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Email Marketing Success Metrics Vary by Subscriber [Video]

Success is rarely a monolith. Usually it’s a mountain range. That’s because marketers typically have of number of shifting goals that change from campaign to campaign. One time you may be trying to maximize revenue, while another time you may be trying to maximize engagement or sharing or some other behavior. We found that to be the case when we examined the success of our own email campaigns.

Success is also a mountain range because marketers generally serve a variety of audiences, each with their own expectations of us. And that means that success with each of these audiences may not look very similar.

Vicky Ge, Marketing Manager, Trade Books, at, is very mindful of the different audiences that the ecommerce giant serves. At The Email Design Conference, I had the opportunity to sit down and interview Vicky about how marketers can best approach measuring success across their various audiences.

You can watch the full interview here, or read a transcript of it below.


We really focus on customer-centricity at Amazon. And so everything we do—we focus on the customer, think about that person’s context and that person’s story, and then work backwards. And sometimes that’s not captured in email metrics.

Metrics by Cohort

I think there are many ways to slice and dice the data that you get back from an ESP. And for us, we try to group out our success metrics by different customer clusters. That’s a little bit what I covered in my talk—these frameworks of looking at your subgroups of customers. And everyone is going to do it a little differently. Every company is going to have different high-value customers or low-value customers. So it’s a little bit case by case. But regardless, as a company you can still go back to your email success metrics and start to create these cohorts. I think that’s the key takeaway.

Many Definitions of ‘Value’

I think we need to be clear on what we mean when we say, “value.” There are different frameworks for looking at value. As I talked about in my presentation, there is a framework around RFM: Recency, frequency, monetary. That’s one way of looking at customer value.

There’s also another framework around level of engagement or level of sharing. Maybe you have someone who doesn’t spend a lot in your company, but tells everybody else to. That’s another type of value.

So there are several different ways to look at customer values. And I would caution people—marketers—who are working on this type of optimization to not pigeonhole themselves into any one valuation.

My goal is to make sure that any person is receiving the content that is most appropriate to that person. If that person is an influencer, I want to send them the content that helps them be an influencer. If that person just likes to shop a lot, I want to send them content that they want to buy. If that person is a browser, I want to send them content they like to browse through.

So I want to make sure that every customer, depending on their set of attributes, is being served optimally. And by optimal, I don’t necessarily mean the most money, generally. I mean, something that’s going to make them the happiest.

Value vs. Cost

I think a somewhat common perception about email marketing is that it’s free. And it’s not. For every customer, there is some sort of revenue associated with that customer. There’s probably also some sort of dollar value associated with that customer if he or she chooses to unsubscribe.

So if you’re a marketer, and you’re struggling to convince a boss or a team that email is somewhere worth investing in, I would spend some time thinking about the value of each mail that you send. And there are frameworks around the internet for how to look at this. A simple one is to look at some dollar value return percent on average minus some dollar value lost per unsubscribe.

And it’s actually pretty worrisome right now because it seems like some half of marketers in the US don’t look at email value. They’re only looking at how much it costs to send out a mail. That’s really not the right way to look at customer value.

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