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 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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Data Cleansing

According to Ken, Outward Media has productized a database of 300,000,000 email addresses that should never be mailed.

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Data Cleansing part 2

In an effort to get a blog post out yesterday before yet another doctor’s appointment I did not do nearly enough research on the company I mentioned selling list cleansing data. As Al correctly pointed out in the comments they are currently listed on the SBL. And when I actually did the research I should have done it was clear this company has a long term history of sending unsolicited email.
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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