Using "Stickiness" to Test New Email Series Effectiveness
R3 for Email I guardianmarketing.substack.com I ExperienceR3.com
Take this scenario ... You've written a new email series for your list. Your goal? a greater level of longer term engagement and of course, more sales.
You make the new series and start testing it.
Here are some results.
Do these open rates look good to you?
(This is sent to a segment of about 2000 subscribers)
Email 1 - 27.83%
Email 2 - 17.82%
Email 3 - 19.11%
Email 4 - 19.67%
Email 5 - 17.78%
Email 6 - 16.59%
Email 7 - 17.85%
Email 8 - 21.50%
Most people would look at that data and immediately come up with several conclusions:
Those open rates are way too low!
should have come up with better subject lines
the emails are probably too long
your list is not interested in this thing
your copy is bad
you haven't given people a good enough reason to read
Blah blah blah. Make the emails shorter, make more compelling subject lines, make stronger calls to action.
All the typical "assessment" that a email marketer or copywriter may make in the dark looking at data like that.
I look at that and think ...
Excellent.
Of course, what I'm looking for and what most people are looking for is different.
If you currently have an email list with a business and you're wanting a much stronger longer term ROI on that email list, if you don't want to do the 'ole' churn-and-burn (where the only move you have is hitting people upside the head with offers over and over, and people tend to drop off after a few weeks), if you for example are wanting to establish R3 for Email ...
If you are trying to figure out the right email sequence to nurture the right people on your email list ...
I've got a perspective I believe will serve you well.
As someone who goes into businesses to help them build better email strategies, broadly speaking there are two different dynamics I face.
The business has no email to speak of at all. They might have done a little lead gen here and there, but for the most part we can consider them starting from scratch.
The business has an email list, actively generates leads, and emails on at least a monthly basis.
The second is what I most often work with and where the dynamic I'm about to show you really comes into play. The first, being a "starting from scratch" type scenario is really a 0-1 scenario, which basically means anything done is infinitely effective and can get you to the second scenario.
For those in that second scenario,
What most people don't realize (outside marketers coming in, the business owners themselves), is that a list like that - especially where a lot of experimentation has happened - usually has a much wider range of interest and intent in the audience than you realize.
To put it succinctly:
If you've been building a list and emailing that list for some time, using all manner of different mechanisms to get people on that list and sell them,
There's a high likelihood your list is a random mix of good fit AND not good fit.
(As opposed to a tight, sculpted list of mostly just good fit people)
If you're looking to build out R3 for Email1, that means figuring out The Filter2 which is going to ultimately bring you a highly active email list of people who are good fits (now and later).
If you aren't specifically using R3 for Email, you still need a way to figure out the people on your list who are a good fit, to isolate out the people who shouldn't be there so you stop wasting resources on them, and to then use that information to get better people coming in the front door to begin with.
After all, if you're speaking to everyone (good and bad fits), then you're speaking to no one. We really* want to spend our resources and system design speaking to the good fit people who are most likely to buy.
So as you can imagine,
There's a messy transition of testing and figuring out the right way to speak to the right people to affect the ideal outcome you want (in the case of R33, it's long term raving fans and inevitable growth).
You need to come up with a theory of what your ideal person will respond to,
And then test.
(Side note, there is no perfect in marketing. There's only hypothesis, testing, and data. The best results only come from iteration on the data)
So, back to the example at the beginning.
When testing out a new email series, it's often people's inclination to try to get as many people to open and read those emails as possible. One of the reasons the open rates appear so low on that series, is because I intentionally avoided trying to get as many people to read those emails as possible.
AS a counter example, with a polished system that has a high degree of resonance, with lead gen that connects on the right level and brings the right people in, for an email series like we're talking about it's not uncommon to see that first email at 80%, and then that last email still above 70%.
So why would I like an email series that's giving me 18% opens?
You might think I'm insane.
But ask yourself,
What are we really trying to do here? Are we trying to take this random collection of good/bad fit people and trying to make as many of them behave the way we want to as possible?
Or
Are we trying to figure the right way to speak to the right people so that they remain engaged?
When you are trying to figure out how to speak to the best people on your list, you don't want to warp your data by also trying to manipulate people into paying attention.
This is making the mistake of peaks and valleys.
The same kind of mistake that happens when you overly emotionally compel someone to buy. It warps the data.
If I break out all the "tricks" to get more people to open an email in the hopes that as many people as possible on my list are going to read and that means more data, it's going to actually break the real data I'm after.
The real value in testing a new email series like this isn't in getting more from your current email list -
It's actually figuring out the stickiness of the ideas with your ideal audience.
Opens, Clicks, Replies are all irrelevant on their own, and in this phase only useful as part of a collection of data that lets us know whether the core ideas we're talking about in the new emails resonate.
We're not interested in getting as many people to read as possible,
We're interested in figuring out if the people who DO start to read then choose to consistently read and engage through the rest of the series.
That is the primary indicator of resonance.
MOST email series do NOT have a high degree of stickiness … they might start off around 50-70% for a new lead, and then gradually drop down to 15-25% (or sometimes not gradually).
(Pro tip, sometimes it's effective and appropriate to force this, where you only send to people who open each email, but when coming into an established system that we're going to change, I usually don't chose this kind of aggressive approach - part of the reason is we typically go into these new series with the reader having no pre-framed expectation that it is coming)
So, most people would approach this new series test with the idea to try to get as many people to read as possible, and get as many people clicking as possible.
But I want this to err on the side of the benign and to have a higher level of friction.
I want to encourage people to stop reading if they aren't feeling it. I WANT people to opt out and not read - because if they still pay attention in the face of all those reasons not to ... that's good data.
Simple subject lines. Longer emails.
I'll say it again:
We're not testing the efficacy of the words in driving as many people on your list to action ...
We're testing the resonance of the core ideas.
Do people stick and keep their attention because of those ideas?
(Because if they do, leading them to action ends up being 1000x easier)
If not, then - in the context of an existing business - you've either identified the wrong core principles or you aren't communicating them clearly enough.
And that is what we want to understand.
What does stickiness look like?
Over the course of the series - let's say 7 days - I want each email open rate to be with a couple percent variance of the first one. OR, if there's a dropoff after the first one (which can happen if you're dealing with a segment that is less tuned in / interested), I want to see that consistency after the second email (see the example at the top of this article).
Understand this:
People will NOT spend their time, effort, energy, attention, etc, to read your emails at all if there isn't something which resonates with their deep interest.
A consistent segment of your audience reading multiple emails from you over 1+ weeks is a very strong indicator that you are resonating with people.
The example here, and where this idea comes from, is a pretty tight use case.
It's likely at the moment that you are NOT applying R3 for Email (especially since I haven't published it yet), nor are you likely applying the same kind of principle filter methodologies I use in email series to shape a list.
BUT
The core idea applies no matter what you are doing ...
When you are trying to make changes to your current email list, be very clear on exactly what you are testing.
Getting as many people to open and take action is often NOT going to help you figure out the long term data that will lead to the reliable and effective system you desire.
What I most often see from people who want change with their email list is a short sighted short term interest in sales now. But they usually go about it in a way which only complicates, muddies the data, and makes longer term growth and clarity much more difficult.
There are ways you can get immediate sales *without* without causing these problems. (And in fact, ways you can do this which can *help* you clarify your messaging)
If that's what you need,
More sales/revenue/cash from your email list in the short term, then go check out The Cash Now Blitz Bundle4. This is a workshop collection with Nic and Laurel which goes over key Cash Now strategies from R3 which are designed to plug and play no matter what state your list is in.
Be Useful. Be Present. Love the Journey.
Joseph Robertson, CMO Man Bites Dog
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