The Data is Pristine and Accessible. In My Mind's Eye!

Tamara Gielen has a post titled Triggered Email Is Only As Good As Your Data over on the B2B E-mail Marketing blog. She describes a scenario where you want to send a satisfaction survey to customers 90 days before their contract expires with your company, and adds on some logic of resending the survey to customers who do not respond to the initial request. Her point is — that may be a lot trickier than it sounds if you’re actually living in the real world:

• The data needed to trigger and send these e-mails lives in different systems
• You don’t have a good way to determine whom at the account should receive the e-mail (you probably don’t want to send the survey to everyone you have in your systems for the acccount)
• You don’t have a mechanism for updating your data when someone leaves the account and is no longer an employee there
• The list goes on…

The real world would put you in a position of needing to make some unpleasant decisions:

• Do you cast the net broadly and risk sending a non-applicable e-mail to a bunch of people in your database, or do you cast the net very narrowly and only send to people you are absolutely sure are the right folk…but then limit the impact of doing the survey in the first place?
• Do you limit the amount of manual cleanup on the data, or do you engage your sales and account management groups to manually flag who should receive the invitation (or something in between)?
• Do you try to explain all of the caveats of the data to the person who initiated the project, or do you just make a series of judgment calls and be prepared to defend/explain them if asked later?

The truth is that, in most cases, this sort of initiative does make sense, but it also requires making a long list of trade-offs, assumptions, and judgment calls to balance the expected impact with the effort required.

The entry brought to mind some interesting data integrity snafus that I’ve come across in my personal life:

• For years, the phone company thought my name was “Jim” rather than “Tim” — initially, this only impacted caller ID, but, over time, that list got sold to various direct marketers, and “Jim” started getting junk mail
• Several months after we moved to Ohio, I went into REI in Austin, and when they looked up my account, they had my Ohio address with a phone number of my former employer — none of this was information that we had ever explicitly provided
• After moving to Ohio, we signed up for a Giant Eagle grocery store card, with our new address and phone number; somehow, a couple of months later, when I didn’t have my card with me and they had to look me up…they had the address as our address in Austin!
• I recently shifted my cell phone plan from my wife’s and my joint account with T-Mobile to my company’s account with AT&T; I found out last week that I show up as “Julie Wilson” on caller ID when I make calls with my cell phone
• For years, Microsoft was convinced that I was a high-level IT manager responsible for my company’s system administration and infrastructure — I’ve never been within a light-year of that sort of role

All of this is to say that the data is messy. It’s never going to be perfect. Spending time and energy on data integrity initiatives makes sense, but that has to be balanced with the practical reality of the world — short of an Orwellian society, the data is always going to have some level of inaccuracy. Understand the data. Understand what you’re trying to accomplish with it. And then make a judgment call.

Photo by Daquella manera