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Dear Email Address Occupant

There’s a great post over on CircleID from John Levine and his experience with a marketer sending mail to a spam trap.
Apparently, some time back in 2002 someone opted in an address that didn’t belong to them to a marketing database. It may have been a hard to read scribble that was misread when the data was scanned (or typed) into the database. It could be that the person didn’t actually know their email address. There are a lot of ways spamtraps can end up on lists that don’t involve malice on the part of the sender.
But I can’t help thinking that mailing an address for 10 years, where the person has never ever responded might be a sign that the address isn’t valid. Or that the recipient might not want what you’re selling or, is not actually a potential customer.
I wrote a few weeks back about the difference between delivery and marketing. That has sparked conversations, including one where I discovered there are a lot of marketers out there that loathe and despise delivery people. But it’s delivery people who understand that not every email address is a potential purchaser. Our job is to make sure that mail to non-existent “customers” doesn’t stop mail from actually getting to actual potential customers.
Email doesn’t have an equivalent of “occupant” or “resident.” Email marketers need to pay attention to their data quality and hygiene. In the snail mail world, that isn’t true. My parents still get marketing mail addressed to me, and I’ve not lived in that house for 20+ years. Sure, it’s possible an 18 year old interested in virginia slims might move into that house at some point, and maybe that 20 years of marketing will pay off. It only costs a few cents to keep that address on their list and the potential return is there.
In email, though, sending mail to addresses that don’t have a real recipient there has the potential to hurt delivery to all other recipients on your list. Is one or two bad addresses going to be the difference between blocked and inbox? No, but the more abandoned addresses and non-existent recipients on a list there are on a list, the more likely filters will decide the mail isn’t really important or wanted.
The cost of keeping that address, one that will never, ever convert on a list may mean losing access to the inbox of actual, real, converting customers.
 

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Delivery versus marketing

I’ve been thinking lately that sometimes that what works for marketing doesn’t always work for delivery.
For instance in many areas of marketing repetition is key. Repeat a slogan and forge an association between the slogan and the product in the mind of the consumer. More repetition is better. Marketers can even go so far as using the same ad to drive consumer action. Television advertising is a prime example of this. Companies don’t create new content for every advertising slot, they create one or a few ads and then replay them over and over. The advertiser doesn’t even really care if the consumer consciously ignores the ads. The unconscious connection is still being made.
In the world of email delivery, though, having many or most recipients ignore advertising is the kiss of death. Too many unengaged users and filters decide that mail shouldn’t go into the inbox. These don’t even have to be ISP level filters, but Bayesian filters built into desktop mail clients.
Sending repetitive ads over email may be an effective marketing strategy, but may not be an effective delivery strategy.
Am I off base here and missing something? Tell me I’m wrong in the comments.

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Inbox rates and conversion rates

Jeanne Jennings published an interesting bit of research on open rates and inbox rates at ClickZ recently. Essentially she looked at two different industry studies and compared their results.
The first study was the Return Path Global Delivery Survey and the second was the Epsilon North American Trend Results. What Jeanne found is that while Return Path shows a decrease in inbox placement, Epsilon is seeing an increase in average open rate.

There are any number of reasons this could be happening, including simply different ways the numbers are calculated. I am not sure it’s just a numbers issue, though. Many of Epsilon’s clients are very big companies with a very experienced marketing team. The Return Path data is across their whole user base, which is a much broader range of marketers at different levels of sophistication.
I expect that the Epsilon data is a subset of the Return Path data, and a subset at the high end at that. It does hint, though, that when the inbox is less cluttered, recipients are more likely to open the commercial mail that does get in there.

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