Banish Invalid Addresses to Boost Deliverability
A look at four sources of bad addresses, and how to deal with each.
A look at four sources of bad addresses, and how to deal with each.
One of the best ways to boost your sender reputation, and ultimately your deliverability, is to reduce invalid addresses. This strategy has gotten lost in recent conversation about feedback loops, spam complaints, and authentication, but it’s essential for good hygiene, and your sender reputation rests heavily on your list-hygiene practices.
AOL recently notified bulk senders via its official Postmaster blog that it’s “refining” how it factors invalid-address numbers in calculating sender reputation and warned those with relatively high invalids would face more delivery problems.
Some commenters roasted AOL for not specifying how many invalid addresses would trigger more delivery problems, but that misses the point. As I wrote here recently, benchmarks themselves are relatively meaningless except to reveal trends in your own delivery statistics.
Instead of focusing on a specific number, develop tactics to reduce your invalids. Suppose your last delivery report says three percent of your mailing list bounced for invalid addresses. That doesn’t automatically mean you’ll be blocked. It means, however, you have room to reduce that number.
Four Sources of Invalid Addresses
Ordinarily, using double opt-in should keep bad addresses out of your database, because an e-mail to an invalid address wouldn’t get delivered, and the request wouldn’t get confirmed. It does nothing to remove addresses that were valid at opt-in but then go invalid later on. It also won’t bring back honest users with fat-finger syndrome.
Many bulk senders use e-mail sending software that automatically removes invalid addresses from future mailings after receiving and processing bounce reports. If you don’t do this, you compound the problem every time you mail to that address. Eventually, you will be blocked.
But, even this doesn’t solve the problem if you don’t correct it at the database level. This is where the process breaks down most often. Senders manually upload a mailing list from their internal databases into their e-mail applications for a one-time mailing.
The application will flag and remove invalid addresses, but it doesn’t change the information in the database. If the sender doesn’t remove those addresses in the database, they will get uploaded again and again and make you ever more vulnerable to blocking.
If this sounds like something you’re doing, review your data policies and suppression lists before you send again.
Resolving Invalid Addresses
Start by figuring out which of the four conditions listed above account for the largest number of invalids:
1. Invalid addresses from closed accounts:
Determine how long the address has been on your list before it began bouncing. Six months or longer? Most likely, the account got shut down. You can’t do much about it beyond removing, but make sure you tell subscribers clearly, in each e-mail, how to change an e-mail address or update a profile. Ensure your unsubscribe procedure is working, with the link easy to find in the e-mail.
Maybe you see large blocks of addresses from the same domain become invalid. This indicates an ISP-level change. Maybe it retired some domains or had its customers absorbed by another ISP. Generally, you can’t just update those addresses with the new domain, because the ISP might require customers to create new addresses.
2. Bad data from affiliates or marketing partners:
If the addresses are recent, as they should be if you process bounces correctly, look for problems in how you acquired them. Check the source codes for your invalid addresses. Did they come from an affiliate or a marketing partner that’s sending you bad data?
If so, talk to the partners involved and either insist they clean their lists before sending them over or eliminate them as partners.
3. Accidental typos at opt-in:
Look for patterns in the domains of your invalid addresses, such as misspelled versions of popular domains (alo.com; yahooooo.com). Three tactics can prevent this kind of bad data from infiltrating your mailing list:
4. Deliberate misspellings:
This could explain large batches of new addresses that have no other apparent flaws. It happens when a marketer offers an incentive to opt in or register at a Web site. The subscribers want the incentive — sweepstakes entry, free downloads, instant discounts — but not the e-mail content, so they hand over a fake address.
Add or clarify language on the opt-in page that reminds users you’ll e-mail the incentive, or redemption information, to the address they give instead of providing it to them as soon as they submit their data.
In both cases of misspellings, confirmed or double opt-in will prevent that bad data from joining your list, but it won’t help you retain subscribers who otherwise are good customers.
Tightening your opt-in procedures, adding error-checking, and policing your marketing partners takes time to set up, but it will reward you with a cleaner list and, ultimately, a stronger program.
Until next time, keep on deliverin’!