Thursday, August 31, 2017

AgilOne Adds New Flexibility to An Already-Powerful Customer Data Platform

It’s more than four years since my original review of AgilOne, a pioneering Customer Data Platform. As you might imagine, the system has evolved quite a bit since then. In fact, the core data management portions have been entirely rebuilt, replacing the original fixed data model with a fully configurable model that lets the system easily adapt to each customer.

The new version uses a bouquet of colorfully-named big data technologies (Kafka, Parquet, Impala, Spark, Elastic Search, etc.) to support streaming inputs, machine learning, real time queries, ad hoc analytics, SQL access, and other things that don’t come naturally to Hadoop. It also runs on distributed processors that allow fast scaling to meet peak demands. That’s especially important to AgilOne since most of its clients are retailers whose business can spike sharply on days like Black Friday.

In other ways, though, AgilOne is still similar to the system I reviewed in 2013. It still provides sophisticated data quality, postal processing, and name/address matching, which are often missing in CDPs designed primarily for online data. It still has more than 300 predefined attributes for specialized analytics and processing, although the system can function without them. It still includes predictive models and provides a powerful query builder to create audience segments. Campaigns are still designed to deliver one message, such as an email, although users could define campaigns with related audiences to deliver a sequence of messages. There’s still a “Customer360” screen to display detailed information about individual customers, including full interaction history.

But there’s plenty new as well. There are more connectors to data sources, a new interface to let users add custom fields and calculations for themselves, and workflow diagrams to manage data processing flows. Personalization has been enhanced and the system exposes message-related data elements including product recommendations and the last products browsed, purchased, and abandoned. AgilOne now supports Web, mobile, and social channels and offers more options for email delivery. A/b tests have been added while analytics and reporting have been enhanced.

What should be clear is that AgilOne has an exceptionally broad (and deep) set of features. This puts it at one end of the spectrum of Customer Data Platforms. At the other end are CDPs that build a unified, sharable customer database and do nothing else. In between are CDPs that offer some subset of what AgilOne offers: advanced identity management, offline data support, predictive analytics, segmentation, multi-channel campaigns, real time interactions, advanced analytics, and high scalability. This variety is good for buyers, since it means there’s a better chance they can find a system that matches their needs. But it’s also confusing, especially for buyers who are just learning about CDPs and don’t realize how much they can differ. That confusion is something we’re worrying about a lot at the CDP Institute right now. If you have ideas for how to deal with it, let me know.

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