Here I am, all excited about discovering a new category of Customer Data Platform systems, which combine marketing database management, predictive modeling, and decision engines. Then I bump into Omer Artun, CEO of AgilOne , which he founded seven years ago to combine marketing database management, predictive modeling, and decision engines. It makes me feel much less clever.
But I guess I can’t hold that against AgilOne. As Artun tells the story, the company was created to provide marketers with a packaged, cloud-based version of the advanced data management, analytics, and execution capabilities that are usually available only to the largest and richest firms. The key is a set of 400 standard metrics, which AgilOne derives by mapping each client’s unique data into a standard structure. This, combined with advanced machine learning techniques, lets AgilOne build ten standard predictive models (engagement, next product, lifetime value, etc.) and three standard cluster models (products, behaviors, and brands) with minimal effort. The system builds on these to deliver packages of standard alerts, reports, guided analytics, individual customer profiles, and campaign lists. It also makes its data and predictions accessible to external systems such as call centers and Web sites via real time API calls, so those systems can use them to guide their own customer treatments.
This quick summary doesn’t do justice to the cleverness or sophistication of AgilOne’s approach. Clever, because the standardization allows it to quickly and cheaply deliver a full stack of capabilities, starting with database building and ending with advanced analytics, recommendations, and execution. Sophisticated, because it tailors the standard structures to each client’s business, so what it delivers isn’t some simple, cookie-cutter output.
Some of the tailoring is unavoidably manual, such as mapping client data sources to the standard data model. But much is highly automated, such as predictive models, clusters, and recommendations. I was particularly intrigued by the standard alerts, which look for significant changes in key performance indicators such as churn, margin, or average order value. That sort of alerting is exactly what I've long felt marketers really wanted from their analytics tools. AgilOne takes this a step further by automatically listing the data attributes with the greatest statistical impact on each item. The company refers to these items as goals to prioritize, which is a bit of a stretch – the most powerful variable isn’t necessarily the one marketers should focus on the most. But, as Damon Runyon said*, that’s the way to bet.
The system also recommends actions related to each alert, such as certain types of marketing campaigns. Again, there’s a bit less here than meets the eye, since the recommendations are drawn from a knowledgebase that’s the same for all clients. But that’s still better than nothing, and clients can customize their copy of the knowledgebase if they want.
The other especially noteworthy strength of AgilOne is data preparation. My original concept of the Customer Data Platform included customer data integration, which involves standardizing and matching customer records from different systems. I’ve pulled back from that because almost none of the vendors actually do such processing. Most assume it will be done elsewhere, or not at all, and only associate records with an exact match on a key such as a customer ID. AgilOne does the hard stuff: quality checks, outlier detection, name parsing, address standardization, geocoding, phonetic matching, persistent ID management, and more. This is also highly automated and uses the company’s own technology. The lack of these capabilities prevents many companies from building a truly integrated customer database at many companies, so it’s extremely valuable for AgilOne to provide it.
If AgilOne has a weakness, it's at the execution end of the process. Users can set up campaigns that generate lists on demand or on a regular schedule. But I didn't see multi-step campaign flows or sophisticated decision management, such as arbitration across multiple eligible offers. Some of that can probably be managed through advanced filters and custom models, which the system does provide. However, making it truly accessible to non-technical users requires a specialized interface that the system apparently lacks.
While AgilOne just recently appeared on my personal radar, plenty of other people had already noticed: the company says nearly 100 brands are using the system. Sales efforts have been concentrated among mid-size B2C organizations, typically with at least 200,000 customers and $15 to $20 million in revenue. Pricing is published on the company Web site and is based on the features used and number of active customers. Entry price for the complete set of features starts around $9,000 per month.
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*“The race is not always to the swift nor the battle to the strong, but that's the way to bet.” Runyon himself credited Chicago journalist Hugh Keough.
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