Predictive Marketing Blog

New Focus for Marketing Analytics: Lead Targeting

For the past 15 years, retailers, banks, non-profit, catalog companies and many other B2C businesses have spent the bulk of their marketing budget on new customer acquisition. On the flip side, vendors have tried to convince them that they should be focusing their analytic efforts on existing customers in order to cross-sell, up-sell or prevent them from churning.

These efforts have had limited success for the past 10 years. Whether vendors or companies are on the wrong path is not my point here, instead I want to explore how we can help companies with their primary pain points, namely:

  • How can we ensure that companies’ marketing budget is spent optimally?
  • How can we see to it that the large customer acquisition budget is not wasted on people who do not have the right profile to become their customers?

To address this issue, one needs to reallocate his analytic efforts on targeted lead acquisition programs. But this undertaking is not trivial as companies have very little information on people who are not current customers. Actually, direct marketing consulting firms have been addressing this issue and ultimately have been able to reduce the complexity of this task.

The process usually breaks down into these 3 steps:

  1. Match external data to an existing customer base
  2. Use machine learning to build customer profiles
  3. Apply these customer profiles to 3rd party data to identify new targeted leads

These steps require some heavy lifting in terms of data management and data science to standardize, de-dupe, and cleanse the data as well as build predictive analytic profiles. While these tasks previously took weeks for database administrators, data scientists, and statisticians to complete, this is no longer the case. Tremendous progress has been made over the past few years in the big data domain combined with cloud computing, which enables the running of hundreds of tasks in parallel (data preparation tasks, model building, etc). With a distributed environment one can, now in few seconds, identify targeted leads as well as understand the profile of his current customers.

As a result, it is therefore possible to help marketers manage and resolve their key pain points:

  • Identification of who they should target their marketing efforts on to increase their customer base is now an easier process. By providing science based relevant leads with actual contact details, they can launch marketing programs with better ROI.
  • Different targeted sets of leads can be provided per specific product offer with a detailed customer profile so they can allocate the appropriate budget to deliver compelling messages.


No need to focus on your entire customer base. Instead, understand your best customers’ profile in order to convert the right leads into the right customers for your company with a personalized message.