Direct mail provides more data elements to target against than any other marketing channel. The typical national data compiler manages over three thousand data points per person.* Combine a multi-sourced wealth of data with sophisticated predictive analytics, and we can precisely rank prospects based on the propensity to respond (or other required outcomes).
Financial Services and Insurance – Credit Data
For financial and insurance clients, we see widespread use of credit bureau prescreened data – both in terms of triggers (credit or insurance inquiries by consumers) and broad market (often dictated by bureau credit score and other data points) campaigns.
As a direct marketing service provider, Nahan partners with credit data agents, which can provide unique sources of value. Credit data agents typically receive and maintain real-time data from all 3 main credit bureaus, providing a comprehensive picture of all credit behavior across bureaus. More data across all 3 bureaus means more net qualified names, typically 15-20% more, and improved credit decisioning. It also means more flexibility in terms of FCRA regulations, allowing for counts to be more easily run before actually pulling a file.
Multiple Industries – Modeled Compiled Data
Compiled data is just that – data compiled from multiple sources and then linked to individuals and households. It’s typically used in travel, healthcare, retail, telecom, and auto direct mail. There are a number of medium and large-sized data compilers that we partner with to provide the best data for our clients. Compiled data typically includes demographic, psychographic and attitudinal data.
Catalogers, Non-Profits, E-tailors and Others – Cooperative (Co-op) Data
Co-op data is customer purchased data collected from thousands of co-op members and maintained in a database. Typically, a member marketer must provide their customer data on a regular basis to join and participate. Co-op members include companies from the catalog, retail, etail, continuity, non-profit, publishers, finance, insurance, and business-to-business industries. The depth and granularity of the data can vary by co-op. Given that customer behavior is often the most predictive of future behavior, this data is very powerful in its ability to predict the future response and purchasing.
B2B direct mail data used to be about two main data sources – Data Axle (formerly InfoGroup) and Dun & Bradstreet. They are still major players providing excellent data. Both, along with a continual flow of new players, now offer much more than the traditional data points like annual sales, number of employees, SIC code, and NAIC Code.
The Role of Analytics
The performance of all data mentioned here can and should be enhanced by predictive analytics. We simply can’t leverage any of these types of data to their full potential without the use of predictive modeling to prioritize prospects.
Our Data Role
Nahan has deep and long-time relationships with many types of direct mail data providers and list brokers. We can determine which source is the right fit for our clients’ objectives. Typically at a lower cost than our clients can obtain on their own. Our expertise ensures the best possible data at the best possible price.