RPME

A Tale of Two Purchased Lists (A Case Study)

a-tale-of-two-purchased-lists-(a-case-study)

Which segments of your list are most profitable? Are purchased lists always low performers? This client case study provides answers to both of these questions – as well as providing a framework for you to use to answer them for your own list segments. As always, don’t just take these test results as gospel – do your own testing to see how your audience performs!

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Case Study: How many products does it take to optimize revenue?

case-study:-how-many-products-does-it-take-to-optimize-revenue?

How many products should you include in an email to optimize revenue? As marketers, we have to balance the number of products we present to potential customers. Too few and you may lose sales because there aren’t enough options; too many and you may lose sales due to analysis paralysis. This is a test I do a lot with clients sending multi-product emails. We work

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Holiday Prep: Best Day to Send Email (A/B Split Test)

holiday-prep:-best-day-to-send-email-(a/b-split-test)

I always get a laugh out of research promising to reveal the ‘best day to send email.’ Because, think about it… if the research says ‘Thursday at 3:00 PM ET’ is the best day/time to send, and everyone started sending at 3:00 PM ET on Thursdays, then the best time to send would be any time but that. Because at 3:00 PM ET on Thursdays

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43% increase in revenue with a holiday campaign! Here’s how we did it…

43%-increase-in-revenue-with-a-holiday-campaign!-here’s-how-we-did-it…

I’m not a big fan of subject line tests for a couple reasons. They’re overused and many don’t have a good chance of success because they lack a sound hypothesis. If I undertake a subject line test with a client I’m going to do it strategically, to give us our best chance at a significant lift in bottom-line performance. That’s what we did for an

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Proof that Click-through Rate is NOT a Good KPI

proof-that-click-through-rate-is-not-a-good-kpi

“We don’t have tracking set up for revenue or conversions. We just look at opens and clicks. Because the email with the highest click rate probably has the highest conversion rate as well, right?” As an email marketing consultant and trainer, I hear this a lot. I get it. It takes time, budget, and resources to integrate Google Analytics or another platform that’s measuring your

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Case Study: Subject Line Change Increases Revenue by 9%

case-study:-subject-line-change-increases-revenue-by-9%

It’s always fun to experience, and write about, big wins, like a 918% increase in revenue, or a 350% boost in list growth, or a 100% increase in site traffic. It would nice if every test delivered that, but that’s not the case. Here’s the thing: if you can earn a lift of 10% on every test and apply each learning before you do your

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Case Study: More Product Blocks, Less Revenue

case-study:-more-product-blocks,-less-revenue

Back in 2020, I was consulting for a B2B client with an enormous number of products. Their buyers are buying in bulk; they don’t buy one of an item, they buy 100 or 1,000 of an item. We did a series of A/B split tests, with different email templates, to find the ‘sweet spot’ – the perfect number of products to include in each email

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Case Study: Less Copy Generates a 918% Lift in Email Revenue

case-study:-less-copy-generates-a-918%-lift-in-email-revenue

Sometimes less is more – a lot more. Case in point: this case study from 2020, where removing some copy generated a 918% lift in revenue-per-thousand-emails-sent (RPME). You can see the control at the left below, the test version is on the right. and the color key to content is there as well. When you’re thinking about what you might test, you always want to

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