Improving campaign results isn’t always a matter of rethinking the content or using creative artwork. Using data modelling is essential to help target the right customers.
In a saturated market creativity is essential to stand out from the competition and ensure your campaigns drive growth. But when different content or marketing strategies aren’t getting results, the issue may be deeper. As ReMark has learned from our experience in the UK market, smarter customer targeting, through advanced data modelling, is a valuable tool.
A saturated market
ReMark has had a long history in the UK market with our first online campaign to British consumers nearly two decades ago. As the birthplace of modern insurance, the United Kingdom—and London especially—is a centre of insurance expertise, but, as an established, mature market, there are still a number of opportunities for innovation. ReMark’s reputation for creative marketing and product development, as well as our expertise in data modelling, have been the backbone of our growth in the UK.
For 10 years ReMark worked with a well-established British consumer brand who offers retail insurance products. We ran direct mail marketing campaigns targeting their over 50s portfolio, selling a guaranteed-issue term-life insurance policy with the target list coming from the client’s own customer database. Customers could respond via a number of channels: over the phone, by mail, in branch or online.
"Integrating data analytics and predictive modelling into the targeting process is key to leading successful campaigns"
One of the key challenges driven mostly by market saturation and competition was that fewer and fewer customers took up the offer from the campaigns. ReMark is known for our international expertise in marketing yet despite different testing strategies and new, creative artwork in the campaigns numbers were still decreasing, with response rates dropping over two years from 0.36% to 0.24%.
Targeting the right customers
The solution? Using data modelling to better target customers and ensure the product was marketed to an even narrower audience who would be more likely to respond. As we’ve seen in other markets the key to addressing low response rates is often an issue of who you target rather than the design of the campaigns themselves. ReMark’s data science team produced a predictive data model built to ‘score’ a potential customer’s affinity to financial products. Key attributes of customer life stage, demographic data and behavioural information were added to already known customer metrics.
>20% increase in response rates with the new targeting process
This model then guided the mailing strategy on which customers to select and what products to offer. Our analysis showed that the general profile of an Over-50s life insurance customer is a narrow one of less affluence and lower savings. In determining who would respond to such a campaign and who likely wouldn’t, strong factors are living in social rented housing, being over retirement age and holding other financial products.
The results were very positive. Our test sample of 168,000 records showed an uplift of over 20% in the response rate over the typical control sample of 900,000, across three campaigns. Integrating data analytics and predictive modelling into the targeting process is key to leading successful campaigns. and ReMark is now able to apply this similar expertise globally with different clients in different markets.