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Best practices in marketing analytics
Rusty Waner – vice president, Product marketing & strategy
-It’s all about delivering value to your consumer and getting right message to them at the right time
-Build an enterprise view of the customers information
-Have multiple views of information, with consistency across all, one in depth integrated database isn’t always needed
-Interactional and transactional details are needed, we need to go beyond contact info
-Use customer intelligent analytics – which is basically segmentation and personalization, trends, and predictive scoring
-Doing it right requires:
Value engagement combined with good management
A good relationship between online and offline data
-Here are some problems companies have faced related to analytics and how they resolved it ;
Companies have encountered problems with acquiring new customers, up selling existing business, and the recruitment cost related to data analytics
What they did in a general sense to resolve such issues was to employ data warehousing, then pull in data from all different business sources and finally using predictive modeling
In most cases companies by doing so have been able to reduce direct marketing cost by up to 30% and achieve goals of maximizing Roi and up-selling more customers
These companies learnt that direct mail and email needs to be sent out through and to integrated segments collated from cleaned data in a database
-Around 10 years ago Euro Star; required help to understand who their customers are, they wanted to know who were their business user, and tourist user, they seeked good data that would provide this information – The reason being is that previous strategies of sending out mass direct mail or emails related to one subject or topic to all recipients delivered poor results.
-Figures show you have 24 – 48 hours to take action on a significant event in the business environment i.e customer sign-up or transaction, however in most businesses s to identify a significant event you need good historical analytics
-Figures show good analytics for targeted emails is essential
Take for example Love film- they send out emails with dynamic content for each individual
They have complex analytics in place for their massive film library, as a result the suggestions they provide for recipients are based on a history of their selection and similarities
Common analytics errors:
Marketing not aligned with customer demands
Processes and metrics matter more than customer
Marketing not aligned across business units
Customer defect while you figure out who they are
Marketing not aligned with operations
Customer engaged but you can’t service their needs
Use your data-warehouse on your customer to avoid these common mistakes- especially by continually looking for key trends, data mining
Marketing needs to be lined up with the overall business goals, stock level and on-line promotion
A campaign to resolve some of these common analytics errors should begin with;
Define agreed quantifiable analytics metrics- I.e click through rate, transaction rate
Apply business performance benchmarks- how much % increase
Define achievable goals and objective- maybe based on competitors rate if you can find it out
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Links
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Originally published on the Contextured PPC Management Blog
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