I spent much of last year writing about Customer Data Platform systems and have reviews on tap for a half dozen more. But I thought I’d start out 2014 with something different, just to show I’m not totally obsessed. Although, as you’ll see shortly, there’s a CDP angle to this story as well.
It would probably be fairly easy for BrightInfo to support mobile and access external data sources, since the necessary changes are unrelated to its core technologies of semantic analysis and recommendations. Most companies today could probably use the system as it stands, since they lack a centralized customer database or policies to coordinate customer treatments across channels. BrightInfo already lets users override the purely algorithmic recommendations by specifying that some content will be shown in all circumstances, that other content will never be shown, and that recommendations will appear only on specified pages. Sophisticated marketers might want more refined controls, such as limits on how often the same content is offered or recommendations based on expected response value rather than the simple click rate. But BrightInfo is targeted at small and mid-size businesses, which are less concerned with such refinements.
BrightInfo officially released its product last September, after about a year of development. The underlying semantic and recommendation technologies came from sister company Softlib Software, which uses them for automated service and knowledge management and was founded in 2004. Pricing is published on the BrightInfo Web site and is free up to 1,000 visitors per month, $89 per month up to 5,000 visitors, and $224 per month up to 15,000 visitors. The system has several dozen clients.
To summarize, then: BrightInfo provides a very simple, very low cost way to increase engagement with Web visitors by making targeted content recommendations. It’s worth knowing about because traditional recommendation engines are often harder to deploy and more expensive.
But what’s the CDP angle? It’s not simply that BrightInfo is an example of an application that could use the customer data in a CDP to make more accurate recommendations. It’s actually a somewhat deeper question of where the recommendation functions belong in a CDP-based architecture. I’d argue that recommendations should be part of the central platform, so they can be used to coordinate treatments across all touchpoints. In other words, it’s probably wrong to imagine BrightInfo as an application that attaches to a CDP and uses its data to improve Web and blog results. Rather, in an ideal world, BrightInfo’s technology would be used within the CDP to generate recommendation that the CDP itself feeds to all applications. This is pretty theoretical and largely irrelevant to BrightInfo itself, which is targeted at companies that don’t have a CDP in the first place. But as marketing technology continues to evolve and more companies have CDPs, or centralized customer databases by any other name, it’s important to understand how the pieces should fit together.