Financial Services: Cross-Sell Opportunities For Home Insurance Products

Complex Needs

Very few industry sectors are as complex and volatile as financial services. It requires a finely tuned balance of intricate moving parts and is fueled by complex and often unpredictable market factors.
This set of challenges combined with high volumes of customer data makes financial services an ideal space for machine learning interventions.

Deep data-driven insights and predictive models enable businesses to better manage transactions and activities in order to mitigate risk and exposure. Businesses can also intervene at key moments within transactions to drive preferred behaviors.

Predictive Analytics in direct sales & marketing

The core objective of the work undertaken with this client was to increase conversion rates within a target segment for specific home insurance policies. Insurance policies are known to be a “grudge purchase”,
a product traditionally mired in inertia and low levels of customer confidence.

The historical data was injected into the Xpanse Platform where it was automatically cleansed and transformed into a format acceptable by Machine Learning. Then multiple Predictive Cross-sell Models were generated, deployed and moved to action within several weeks.

The right message, to the right customer, at the right time

The resulting leads were grouped based on “propensity score” or “affinity” to purchase the policy, allowing the sales and marketing team to prioritize their time focusing on the Tier 1 & 2 leads most likely to convert.

By observing performance on a weekly basis, the sales team confirmed that Tier 3+ leads were ineffective and could be dismissed. The marketing team now had clear persona profiles for what the most valuable leads looked like and could execute targeted lead generation campaigns to drive the acquisition of Tier 1 leads.

Measurable Results:

  • Radical improvement of conversion rates: Tier 1 & 2 leads were proven through A/B testing to be much more effective for the sales teams.
  • Cost of operation: Reduced cost of buying leads by focusing on key characteristics of Tier 1 & 2 profiles.
  • From reactive to proactive: The detailed and proven lead scoring & predictive system allowed the marketing team to be more informed and more targeted in their lead gen. campaigns.