Thoughts on Data Hygiene

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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Data is the key to deliverability

Last week I had the pleasure of speaking to the Sendgrid Customer Advisory Board about email and deliverability. As usually happens when I give talks, I learned a bunch of new things that I’m now integrating into my mental model of email.
One thing that bubbled up to take over a lot of my thought processes is how important data collection and data maintenance is to deliverability. In fact, I’m reaching the conclusion that the vast majority of deliverability problems stem from data issues. How data is collected, how data is managed, how data is maintained all impact how well email is delivered.
Collecting Data
There are many pathways used to collect data for email: online purchases, in-store purchases, signups on websites, registration cards, trade shows, fishbowl drops, purchases, co-reg… the list goes on and on. In today’s world there is a big push to make data collection as frictionless as possible. Making collection processes frictionless (or low friction) often means limiting data checking and correction. In email this can result in mail going to people who never signed up. Filters are actually really good at identifying mail streams going to the wrong people.
The end result of poor data collection processes is poor delivery.
There are lots of way to collect data that incorporates some level of data checking and verifying the customer’s identity. There are ways to do this without adding any friction, even. About 8 years ago I was working with a major retailer that was dealing with a SBL listing due to bad addresses in their store signup program. What they ended up implementing was tagged coupons emailed to the user. When the user went to the store to redeem the coupons, the email address was confirmed as associated with the account. We took what the customers were doing anyway, and turned it into a way to do closed loop confirmation of their email address.
Managing Data
Data management is a major challenge for lots of senders. Data gets pulled out of the database of record and then put into silos for different marketing efforts. If the data flow isn’t managed well, the different streams can have different bounce or activity data. In a worst case scenario, bad addressees like spamtraps, can be reactivated and lead to blocking.
This isn’t theoretical. Last year I worked with a major political group that was dealing with a SBL issue directly related to poor data management. Multiple databases were used to store data and there was no central database. Because of this, unsubscribed and inactivated addresses were reactivated. This included a set of data that was inactivated to deal with a previous SBL listing. Eventually, spamtraps were mailed again and they were blocked. Working with the client data team, we clarified and improved the data flow so that inactive addresses could not get accidentally or unknowingly reactivated.
Maintaining Data
A dozen years ago few companies needed to think about any data maintenance processes other than “it bounces and we remove it.” Most mailbox accounts were tied into dialup or broadband accounts. Accounts lasted until the user stopped paying and then mail started bouncing. Additionally, mailbox accounts often had small limits on how much data they could hold. My first ISP account was limited to 10MB, and that included anything I published on my website. I would archive mail monthly to keep mail from bouncing due to a full mailbox.
But that’s not how email works today. Many people have migrated to free webmail providers for email. This means they can create (and abandon) addresses at any time. Free webmail providers have their own rules for bouncing mail, but generally accounts last for months or even years after the user has stopped logging into them. With the advent of multi gigabyte storage limits, accounts almost never fill up.
These days, companies need to address what they’re going to do with data if there’s no interaction with the recipient in a certain time period. Otherwise, bad data just keeps accumulating and lowering deliverability.
Deliverability is all about the data. Good data collection and good data management and good data maintenance results in good email delivery. Doing the wrong thing with data leads to delivery problems.
 
 

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It's not about the spamtraps

I’ve talked about spamtraps in the past but they keep coming up in so many different discussions I have with people about delivery that I feel the need to write another blog post about them.
Spamtraps are …
… addresses that did not or could not sign up to receive mail from a sender.
… often mistakenly entered into signup forms (typos or people who don’t know their email addresses).
… often found on older lists.
… sometimes scraped off websites and sold by list brokers.
… sometimes caused by terrible bounce management.
… only a symptom …

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Organizational security and doxxing

The security risks of organizational doxxing. 
These are risks every email marketer needs to understand. As collectors of data they are a major target for hackers and other bad people. Even worse, many marketers don’t collect valid data and risk implicating the wrong people if their data is ever stolen. I have repeatedly talked about incidents where people get mail not intended for them. I’ve talked about this before, in a number of posts talking about misdirected email. Consumerist, as well, has documented many incidents of companies mailing the wrong person with PII. Many of these stories end with the company not allowing the recipient to remove the address on the account because the user can’t prove they own the account.
I generally focus on the benefits to the company to verify addresses. There are definite deliverability advantages to making sure email address belongs to the account owner. But there’s also the PR benefits of not revealing PII attached to the wrong email address. With Ashley Madison nearly every article mentioned that the email address was never confirmed. But how many other companies don’t verify email addresses and risk losing personally damaging data belonging to non customers.
Data verification is so important. So very, very important. We’ve gone beyond the point where any big sender should just believe that the addresses users give them are accurate. They need to do it for their own business reasons and they need to do it to prevent incorrect PII from being leaked and shared.

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