This blog series is based on The Definitive Guide to Predictive Marketing, available for download now. Check out Part 1, and stay tuned for the installments to come! 

Too much predictive intelligence works just fine until it bumps up against an actual customer. Then things start to get hairy. 

That’s because too many marketers, instead of leveraging a single customer view fueling sophisticated marketing intelligence, are facing multiple data flows and disparate systems that claim to offer predictive capabilities, but are hamstrung by the way those systems are stitched together. If the data flows and systems weren’t designed from the ground up to work together, it can be unacceptably difficult to leverage even accurate and timely insights into effective customer engagement.

Individual point solutions for predictive technology rely upon segment-level exporting. They can’t make predictions at the individual level or in real-time. Marketing clouds have a similar problem. While marketing clouds are often sold under a single brand name, they have been assembled through acquisitions and are often made up of multiple, separate technologies, each with their own database.

Enterprise marketing clouds and predictive point solutions rely on multiple data flows, which generate tremendous costs in time, money and accuracy. They have tremendous difficulty in helping marketers improve key metrics, because the predictions are only available at the segment level.
Enterprise marketing clouds and predictive point solutions rely on multiple data flows, which generate tremendous costs in time, money and accuracy. They have tremendous difficulty in helping marketers improve key metrics, because the predictions are only available at the segment level.

In order to make predictive intelligence work, marketers should use a single platform for data collection, marketing automation, and predictions. Because such a platform enables marketers to minimize data flows, predict behavior at the user-level, and automate optimization, a marketer using such a system can impact consumer behavior on a daily basis and dramatically increase revenues.

The most effective way to use predictions to drive transformative revenue gains is through the use of a single platform that is natively built for multichannel data collection, cross-channel engagement, and predictions, all at the individual user level.
This is the most effective way to use predictions to drive transformative revenue gains, and how we recommend all marketers approach their predictive decisioning technology and strategy.
If you’re talking to predictive technology vendors, we’d suggest you ask the following questions.

• Do you offer a single platform solution for data collection, marketing automation and predictions?

• Are predictions actionable at the individual user level or only at the segment level?

• How many data flows are needed to leverage predictions in specific channels, such as email?

Get the right answers to these questions, and there’s a good chance the promised predictions are going to be timely, targeted, and make a real impact.

–Neil Capel, Founder and Chairman of Sailthru

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