Lists are the bane of database marketers existence. Everyone thinks their own data sucks but the real disappointment usually comes when you rent a compiled list and realize they suck too. Everyone wonders why this is but few have done anything about it -- till now.
Ruth Stevens and Bernice Grossman have been writing white papers on database marketing since 2005. Both are well known independent thinkers and marketers with extensive direct marketing and database chops. For their seventh outing they devised a wickedly simple test titled "Online Sources of B-to-B Data: A Comparative Analysis" to understand the limitations of compiled lists.
They convinced ten database compilers to participate and asked them to find 10 selected executives from 10 different industry verticals in their databases. It was a dip stick exercise to quickly measure the coverage and quality of leading databases. The vendors ranged from big data houses to online cooperatives. All have online ordering capabilities which generally means they are willing to deal in small lots and/or niche verticals.
Bottom line -- when they had your data it was pretty accurate, though coverage was spotty across databases.
In addition the study turned up a bunch of surprising results:
- There was a wide variance in company and contact counts. In one category -- stone, clay and glass products -- company counts ranged from 386 on one database to 36,382 on another.
- Email addresses were the hardest datapoint to find. Unfortunately these days its the datapoint most in demand.
- When a vendor had your record, there was a good chance of accuracy.
- But many vendors didn't have the 10 executives in their database. In the worst case only 2 of ten vendors could find Jim Carey of Northwestern University. Maybe its a subtle hint about academics.
- C level names seemed to be evident in more databases than lower ranking players. This could speak to the method of compilation.
So what's a B2B marketer to do? Bernice and Ruth recommend these steps.
1. Quiz the vendors on what they have and how they got it.
2. Don't assume subsidiaries of large compilers have the same data or use the same compilation or cleansing techniques. They don't. Ask.
3. Be very specific when placing list or database orders. Use SIC codes or other tools to keep 'em honest and to be sure you get what you thought you ordered.
4. Check for industry or vertical specialization. Test their coverage before you buy. Shop for the vendor who has the best data on your target audience.
5. Run a data append test before you buy to test coverage and accuracy and to compare multiple vendors. Build in some house names that you know for sure as an accuracy benchmark. Better yet buy a small number of names and verify the data yourself by phone before you place a bigger order.
There's about 12 million companies in the USA and evidently getting to someone in them still isn't easy as you think it might be. These kind of exercises help us understand the realities and limits of databases which in turn drive our thinking on how best to use the data we can get our hands on.
Comments