Why Use Modeled Cooperative Databases for Mail?

Today's modeled cooperative databases offer big advantages for B2C and B2B direct marketers, which is why AccuList now represents 18 private modeled cooperative databases that clients can use to optimize direct mail results. These databases include millions of merged, deduped, and "modeled and scored" hotline names from thousands of commercial and nonprofit participants. At no charge, each can match the client's database, model client postal addresses, and deliver optimized “look-alike” names. The database will prioritize those modeled names by decile or quintile to help clients further identify targets most likely to respond to an offer or fundraising appeal. Marketers sometimes hesitate to participate because of unfounded fears of sharing exclusive/unique customers, catalog buyers, subscribers or donors with membership-based database participants. Note that these databases generally match a marketer's names against the cooperative database files and share transactional data. If there are matches, only transactional information is added to the cooperative database records; and if there are no matches, the unique names are not added to the pool. Why do cooperative databases opt to incorporate only multi-occurring or duplicate records? Because that is data that tends to be far more predictive, with proven response. Plus, the reality is that very few names are unique to a firm, publication or fundraiser. About 80% to 90% of consumer prospects are multi-buyers, and 90% of nonprofit donors give to two or more organizations, so these names are already included in cooperative data. On the other hand, by participating to access a huge pool of names rich with demographic and transactional information, marketers reap many gains. Acquisition campaigns clearly can benefit from netting look-alike prospects from the large cooperative database pool, a real boon for regional or niche mailers who struggle to find acquisition volume. The large universe also allows for more segmentation to target not only higher response groups but more valuable response segments. In the case of nonprofits, that could be high-dollar donors, for example. Profiling and modeling can create better results from house names, too. Instead of mailing the whole house file, current customers, subscribers or donors can be flagged for likelihood of response and upsell, for channel and messaging preference, for risk of lapse/attrition, and more. Plus, modeled databases offer cost efficiency via an attractive list CPM; recent, clean, deduped records that lower mailing costs; and optimization selects (or deselects) that also boost mailing efficiency and ROI. For more, see https://www.acculist.com/why-participate-in-modeled-cooperative-databases/