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Challenge:

A leading aerospace company was challenged with identifying viable targets and prioritizing the time of a limited business development staff.  The management team also wanted a thorough understanding of the prospect universe to more accurately assess current and potential market share. While the company had a variety of data inputs in the form of contact lists, current customer lists, tradeshow attendees, etc., they had no means of tying the information together.

Solution:

We educated the company in “Big Data” and used a new, advanced analytic approach to design and execute a multi-source datamart. The mart was a compilation of a variety of inputs – current customer look alikes, trade show visitors, website inquiries, purchased lists and publication lists – which were used for predictive modeling. From the models, Wheelhouse identified segments and micro segments for each division of the company. The segments were then prioritized based on propensity to purchase (for prospects) and propensity to upgrade (for customers).

Results:

The new datamart was tested via a divisional email campaign, with highly successful results. The new list increased email deliverability, increased open rates and conversion rates. What’s more is that the company can now start to feed dispositions into the base, which creates a true “data lifecycle” and allows for the assessment of current and future trends.