One of the big deliverability vs. marketing arguments has to do with data hygiene and dropping inactive users. Marketers hate that deliverability people tell them to let subscribers go after a long time of no activity from the subscriber.
Data hygiene is good. Email is not permanent and not forever, and the requirements for data hygiene in the email space are very different than the requirements in the postal mail space. There is no such thing as “dear occupant” in email. I mean, you can sent to occupant, but the occupant can then hit the this is spam button. Too many emails to “occupant” and mail goes to bulk instead of the inbox. These are real risks.
With that being said, there are a lot of things to consider when putting together a data hygiene program. You’re looking to remove people who are no longer interested in your brand as much as they are no longer interested in your mail. You’re trying to suss out who might have abandoned the email address you have for them. It’s complicated.
I’ve worked with a lot of clients over the years to implement data hygiene programs. Sometimes those programs were to deal with a bulk foldering issue. Other times clients have been trying to address a SBL listing. Still other clients were just looking for better control over their email and delivery. In all cases, my goal is to identify and classify their recipients into 3 groups: addresses we know are good, addresses we know are bad, and then addresses we don’t know about.
Good addresses get mailed. Bad addresses get dumped. The challenging bit is what do we do with the unknown addresses? That’s when we start looking at other data the client may have. Purchases? Website visits? What do we have to work with and what else do we know about the people behind the addresses. Once we’ve looked at the data we design a program to take the addresses we don’t know about and drop them into either the good or the bad bucket. How we do that really depends on the specifics of the company, their program and their data. But we’ve had good success overall.
There’s been a lot of discussion on hygiene this week, after Mailchimp published a blog post looking at the value of inactive subscribers. They found something that I don’t find very surprising, based on my observations across hundreds of clients over the years.
[T]he data backs it up: An inactive subscriber is a better customer than a non-subscriber.
This actually came up at the MessageSystems Insight Conference in Monterey last year. One of the MailChimp guys asked me about pruning during my talk. Afterwards, we had a conversation at dinner. He said MailChimp was looking at changing their recommendations and asked my opinion on the blanket ‘prune your subscribers’ recommendation. Specifically he wanted to know what I thought about it in the case of retailers.
I told him I’d never held on to the idea that a company should just prune subscribers from a list in the absence of delivery problems. If the users are not hurting delivery, there really isn’t a reason to drop them. Remember, ISPs measure engagement differently than marketers, so they may be engaging with the mail in ways senders can’t track.
I do think there is some point where a sender should give up mailing, but that is really going to depend on the sender and their process. Newsletters vs. advertising vs. retail vs. e-commerce have different customer and product lifespans.
What you’re selling matters, too. Cars have a different lifespan than light bulbs or toothpaste. If you’re selling something with a short interval and a customer hasn’t purchased in 4 or 5 or 6 cycles, maybe you should decide this isn’t a customer any longer. But if you’re selling cars someone may wait 4 or 5 years between purchases.
There’s also the data you started with. How did you initially acquire the customer? That also impacts how an address affects your deliverability. Some subscription pathways are going to be riskier and should be taken off your list sooner than others.
As with everything in deliverability, there is no one answer to when to stop mailing an address. It really does all depend on the specifics.
I’m glad MC did the work. I didn’t know our conversation over drinks was going to lead to such interesting data.
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