analyzing DISPARATE DATA STREAMS FOR targeted customer retention and growth
The CHALLENGE
A pharmaceutical organization was struggling to bridge the gap between their customer data silos to have a unified, data-driven account targeting strategy.
Burke, with the support of their Data Scientists, pulled together the company’s disparate information sources and created a segmentation framework based on all customer account data using Geode|AI®. This allowed the company to create more personalized sales strategies, leading to better targeting of key accounts that drove revenue.
The APPROACH
Burke’s Data Scientists employed advanced analytical models as a part of the Geode|AI® suite of services. The team was able to combine large, disparate data sets, such as integrated sales call information and geodemographic characteristics with transactional data, to create a common framework for targeting key accounts. The team then implemented a variety of unsupervised machine learning approaches – including Gaussian Mixture Models and K-Means – to efficiently uncover key revenue-generating segments among 14,000 existing customers. Since the customer records included revenue information, identifying these core segments facilitated unique outreach and set the stage for innovative targeting strategies for retention and growth of these key customer accounts.
The OUTCOME
Burke ultimately identified five target segments, comprising about 20% of accounts and 50% of sales revenue. The identification of these segments enabled the client to review and refresh their active account inventory, and subsequently allowed for a more structured approach to future sales targeting. The client moved from a one-for-all approach to a targeting strategy that personalized outreach for their core strategic accounts, allowing them to more easily retain their most valuable accounts.
FEATURED CASE STUDIES
