5 answers you need before mailing old addresses.

From the archives: Mailing old addresses: 5 questions to ask first
James asked the question on twitter:

If you haven’t mailed an address in 5-10 yrs, would you include it in a re-engagement mail?

A number of people responded that addresses that old should not be mailed. I think the answer is more complex than can be handled in 140 characters.
Five to ten years is a very long time. Think about what you were doing 10 years ago. It’s easy right now, 10 years ago as a nation we were still reeling from the September 11 attacks. On a more personal note, Steve and I were just making the decision to start Word to the Wise. But what about 5 years ago? I can’t remember what we were doing or what our business goals and limitations were.
If you’re going to mail addresses that were collected 5 or 10 years ago, you must give some thought to a number of questions.

1. How has my target market changed in the last 5 – 10 years? How likely is it that customers from then would be interested in my products now?
People grow and change. As we move through different life stages, we have different needs and shop for different products. When thinking about whether or not to send mail to those old addresses, think about customer demographics. Is someone who wanted your product in the past also going to want your product now? What life stages are you targeting?
If you can honestly say that your product has a 10+ year target market, then mailing old customers may be acceptable. But if you focus on a narrow demographic it’s possible that your former customers are no longer interested in anything you have to offer, no matter how compelling the copy.
2. What do I have to offer a customer from 5 – 10 years ago? Is my current product line likely to interest them?
Just as people grow and change, businesses grow and change as well. When we first started Word to the Wise a lot of my consulting was directed at senders who were having blocklist problems and often didn’t have permission to send the mail they were sending. We didn’t have to talk about bulk folders, as most major ISPs hadn’t adopted the bulk folder yet. We didn’t have to talk about Feedback loops or “this is spam” buttons because such things didn’t exist yet. They primarily wanted to know how I could help them get and stay off the RBL or SBL.  In contrast, most of my current customers are opt-in senders who want information about how to engage users and get a better responses to their email.
Sure, old customers may be interested in new products and re-establishing contact with an old vendor. Others may have no interest at all. Some small percentage having an interest in your product isn’t sufficient. You need to be sure that a large percentage of recipients are going to want your new product.
3. How long does my product last? Are older customers still interacting with my product? Or have they forgotten I even existed?
There are pieces of software I’m using from 5 or 10 years ago. I’d be fine with a re-engagement email letting me know about other offers they have. But there are also bits of software I downloaded, tried and promptly forgot. I’d be annoyed if the vendor tried to email me. That really nifty pepper mill we bought 6 years ago? Love to hear from them about new stuff. That random kitchen gadget gathering dust in the back of a drawer? Not so much.
So much of making decisions about email is gauging how receptive recipients are to your message. When trying to decide to email very old customers, it’s important to understand your previous customer base.
4. What value am I bringing to the recipient? Do I have something new to offer? Can I push a new product or new launch?
The core of email deliverability is sending mail that your recipients want to receive. If you’re contacting recipients that haven’t heard from you in years, you need to put extra effort into making the email relevant for their lives. One of the ways you can do that is to share your excitement with a new product line, or a re-brand of your company.
Another way to make the email relevant is to make the email informative. Talk to the recipient about how you’ve changed in the intervening years and how your products can help the recipient. Your old customers are more likely to accept your intrusion if you have useful information for them  with your old customers
5. Where did I get these email addresses? Do I have a good audit trail for them?
This is where we get to those pesky details. Do you actually know where the addresses came from? Do you have even a partial audit trail. Can you tell what product was bought by the address? Do you know when the address was entered into your database? Do you even know if these are addresses of customers or not?
In my experience, most companies don’t have good audit trails for older addresses. They don’t know where the addresses came from. They don’t know if they’re actual customers. These are the things that cause re-engagement to fail totally.
You should NEVER mail old addresses unless you can identify where the address came from and the specific purchase that address is associated with. If you don’t have that data, then your delivery is going to be awful. You can only aspire to get into the bulk folder. More likely, you’re going to end up with mail blocked at many ISPs.
For the sake of argument, let’s say you do have that data. Someone at your company set up a database that captured everything you may need to mail old customers.
It’s not enough to have the audit data, you should take a deep dive into the data itself. How many of the addresses are at any of the dozens of domains that have retired in the last 10 years? How many are @home.com, @attbi.com, homestead.com or mcimail.com? None of these domains exist any longer. How many are @compuserv.com, @prodigy.net or earthlink.net? These are domains that were popular long ago, but are no longer in wide use. It’s unlikely your customer still has that address.
Still thinking about mailing that list, because it’s mostly @aol.com or @hotmail.com addresses? That may still risk your delivery. Old addresses at major domains are sometimes turned into spamtraps and mailing these addresses may result in blocking. Even running the addresses through one of the ‘list cleaning’ vendors may not protect you from delivery problems related to old addresses.
Statistics show that 30% of email addresses are abandoned by their owners in a year. That means that even 5 years back only about 20% of those addresses are still in use by your customers. The others are abandoned, turned into spamtraps or just won’t deliver. If 80% of your list goes into a black hole, how much does each sale have to be to make it profitable to contact those old customers?
Each question should take an average business quite a bit of time to answer. The first 3 questions are about the intersection between you and your customer. They’re about you, the business, honestly evaluating your product (then and now), your target market (then and now) and the chance that you will meet their needs now as you met them then. The fourth question is about what you want to tell your old customers. But none of those questions are even worth asking unless you know you have a database worth sending to. And even if you do, will the ROI on a mailing be enough to justify the expense to put together an effective re-engagement campaign?
 

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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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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.
listshoppingcart
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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Dueling data

One of the things I miss about being in science is the regular discussions (sometimes heated) about data and experimental results. To be fair, I get some of that when talking about email stuff with Steve. We each have some strong view points and aren’t afraid to share them with each other and with other people. In fact, one of the things we hear most when meeting folks for the first time is, “I love it when you two disagree with each other on that mailing list!” Both of us have engineering and science backgrounds, so we can argue in that vein.
ThatsFunny
One of the challenges of seemingly contradictory data is figuring out why it seems to disagree. Of course, in science the first step is always to look at your experimental design and data collection. Did I do the experiment right? (Do it again. Always do it again.) Did I record the data correctly? Is the design right? So what did I do differently from what you did? For instance, at one of my labs we discovered that mixing a reagent in plastic tubes created a different outcome from mixing the reagent in glass vials. So many variables that you don’t even think of being variables that affect the outcome of an experiment.

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