Mail.app outs lazy marketers

The default mail client on OS X is Mail.app. In recent versions it does it’s best to bundle threads of email together to make it easier for you to keep track of conversations via email – they appear in the list of messages as a single entry with a badge showing the number of messages in that thread. There are standard ways to track mail threads, but they sometimes get broken by mailing list software, so Mail.app also bundles together messages with an identical sender and Subject line.
That has an unexpected side effect, when it comes to email marketing.

That little “4” badge on the right tells me that this is the fourth time Marriott have sent me this same email (over a period of several months) and there’s really no need for me to open it and read it again.

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The really great thing, for the ISPs, about engagement metrics is that they directly measure how much a particular email is wanted by recipients. There’s no guessing about it, it measures how engaged the recipient is with a mail. Even better is the fact that, unlike proxy metrics, engagement metrics are extremely difficult for the sender to manipulate. As a sender I can artificially lower complaints and bounces without improving the mail I’m sending. But I can’t improve engagement metrics without actually engaging my recipients.
As I wrote back in 2010:

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Relevant and timely marketing

What better time to advertise pizza specials than at 2:30 pm on a Friday afternoon?
Either my local pizza joint is doing sophisticated tracking (hrmmm… these people often order pizza on the weekend, email on Friday) or I’m just smack dab in the middle of their average demographic.
In either case, advertising pizza on a Friday afternoon strikes me as the epitome of timely, relevant marketing.
Pizza for dinner, anyone?

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Poor research and a quickly written blog post led to me endorsing a company that I absolutely shouldn’t have. And I do apologize for that.
With all that being said, Justin had a great question in the comments of yesterday’s post about data cleansing.

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