Archive for the ‘Email List Management’ Category
Posted by Rob Ropars on August 26th, 2011
We’ve all heard that if you’re in marketing, in particular email marketing, you should constantly be testing to maximize results. The most common test mentioned is the ubiquitous “A/B” split test, meaning a 50/50 list split to test one variable against another (graphics, copy, offer, layout, list, time of day, day of week, etc.).
But is an A/B test all you can or should do? If you have only a few thousand or fewer emails to work with, an A/B test may be all you can do to ensure statistically reliable results. However, if your list is too small, an A/B test might not make any sense. For example, if you only have a few hundred email addresses, splitting and conducting one test will literally tell you nothing (statistically) other than directionally relevant information. Instead you may need to try to replicate the test over time, to aggregate the results and to analyze your collective data over a longer period.
The first consideration is to quantify how many email addresses you need to test to ensure you have a representative sample and more importantly, to ensure the results are reliable. There is a lot of math and science behind this topic, and fortunately a lot of math/science/statistics sites have free online tools such as this one.
You must set up the test(s) correctly (with sufficient sample sizes and assumed response rates) on the front end to ensure that results on the back end are reliable, meaning with a confidence level that you’re comfortable with (we recommend a 95% confidence level if it’s possible). Again, there are resources online to assist such as this one. The key is to avoid the common mistake of merely looking at results and assuming winners/losers based on seemingly different response rates.
Before testing, you have to identify the goal or the question you’re trying to answer. We recommend that you actually write these down and then, as briefly and concisely as possible, describe the various yardsticks you will use to determine your winner. As form follows function, the goals/objectives of the test coupled with the means to measure results should help drive copy, graphics, and/or layout to ensure the messages are properly structured and focused on whatever question you’re trying to answer..
Let’s say your goal is a higher click rate and after an A/B test you find “A” has a 2.7% CTR and “B” has 2.85%. It is a common mistake to use subtraction and declare that “B” was the winner or that “B” was only 0.15% higher and that could lead you down the path of thinking it wasn’t a significant result (i.e. a virtual “tie”). Or maybe you routinely just pick the higher percentage as the winner and run with that. Using proper percent increase/decrease calculations, we find that this is actually a 5.56% increase from “A” to “B.”
That however may or may not be statistically significant, but as you can see it’s a much larger increase than originally assumed. In order to determine if the results are statistically significant, use one of the calculators, plug in each version’s list size and the click percentage (or open percentage, or conversion rate, etc. depending on the key metric you’re analyzing) and it will instantly tell you whether this difference is enough to be reliable (with a 95% confidence level).
In this example, let’s pretend I sent “A” and “B” to a random 2,000 people each. The calculations indicate that this would not be enough of a difference to be statistically reliable. In fact, the “B” cell’s click rate would have to have been at least 3.81% in order for the difference to be reliably significant. However, if you didn’t analyze the results properly you wouldn’t know this.
The other way to ensure you’re maximizing your results is to avoid doing a full scale A/B test. If your database for an email marketing campaign is large enough (again calculate minimum sample size), you can do a different kind of split test. First, split your list 10%/90% (ensuring it’s random). Then split the 10% group in half so you have two small splits and the remaining 90%.
Deploy your test to the 10% splits, give as much time as possible for activity to occur (twenty-four hours if possible), analyze the results and then deploy the winner to the remaining 90%. That way you’ve done your best to maximize the campaign’s results without going “all in” on a typical full file A/B split.
As with gambling, learn the rules, do the math, analyze the data and place your bets. Do it right, and the odds will swing in your favor.
Posted by Dave McCue on June 29th, 2011
While there are a myriad of advanced email marketing techniques available, the fact remains that for some marketers it’s enough of a struggle simply getting messages out the door in time without adding any more layers of complexity to the process. If you find yourself in this camp, remember that there are some basic strategic techniques that can help you move “beyond the basics” without putting your deadlines at risk. One tried-and-true technique is the application of filters to your mailing list(s).
Here are 5 effective ways to use list filters:
- Engagement
Filtering based on recipients who rendered and/or clicked on a message(s) can be very useful. This demonstrated interest in a topic/product/offer provides valuable insight into what these recipients are looking for. Use this knowledge to deliver messages with related content, complementary products or similar offers. Or, use this as a suppression filter for an “inactive re-send” campaign that sends the same message to recipients who did not engage with the original.
- Non-activity
This filter is useful not only for the “inactive re-send” approach mentioned above, but to identify recipients who have not engaged with messages over a period of time (12 months, for example). Some email marketers actively reach out to this group of recipients to learn if there is something specific they would like to see on future emails. Others simply use this filter to exclude unengaged recipients, as continuing to include them on mailings only serves to drive down response rates and incur message volume that could be put to better use.
- Clicked a specific link
More definitive than a filter based on general click activity, this filtering technique is valuable when conducting follow-up to a message with several different calls-to-action.
- ZIP Code radius
If you’re collecting ZIP Code as part of your subscriber opt-in process, a radius filter is a great way to target your messages. If your organization has multiple locations, promote the location nearest your subscribers. For special offers, you can factor in travel distance and sweeten your offer accordingly (e.g., 15% off for recipients within 10 miles, 30% off within 20 miles, etc.)
- Date of opt-in
The date that a subscriber signed up to receive your emails can be an effective filter when setting multi-touch Welcome campaigns (e.g., 30/60/90 days out). You may also want to exclude recent subscribers from the sort of “inactive” segmentation mentioned above, or from only receiving the tail-end of an ongoing series of messages (e.g., “Message 9 of 9″).
The filtering techniques mentioned here are only a sampling of the way list filters can be used to make your email messages more relevant and more productive, and since filters can be used on any number of deployments, they only require an initial setup before becoming part of your normal processes.
Posted by Bill Leming on March 14th, 2011
Over the past several months we’ve fielded a number of questions from clients regarding “who” among their customer base they should be communicating with via email. The question that is rarely asked but should be asked more often is “Are there individuals that we should NOT be including in our standard email message plans?”
The answer will vary based upon your industry, business model, and other factors. A good starting point is to analyze all of the various customer segments within a database with whom you could be communicating via email, then identify if there are specific segments that you should intentionally exclude from your email communications. Typically, you’ll find at least the following three groups of customers that you may want to consider excluding from your standard email program or, at a minimum, treating specially.
The first is the “Elite.” These consist of the top 1% that represent an inordinately high percentage of the annual revenues and/or profits. Like the 80/20 rule, these customers may control as much as 10-20% of your annual revenues/profits. Should you be writing them, calling them, or taking them to lunch? Don’t they deserve that? If email is their preferred medium of communication, those emails demand the utmost attention from you regarding their specific needs, interests, circumstances and personal preferences. Consider sending their email from the CEO or whomever within your organization owns the relationship. These are not the type of recipients you should be including on any general, broadcast-style mailings.
The same may also be true for another group consisting of Board members, powerful friends of the organization and their associated households/businesses. I’d strongly encourage email marketers to exclude this group from solicitation, particularly at the outset of any new email communication initiative and until such time as you’re absolutely certain that the program is free of any bugs or potential miscommunications. If and when these customers are added back into the email mix, be sure the communications sent their way include some indication that you know who they are and appreciate their contributions.
The third group you may want to consider excluding consists of what may be referred to as “Eccentrics.” These are the customers that call your help desk an inordinate number of times with inane questions that tie up your resources. Once identified, the “eccentrics” are the group that you may want to individually delete from your standard emails.
When the email marketing conversation turns toward segmentation, a key point that we always try to stress is the idea that emails are not sent to “lists,” they are sent to “people.” Keep this in mind as a reminder that some people—for a variety of reasons—may need to be treated a little bit differently when it comes to your email marketing. In some cases, like those mentioned here, that may mean approaching them with extreme caution and/or excluding them entirely.
Posted by Nic Winters on August 27th, 2010
One advantage of email marketing over many other forms of marketing has always been the ability to track activity and clearly see the actual results related to your messaging. However, this leads to large amounts of information and marketers often get lost in the mountains of data. When taking on this ever-growing mass of information, it is important to identify trends and often your best bet is to look into summary-type reports that allow you to view how results have played out over time.
From time to time we find that three reports within the SubscriberMail interface that clients occasionally tend to underutilize are Subscriber Summary, Subscriber Details, and Subscriber Timeline. These reports provide a wealth of information related to the growth of your subscriber list over time.
Subscriber Summary: shows how many people have been added to your account via opt-in code on your website(s) along with the unsubscribes, bounces, and double opt-ins (if applicable) for a given date range broken out month-by-month
Subscriber Details: shows the details related to each individual that has been added to your account via opt-in code on your website(s) – including the list name they were added to and the webpage on which the opt-in form is located
Subscriber Timeline: allows clients to view day-by-day or month-by-month charts of the gain and loss of subscribers from their lists
Utilizing these reports can provide clients with information related to their opt-in lists and effectively evaluate their efforts to drive list growth.
Contact the SubscriberMail Client Support team at support@subscribermail.com for more information regarding how you can utilize the full SubscriberMail reporting suite.
Posted by Matt Rotroff on April 23rd, 2010
No matter how deep we end up diving into the technical facets of email delivery, it’s important we don’t forget the simple rules we started with. One of the most important of those rules is keeping your email list clean. Keeping a clean email list increases your email delivery rate and inbox placement more than you may think.
Staying current - Keep track of when you attain email opt-ins and how active those opt-ins are. Having an email address or group of addresses that are out-dated can have you unknowingly sending to old addresses that have been converted to spam traps. If you don’t remember how long ago nighthawk@flash.net signed up to receive email, he probably won’t remember either, which leads to a greater likelihood that it will become a spam complaint. Spam complaints and spam traps are two major email marketing issues that can be partially avoided by making sure your email lists are current and contain only active email subscribers.
Unknown users – Another reason to continually scrub your email list, especially of hard bounces, is to clear out any unknown users (bad addresses). If there are too many invalid email addresses in a single mailing, there is a risk of getting temporarily blocked at a recipient’s email server. That means a good amount of the valid email addresses may not be getting your message because of a few too many bad apples.
With the right tools and a little bit of persistence, keeping your email lists well groomed can become an easy and rewarding task. Although there are areas like authentication and filtering that are more complex, the basic building block of list hygiene is the foundation of strong email delivery.
We’ve all heard that if you’re in marketing, in particular email marketing, you should constantly be testing to maximize results. The most common test mentioned is the ubiquitous “A/B” split test, meaning a 50/50 list split to test one variable against another (graphics, copy, offer, layout, list, time of day, day of week, etc.).
