In a cooperative marketing database, multiple mailers contribute their house lists. Merge/purge removes duplicate names, giving you a single unduplicated master database reaching all the business buyers in all the lists comprising the cooperative.
As a result, cooperative databases often give mailers access to a larger universe of names than any individual list can. Selections and searches can be conducted across all records in the database, increasing your ability to model, refine list selections, increase response rates, suppress undesirable records (e.g., prospects who never respond) and reduce rental costs.
There are approximately a half-dozen, large co-op databases on the market today. These include Executive Data Bank, MeritBase, Experian, Abacus and Edith Roman’s List Exchange Database (LEX).
When choosing records to mail – whether from a co-op database, a segment of the database or even individual lists – you can use a P/E coefficient to identify the most responsive names. The P/E coefficient is the ratio of penetration to employees.
By “penetration,” we mean the number of buying influences on the list at a particular location or site. When mailing to a co-op database, you can quickly and easily search the database to find out how many names it contains at any site of any company. The higher the penetration, the better the quality of your name selection – and conversely, a low penetration is a negative.
Say penetration is one – you only have one person from the business site in the database. It could mean the site is a tiny mom-and-pop business with limited purchasing power. Or, the name may be a seed on one of the lists in the database. Low penetration also might mean that the business does not employ many people fitting your ideal customer profile, and therefore would not be an active purchaser of your product category.
On the other hand, large penetration means that the business is probably of a significant size with a significant budget, and that it employs many active buyers who fit your ideal customer profile – a good sign you should mail to them.
An even more accurate predictor of responsiveness is the P/E coefficient – the ratio of penetration (how many potential customers at the site are in the database) to the total number of employees at that site.
If the P/E is high, it means that your database contains a relatively large number of buyer names in proportion to the total number of employees at this site.
So if the site had 100 employees, and 20 of them fit your ideal customer profile, then one out of five employees at the company is a potential customer for your product or service – a relatively high P/E coefficient. This tells you the business is actively engaged in projects or tasks that require what you are selling.
On the other hand, if the database contains just one name at the site that fits your customer profile, and the site employs 1,000 people, then one out of a thousand employees is a potential customer for your product or service. This low P/E coefficient indicates that the business probably has minimal demand for your product.
You can apply the P/E ratio to the entire cooperative database, a subset of the lists in the database or even a single mailing list. If you are targeting a job function or title across a broad range of industries – for instance, your potential customers are purchasing agents at virtually any type of business of any size – you might choose to select sites with high P/E ratios from the whole database. On the other hand, if your target is chemical engineers at processing plants, you’re more likely to look at a small subset of the database.