Recycled spamtraps

Spamtraps strike fear into the heart of senders. They’ve turned into this monster metric that can make or break a marketing program. They’ve become a measure and a goal and I think some senders put way too much emphasis on spamtraps instead of worrying about their overall data accuracy.

Recently I got a question from a client about the chances that any address they were currently mailing would turn into a recycled spamtrap. Assuming both a well behaved outbound mail server and a well behaved spamtrap maintainer the answer is never. Well behaved spamtrap maintainers will reject every email sent to one of their spamtrap feeds for 6 – 12 months. Some reject for longer. Well behaved mail servers will remove addresses that consistently bounce and never deliver.

Of course, not everyone is well behaved. There are maintainers who don’t actively reject mail, they simply pull the domain out of DNS for years and then start accepting mail. Well behaved mail servers can cope with this, they create a fake bounce when the get NXDomain for an address and eventually remove the address from future mailings. There have been cases in the past where spamtrap maintainers purchase expired domains and turn them into spamtraps immediately. No amount of good behaviour on the part of the sender will cope with this situation.

On the flip side some MTAs never correctly handle any undeliverable address when the reason is anything other than a direct SMTP response. Generally these are built on the open source MTAs by people who don’t realise there are mail failures outside of SMTP failures.

There are three general cases where recycled spamtraps will show up on a list.

  1. A list has been improperly bounce handled.
  2. An address has not been mailed for more than a year.
  3. Someone signs up an address that’s a recycled spamtrap (same as how a pristine trap will get added to a list)

ESPs have to worry about recycled spamtraps in another common case. A new customer brings over a list and decides to retry addresses that their previous ESP marked as bounced. (It happens. Regularly.)

Recycled addresses are a sign that there is a problem with the long term hygiene of a list. As with any spamtrap, they’re a sign of problems with data collection and maintenance. The traps aren’t the problem, they’re just a symptom. Fix the underlying issue with data maintenance and traps cease to be an actual issue.

Related Posts

Incentivizing incites fraud

There are few address acquisition processes that make me cringe as badly as incentivized point of sale collection. Companies have tried many different ways to incentivize address collection at the point of sale. Some offer the benefit to the shopper, like offering discounts if they supply an email address. Some offer the benefits to the employee. Some offer punishments to the employee if they don’t collect addresses from a certain percentage of customers.
All of these types of incentive programs are problematic for email collection.
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On the shopper side, if they want mail from a retailer, they’ll give an address simply because they want that mail.  In fact, asking for an address without offering any incentive is way more likely to get their real address. If they don’t want mail but there is a financial incentive, they’re likely to give a made up address. Sometimes it will be deliverable, but belong to another person. Sometimes it will be undeliverable. And sometimes it will be a spamtrap. One of my delivery colleagues occasionally shares addresses she’s found in customer lists over on her FB page. It’s mostly fun stuff like “dont@wantyourmail.com” and “notonyour@life.com” and many addresses consisting of NSFW type words.
On the employee side there can also be abuses. Retailers have tried to tie employee evaluations, raises and promotions to the number of email addresses collected. Other retailers will actively demote or fire employees who don’t collect a certain number of addresses. In either case, the progression is the same. Employees know that most customers don’t want the mail, and they feel bad asking. But they’re expected to ask, so they do. But they don’t push, so they don’t get enough addresses. Eventually, to protect their jobs, they start putting in addresses they make up.
Either way, incentivizing point of sale collection of information leads to fraud. In a case I read about in the NY Times, it can lead to fraud much more serious than a little spam. In fact, Wells Fargo employees committed bank fraud because of the incentives related to selling additional banking products at the teller.

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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.

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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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