Insurance sales are complicated and very different than selling physical products. The cost of insurance varies based on a range of factors such as location and age. In many cases the rates will vary between two adjoining zip codes and will certainly vary between providers.
Understanding that rate quotes are often the difference between winning and losing, the client wanted to gauge the competitive landscape. This knowledge would steer marketing efforts targeting activity where they were most likely to win.
The client’s internal research team had already acquired a unique set of data from a top aggregator – this data included rates quoted across the country by a variety of providers. The team knew that this was great data but did not have a program to make it actionable for marketing purposes. Reach Analytics built a comparative pricing model and scored individual micro-markets to best direct the marketing spend.
Upon implementing the pricing model, the team quickly identified the geographies where they had superior rate quotes. They also identified areas where they competed poorly. The model scored every zip code on the company’s ability to compete with their top competitors.
Results from analyzing a US random direct mail campaign showed:
- The pricing model could shift 40% of the mailings to more competitive areas from the previous campaign and by doing so it generated a 56% increase in sales.