Informatica Buys AllSight and What It Means for the CDP Industry

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Informatica announced last week that has purchased AllSight, a Toronto-based Customer Data Platorm vendor. This is interesting on several levels:

  • A CDP vendor is being bought by an established enterprise data management firm. This is a normal event in the development of a software category: products are developed as single-purpose “point solutions” and then, after the category is validated and requirements are standardized, the capability is assimilated into larger suites by acquisition (usually) or internal development. The most surprising thing about the CDP industry so far has been that this hasn’t happened very often.  There have been some deals but the two biggest each came with an asterisk: Salesforce bought Datorama but positions it primary for campaign measurement and Arm Ltd., which purchased Treasure Data, is not a typical enterprise software vendor. By contrast, Informatica is very much a leader in enterprise data management, with a major presence in integration, Master Data Management (MDM), governance, and security. The purchase confirms what we already knew: business managers recognize they need unified customer data and enterprise software vendors will offer them solutions.


  • It illustrates the difference between MDM and CDP. This is one of those questions we still get fairly often. Informatica lays out the contrast quite nicely: they characterize MDM as limited to highly governed, structured data that delivers the “best version of the truth” about master objects (customers, products, supplier, etc.), while AllSight stores transaction and interactions in addition to the master objects, supports unstructured as well as structured inputs, and allows multiple data views and matching options. AllSight is an exceptionally powerful CDP, with features including machine learning-based identity matching, natural language-based information extraction from unstructured data, a graph data store for complex relationships among objects, ability to create derived variables, and high scalability. These are not found in all CDPs, which is probably one reason Informatica selected AllSight in particular. But all CDPs share the core CDP capability of storing all types of customer information without losing any of the details, which is beyond the scope of MDM.

  • It confirms the importance of a persistent data store. This, like storing all information, is part of the core CDP definition. Some enterprise software vendors still argue it’s enough to connect personal identifiers in different source systems and then to pull data from those systems as needed. That is how Informatica has been doing things, apparently. But they’ve now described a progression from “distributed” customer views (disconnected systems) to “federated” views (data remains in transactional systems) to “consolidated” views (data is stored centrally and synchronized with source systems). Reasons they cite for doing this include scalability and real time performance; I’ll add greater consistency, easier control, visibility, and ensured access to historical data.
  • It shows use of CDP beyond marketing. Informatica sells primarily to IT staff, which in turn supports all corporate departments, not just marketing. In their briefing on the topic, Informatica made clear that a major reason for buying AllSight is to access the funds controlled by marketers and analytics teams. But they also argued that AllSight will give them more to sell to IT staff, which will use it to better manage large volumes of unstructured data, prepare analytical data sets, add insights based on artificial intelligence and machine learning, and support specific applications such as risk and compliance. Growth to support new use cases and departments is another natural business development for any category.


  • It gives a literal example of “CDP Inside”. This is my shorthand for recognizing that CDP functions are increasingly available within larger systems, in addition to being stand-alone products. This is arguably the most important trend in today’s CDP industry.  Let’s explore it in more depth.  

“CDP Inside” matters because it’s inevitable as the market matures. So far, the main reaction, at least among vendors and analysts, has been to debate which products are properly labeled as CDP systems. Not surprisingly, each CDP vendor wants a definition that matches their own configuration. But those configuration range from products that only build a unified, sharable customer database to products that build the database, analyze its contents, and use it to create personalized marketing messages. The resulting definitions are thus incompatible.  That’s a bit of a problem.

The bigger issue is that even the broadest definition excludes other products that include CDP capabilities. Informatica is good example: AllSight didn’t stop being a CDP just because Informatica bought it, but it’s hard to argue that Informatica should now call itself a CDP system as a result. The same question will appear when Salesforce, Oracle, and Adobe finally deliver proper CDP capabilities – which will doubtless happen, sooner or later. Rather than calling every system with CDP capabilities a CDP, I think it’s more useful to define core CDP capabilities and then to judge every system’s CDP features against that list. This, again, is an entirely normal market development: companies choose all the time between buying “best of breed” point solutions and buying larger suites that include similar functions. Companies with the most demanding requirements and most sophisticated users often find themselves purchasing “best of breed” products while those with simpler needs often find the product embedded in a suite is good enough.

CDPs are slightly different from other suite components because many suites are connected internally but isolated from external systems.  CDPs are by definition required to connect with external systems.  This means a suite with CDP functions wouldn’t qualify as having a “CDP inside” if those functions couldn’t also connect with external data sources, analytical, decision, and delivery systems. But there’s no technical reason that suite vendors can’t provide systems capable of such connections and their importance is probably well enough understood that most suites will provide them.  Conversely, suite vendors are under increasing pressure to open their systems to integration with external products.  This may make it easier for “best of breed” CDPs to survive than it has been for other “best of breed” products in the past.

Of course, even accepting the notion of “CDP inside” doesn’t resolve the debate over what scope of functions should be included on the CDP requirements list. I lean to a narrower definition, limited largely to building the unified, sharable database, on the theory that analytics, decisions, and distribution systems can be purchased separately. This strikes me as a reasonable practical definition for a software category.  In concrete terms, it means that buyers face a separate “suite vs best of breed” decision for each of those components. The counter argument is that some analytics, decision, and distribution capabilities are substantially more effective when they are directly integrated with the unified customer database, so they should be considered part of the core CDP requirements. I suppose the easiest solution is to include the broader requirements on any list and let each buyer decide for herself which ones matter.



The more inclusive approach is in fact what we’re currently taking at the CDP Institute, where I’ve been distinguishing between data, analytical, and personalization CDPs. This seems to reduce confusion, so I’m reluctant to abandon it. Our current projects include improved evaluation criteria for each of those functions, which will make it easier for buyers to determine which vendors fit into each category or, more precisely, how well vendors meet the requirements for each category. The good news is that the same evaluation criteria can be applied to the CDP components of broader products with a “CDP inside”. So the work will help marketers to make sound choices across all their options regardless of how we define a CDP.  And making good choices, not defining software categories, is ultimately what matters.

2 COMMENTS

  1. David, this article was extremely informative and personally enlightening because, as an MDM practitioner, I understand and evangelize the profound significance of accurate & consolidated customer data to an organization, but was somewhat ignorant of the CDP segment that Allsight plays in. This article lays out a clear perspective of the acquisition from a CDP-centric point of view which fits very nicely with my views from the MDM side of the fence, where I hope to offer some insight.

    Until now, Informatica’s stack focused on pure-play MDM: consolidation, stewardship, and publication of master data. That meant to truly get a 360-view of your customers, you had to tie your MDM Hub to traditional and modern analytic platforms to gain insights based on customer transactions and interactions. After you’ve achieved that you would try to use those behavioral and relationship insights in real time through systems of engagement (i.e. mobile apps, social media, marketing automation, etc.) for next best action recommendations and consistent omnichannel experiences. This is obviously very challenging, and you describe it well in your blog.

    A specific point I’d like to comment on is your suggestion that Informatica’s software has focused on linking identifiers from disparate systems and pulling data from sources as needed. What you are describing in MDM-speak is a “Registry” solution, which is one of 4 MDM implementation styles (as defined by Gartner). Informatica certainly supports this approach, but also supports the other 3 styles as well, which loosely align with what you describe as a “Consolidated” customer view.

    Thank you for offering your thoughts on the subject for free – I, for one, have greatly benefited from it!

    -Bryson

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