprise tool being sold to enterprises using the appropriately polished enterprise jargon, which can be confusing. We’re working to understand the platform in simpler terms (see my AEP cheat sheet here), which is also the aim of this post.
AEP is an evolution within the Adobe brand.
In the beginning, or, well, recently, Adobe Analytics is what analysts would normally use to manage a website’s data. We’d use Adobe analytics to tag websites, and those tags would then go into Adobe Analytics and become part of the Experience Cloud.
Adobe Analytics lets you visualize data in a couple of ways: legacy reporting and a tool called Analytics Workspace. Workspace is the tool that Adobe has pulled out of Adobe Analytics and into AEP, and now they’re calling it “Customer Journey Analytics.” It’s the exact same feature set, and it looks the same except that it’s an updated version. Notably, now CJA can only report on data from the AEP datalake. It can’t pull data from anywhere else, so it’s solidly an AEP tool.
AEP isn’t just a data lake.
AEP is not just a data lake or a database (or even a database inside of a data lake, which might be a more accurate description of the data storage component of AEP). Perhaps the defiance of the platform’s structure to fit neatly into a term we’re familiar with is one reason Adobe calls it, instead, a “platform.”
However, to return to the original point, AEP is open-ended and it’s a data lake plus a lot of services, too. There are different technologies for doing the data collection and manipulating the data, but if you think at a high level about what any of these technologies do, all of them put data into the data lake and/or take data out of the data lake.
The different technologies work together but offer users options depending on what they need to do. The data lake part of AEP is like a (data) bus. It carries a ton of people (data), but it’s not a speedy trip. The customer profile service part of AEP is like a cargo helicopter. It carries maybe a dozen people, it’s fast, and it’s built for fast queries. The edge service is a fighter jet. It carries a few people and is lightning fast.
While all the technology within AEP all touches the data lake, it’s important to understand that when you buy AEP, you’re not buying the data lake—you’re buying the tools that help you move and manage the data.
AEP helps you do stuff.
Tools are handy technologies that help you do stuff. In AEP, some tools are labeled as “Applications” and some are labeled as “Features,” and few are labeled as “Tools.” This is confusing, but the thing you need to know about AEP is that it has tools that help you do things. Here are the five primary tools that help you do things in AEP. Again, all these tools either push data into or pull data out of the AEP data lake.
- Customer Journey Analytics– Like we mentioned above, CJA is like Analysis Workspace, except it gets data from the AEP data lake instead of getting it just from Adobe Analytics. Unless you live and breathe SQL, this is a fundamental product that you’ll need for analysis if you’re using AEP.
- Data Science Workspace– This is a data scientist’s playground where you can run code like R, Python, and Scala to do super complicated stuff that you wouldn’t otherwise be able to do in Analysis Workspace (or CJA).
- Journey Optimizer- This tool is the combination between Journey Orchestration and Offer Decisioning.
- Journey Orchestration determines which point in the purchase lifecycle someone is in and provides next steps. Offer Decisioning is more about displaying a message to get someone to take an action, while Journey Orchestration is more about contextualizing where they are in a process to take them where they SHOULD be. This is an Application but isn’t a SKU you can buy since it rolls up into Journey Optimizer.
- Offer Decisioning is where you play with creative assets to build dynamic marketing offers. For instance, you would build an ad in Offer Decisioning, and then Journey Optimizer would automatically know what to display to the user. To be more specific, maybe you have a $10 off and a 5% off coupon. You would create both offers and then use Customer Profiles to drive what offer to send to the user. Like Journey Orchestration, this is an Application but isn’t a SKU you can buy since it rolls up into Journey Optimizer.
4. Real-Time CDP (RTCDP): The platform that creates segments from profiles and other data. You can set up stuff like segments to send emails to people in certain phases and tie it into other ad tech. There’s also a B2B and a B2C version of this. The B2B version adds account-based functionality and has built-in connectors to platforms that let you pull in professional industry data (like account status and funnel stage). The B2C version focuses more on the checkout funnel, cart abandonment, etc. The following are tools that inform the RTCDP:
- Identity Graph is a visual representation of how different datasets from different sources connect (like offline, CRM, site analytics, etc). It looks like a prettier database mapping table. It has the fun name because there’s also an unspoken implication that the data is collected and retrieved in real-time. For instance, if Adobe Analytics has your ECID and Email and your email CRM has email data – you would use the email as the primary key (or “Identity Key”). Then you might also have ECID in Salesforce for something – you would also use ECID as a primary key. Suddenly, all those systems can connect! Yay! Alert: this is not a product you can buy. It informs the RTCDP.
- Real-Time Customer Profiles help you see a customer’s complete data profile on-demand… like, all the stuff they’ve done. Say you’ve passed a bunch of data into AEP and built that fancy Identity Graph. AEP then creates the customer profile (and is accessible via each tool except CJA). RT Customer Profile takes that information and builds profiles. Usually, it’s viewed in aggregate, but you can definitely use it on an individual basis. This sequence of words makes sense and kind of feels like more of a marketing term to describe something you can SEE without going into what you should DO with the data. You can’t buy this: It rolls up into RTCDP.
5. Intelligent Services: This tool is made of fancy algorithms that do stuff like assign scores to determine the likelihood a customer will do something you want them to do on your website (propensity models). It can also automatically build attribution models. The tool itself doesn’t DO stuff with the website. It won’t dynamically display an offer. You would use this tool alongside another tool (like Journey Optimizer) to act on those segments and scores. So… Skynet?
Other differentiating features of AEP.
Functionality also contributes to the brand evolution that is AEP. Here are six new things you can do with AEP.
- Build Customer Profiles. Data enrichment helps you build out deeper customer profiles. This is adding data to data. You can think about this how we think about Classifications in Adobe Analytics (SAINT or auto). On the website, I might know someone’s customer ID but I want to add some more context to it that I have from some other place. So, online, I know it’s customer x who just made a purchase, but offline, I know that customer x just went to the store in-person because they used a loyalty card. This process ties the data together from those two sources so you don’t have to go to two different places to see it. This can be done with Launch Server-Side, among other methods. You can take advantage of customer profiles with Offer Decisioning (above).
- Enable Identify Graphs. AEP uses identity graphs to build real-time customer profiles (see both of these terms above). The identity graph shows you what constructs the aforementioned customer profiles.
- Utilize Edge compute services. “We can do real-time personalization because we’re getting data from the edge.” A place where you can retrieve and use data really really fast (like real-time). Previously, it could have taken a while to retrieve data from some source because some server would have to dig it up. That would impact site performance. This basically eliminates the performance hit.
- Enable Data Governance. This is basically AEP’s Data Usage Labeling and Enforcement (DULE). Any field in XDM can have its own policy like “This PII field can’t be used for advertising”. That dictates what information is passed into what platform and how it’s used. Basically this helps you stay legally compliant – but it also addresses stuff like admin permissions, data integrity, etc.
- AEP is API-first. This means you can build stuff like apps using data from the data lake. An app might be something like a BI tool (like Tableau) or it could be something neat like an in-store visualization built by your in-house development team. Adobe’s basically saying they’re making it easier to build stuff outside of Adobe with your data stored inside Adobe.
- Enable Composable Services “Innovate with open and composable components.” This just means AEP has an API. They call it this because you can “compose” products by leveraging the API. This just means it’s easier to build third party apps on top of your data in the data lake. Also see: API-First
Adobe Experience Platform does what now?
Bottom line: the Adobe Experience Platform seeks to both build successful customer experiences and optimize customer experiences in real time by capturing all the data a customer provides, then processing and centralizing that data within the moment to create actionable customer profiles. An enterprise can use these profiles to satisfy customers’ real-time needs, to surface predictive insights, and to deliver the best experience at the right time.
Stay tuned for more posts about the Adobe Experience Platform, including posts about when and how to migrate to AEP and use cases for each of the platforms’ tools. Make sure your program is as mature as possible and ready to take advantage of all these changes.
Peruse our archives for more posts about analytics, data engineering, and Adobe.
.png)