More accurately segment and target customers based on estimated assets, investment style, spending capacity, credit, risk – not on demographics.
Customers want us to see them, understand them and connect with them. Marketers must motivate the right audiences to act while providing an exceptional customer experience, which is easier said than done in Financial Services. Compliance risk makes personalization efforts more complex and segmentation models built on protected class variables are problematic.
That’s why Equifax and Neustar have come together to build Financial Spectrum™, a powerful way to segment customers based on estimated measures of consumer financial capacity, investment style, behaviors, and characteristics - thus reducing possible compliance risk.
Customers have specific financial preferences that can be difficult to discern or discover
Marketers have strong demographic-based insights, but have concerns about compliance risk
Increasing privacy concerns raise the compliance risk associated with personalized offers
Difficulties forming a complete view of persistent customer behavior, including financial preferences
Challenges with segmentation resulting in poor campaign performance or measurement
Using multi-dimensional financial and economic insights, we have identified the persistent characteristics that help you to better serve your customers, your business, and which are most predictive for financial services marketing.
Leveraging proprietary IXITM Network direct-measured™ asset data, Neustar built a segmentation schema across all US households that is stable over time, and links to syndicated data sources – providing a better understanding of the likely financial profile of U.S. consumers, such as financial affluence level, asset allocation, investment style, channel preference, media usage, and other lifestyle preferences.
The segmentation criteria used in Financial Spectrum™ focus on statistical separation, simplicity, stability and actionability. Using proven, agglomerative clustering and non-protected class data, we created a non-FCRA financial segmentation schema of fifty-eight (58) clusters that maintains financial and demographic similarity, including: estimated financial capacity, investment style, psychographic details and other behavioral characteristics.
We are committed to the responsible use of personal information to help businesses make better decisions and deliver personalized content without sacrificing individual privacy.