Case Study | Insurance

View our case study on how Sutherland helped a top US auto insurance company drive smart, actionable and scalable solutions with applied analytics.

Services Sutherland Labs, Digital Engineering Services, Business process services
Industry Insurance
JANUARY 13, 2017

Our client wanted to understand the effectiveness of its marketing media mix in driving auto insurance quote volumes into its call centers. A smart, actionable, and scalable solution was needed for analyzing their media efforts, the whole delivered at speed and with consistency. This entailed analyzing a number of factors, including media spend, ratings, impressions, external economic factors, and other relevant metrics.

Sutherland leveraged nBAAPTM to build a media mix model for quote volumes from existing customers (CQV) and quote volumes from prospects (PQV). Our team:

  • Identified the key drivers impacting quote volumes for various insurance product segments
  • Identified the incremental impact of each media action and external factors such as unemployment rate, etc. on quote volume
  • Created what-if simulators based on the knowledge gleaned from the media mix models

The insights acquired from the scenarios we ran helped the insurer plan optimal marketing investments. Analyses included:

Scenario 1: The response curve equation was applied to current and future media spends or impressions. The difference between the two was the incremental quote volume, which is spread across the weeks using the decay factor.

Scenario 2: In this analysis, the user can alter the current and future spend or impressions for various media and see how much each of it contributes to the quote volume. The equation is applied to the current spend; the resultant quote volume is the current quote volume. Similarly, applying the equation to future spend yields the future quote volume.

The Variables analyzed across multiple scenarios included:

  • Dependent variables
    • Quote volumes from existing customers (CQV)
    • Quote volumes from prospects (PQV), two different models
  • Independent variables
    • Broadly classified as impressions (mainstream media, cable TV, Spanish TV, etc.) - Spend (radio, print, news and magazines, etc.)
    • Clicks (keyword search, banner ads, organic and paid search)
    • Macro-economic indices such as unemployment rate, gas prices, etc.

The various analyses helped the carrier allocate media spends for desired quote volumes. This new insight was used to identify prospects and focus call center resources for the most impactful outcomes.

Partnering with our client, Sutherland:

  • Helped drive up quote volumes incrementally by 22% while keeping the media spend constant
  • Provided unique insight into how different marketing tactics (investment in media types) and external factors drive incremental quote volumes into the call centers; data the carrier never had before
  • Identified which key marketing channels maximize leads
  • Provided insights from what-if analyses where multiple scenarios were simulated to arrive at optimal budget allocation across media channels

Learn More About Our Sutherland Robility Services?

Related Insights