I work for a largish international company focused on B2B sales with offices in North America, 16* European countries, and 8 countries in the Asia-Pacific region. In the U.S., the company is divided into 6 autonomous Business Units and smaller offices focused on regional, partner, and public sector marketing and sales. Then throw in the fact that we pull all data from the same 9 pools and that contacts can have interests in multiple product areas and everyone wants to send email.
This is not always the best example for a good customer experience.
The data structure for a company of this size and complexity is very fragile. Every office wants to send to their “base,” not realizing that their base actually coincides in many cases with the other offices’ bases and sales. It’s a big Venn diagram (I can’t believe I actually referenced a Venn diagram) and acts like a big data ecosystem- when one section does something bad, it effects everything, like plankton in the ocean or when bees die because of everyone needing to check Facebook or Twitter every 5 seconds on their iPhones.
If business units/different offices/any entities with different goals and incentives share a database, a higher potential for DB exhaustion exists than in an environment where only one interest is focused upon. “No kidding,” you may say. To combat exhaustion and generally pissing off contacts, the users of a shared database must observe and respect recency and content relevancy. If not, contacts can receive multiple offers from different sources within the same company without the company even realizing. However, the contact notices and will let you know (HINT: this is bad).
For some companies, specifically those focused on B2C, email frequency doesn’t seem to matter. I get at least 1 Banana Republic/Gap/Piperlime/Old Navy email per day, sometimes 2 or 3. Same with Tiger Direct and Amazon. Some B2C companies are able to send frequently from different divisions to the same database (I’ve never signed up for Piperlime emails) because they are sending coupons and deal offers. I never unsubscribe, just always glance and delete- someday they may have a good deal.
B2B doesn’t have that kind of leeway; most sales decisions require more than a knee-jerk reaction that B2C businesses try to invoke. If the B2B marketer emails the same person more than 1 time in a week (or day), no matter if it is from a different division, expect a nasty email (best case), an unsubscribe (not terrible, but not optimal), or a spam complaint (oh shit). Once any of these scenarios occur in one division, it affects the entire company, from IP/domain reputation to contacts unsubscribing from all emails.
In this type of data ecosystem, it is important for the email marketing team (or whatever team is responsible for list pulls and segmentation) to completely understand any and all of the data they are required to obtain on behalf of requestors. In short, list generators must be proactive, not reactive, and given to the tools uphold standardized rules (such as recency) and the ability to make suggestions to optimize lists. And content must- MUST!- be relevant to each receiver.
In turn, email list developers must show the ability to add value to the list pulls by citing in-company testing and have knowledge of best practices for email as a whole, the industry, the company’s own database (this is accomplished through running statistically relevant tests to show the value of segmentation and cross-promotion, experience, and probably a little luck).
* In his book Jailbird, Kurt Vonnegut specifically uses the number form for every numerical reference. Either because I enjoy that book immensely or because I am too lazy to remember back to my AP Style class to figure out when to use the number or spell it out, I will do the same. I have better things to do, like play Scrabble on Facebook.
