Thoughts on Data Hygiene

zombieemailOne 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.

Related Posts

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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Zombie email: Part 1

Zombie email addresses: those email addresses that never really die, eat your brains and destroy your email delivery. To understand zombie addresses and why they’re just now becoming a problem, we really need to understand some of the history of email addresses.
In the early days of the net, people got an email address usually associated directly with their access to the Internet. Many of them ended with .edu or .gov. I even had one that ended in .BITNET for a while. The first ISPs followed this convention. Users signed up for an account at a local dialup and were assigned an email address, and that was their email address. It wasn’t until the late 1990’s where there was widespread access to multiple email addresses.
What this means is that when people left a job, or canceled their Internet access their email address went away. Addresses that were abandoned would, after a short period of time, start bouncing back with user unknown, giving everyone the opportunity to stop mailing that account.
Even with the advent of multiple addresses for a single account and the easy availability of free addresses from places like Hotmail addresses that had been abandoned would still bounce off a list. Why? Because accounts had limited storage. My first dialup account had, I think, 10MB of space. It may have been as much as 20MB, but it wasn’t very much. Accounts receiving a lot of mail that weren’t checked frequently would fill up and start bouncing mail. Senders would be able to remove abandoned accounts because they were full.
Tomorrow we’ll talk about two things happened in the early 2000’s that changed email and led to the rise of zombie email.
Zombie Email: Part 2
Zombie Email: Part 3
Zombie Apocalypse

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Zombie email: Part 3

Last week, in Zombie email: part 1 and part 2 I talked a little about the history of email addresses and how changes in the ISP industry in the early to mid 2000’s brought about the rise of zombie email addresses. Today we’ll look at the effect zombie addresses have on email stats and why ISPs are starting to monitor zombie addresses.
A zombie address, despite the fervent belief of some email marketers, doesn’t come back to life. The person who initially registered that address has decided to stop using that email address.  The defining factor of a zombie address is that there isn’t now and won’t be anyone in the future reading email sent to that address. There is no human there to read or react to any email sent to that address.
A zombie address does not represent an actual recipient, they’re just remnants of a recipient that once was present.
Having a list containing any significant number of zombie addresses can throw off metrics enough to mislead a sender about the effectiveness of their email marketing program. Sometimes, the zombie addresses make the metrics look worse, sometimes they make metrics look better. In either case, the metrics don’t accurately represent the performance of a marketing program.
Zombie email addresses do bulk out a mailing list, making lists look bigger. They’re not real addresses, so they don’t reflect quality, but they do impress marketers that think bigger is always better. But, in reality, you may as well add thousands of addresses at non-existent domains for the real value these addresses bring to your list.
Zombie email addresses on a list depresses any metric that use “number of emails sent” or “number of emails accepted” as a denominator.  If 10% of a list is zombie addresses, then an open rate reported as 15% will actually be an open rate of 16.7%. The more zombie addresses on a list, the more the statistics will be depressed.
In addition to having lower open rates, lists with more zombie addresses also have a lower complaint rate. In fact, in the recent past spammers have padded their lists with zombie addresses as a way to artificially lower their complaint rates.
Spammers using addresses created just to bulk up the denominator and lower complaint rates have led ISPs to start monitoring the types of addresses on a particular list. I first heard about ISPs looking at recipient profiles at a meeting in 2006, so it is not, in any way, a new technique for ISPs. What is new is the number of zombie addresses on legitimate, well maintained lists, and the fact that they are present in high enough volume to affect reputation and delivery.
ISPs use zombie addresses to monitor the reputation of a sender because it is a more accurate way to measure what the recipients think about an email and that sender. Senders ignore zombie addresses because they make some stats look bigger (total list size) and better (lower complaint rates). Many senders also believe that addresses come back to life, despite all evidence to the contrary, and will not purge an address for any reason other than it bounces. They’d rather live with inaccurate and misleading metrics than removing non-performing addresses.
Tomorrow, in the final post of this series, we’ll examine how senders can identify potential zombie addresses and what steps they can take protect themselves from the negative reputation hit from zombie addresses. (Zombie Apocalypse)

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