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James Taylor
James Taylor's Decision Management
James is one the leading experts in enterprise decision management, a published author and a principal of Smart (enough) Systems LLC. His blog discusses the use of decision management technologies like predictive analytics and business rules to deliver agility, improve business processes and bring intelligent automation to SOA.

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February 06, 2008
Marketing Analytics in a Post-Web 2.0 World

Steve Wind-Mozley had an article on CRM Daily - Analytics in a Post-Web 2.0 World - that caught my eye. The summary of the article says:

In the established online marketing world, canny marketers have long understood that one size does not fit all. They have been pushing technology providers to enable them to deliver marketing collateral that is tailored to the individual consumer targeted on the fly. This is leading to marketing campaigns being increasingly targeted.

Steve makes the point that the realities of multi-channel customers are evolving as the number of potential channels through which a customer can interact is exploding. To websites and email we must add video, RSS feeds, blogs, wikis, social media and more - there are lots of ways to interact wit customers over the internet. To make use of this he correctly points out that marketers need to tie everything back to a customer or prospect - no easy task as more and more of these activities take place where companies have a hard time getting logs. While Steve does mention offline behavior too, he comes to it later than I would. Integrating "soft" behavior information with "hard" customer profile and sales information is going to make a big difference to its value. Steve's proposed usage of this combined data is still focused on improving the online experience where I would go beyond that and talk about the decisions that can be altered based on it - offline or online decisions in everything from marketing to sales to customer service to warranty to loyalty programs.

I also have a specific suggestion to address the problem Steve notes of too much data - start with the end (the decision) in mind and find/integrate the analytics/data that will make a difference to that decision. What would it be useful to know about a customer before making each decision? How can you find that out about a customer or is there some set of behaviors that act as a good surrogate? This will help keep you focused on the data that matters.

I also blogged on social media and enterprise decision management a couple of times - here and here.

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