STO Doesn't Always Make Cents
Send Time Optimization for large Flash Sales & Promos can come with trade-offs. And it may not ultimately drive the results you are looking for. Here's what I learned several years ago.
What’s good on paper isn’t always good for every use case.
Send time optimization is one of those tactics that can be easy to generalize as a must-do, low-hanging fruit lever. But in my experience, it works better for automated drip sequences versus larger, multi-touch campaigns.
Today, I’m going back in the archives to share a case study from my time at Grammarly where we used a leading Send Time Optimization tool to try and drive incremental conversions for our monthly promo (discount) series.
And this won’t be a shocker given my positioning above, but it did not result in a win. It almost did, but there was a common short-term lift that ended up being a wash after the full campaign was over. Keep reading for the compelling and, in hindsight, logical takeaway.
Then, for fun, I’ll share a few more examples of significant AB test results that led us to either adopt—or ditch—a new technique for that same promo series. Yay, testing!
And we’re off...
Our Promo Series In a Nutshell
The Grammarly promo series has, to date, typically been an email-exclusive offering. We send themed, premium-focused emails to encourage our free users to try one of our individual subscription plans (Monthly/Quarterly/Annual).
In most cases, we offer a discount to these users to entice them as they’ve already been on file for a little while and haven’t converted yet.
On average, we produce one promo per month with two to three dedicated announcements and reminders to support it.
The monthly promos have provided a petri dish to some of our most compelling tests over the years because a) the engaged audience size is HUGE (large enough to do A/B and multivariate tests) and b) we can tie success to the business metrics very easily: namely unique premium upgrades.
Depending on the nature of the test we will also look at metrics like AOV, projected LTV, and conversion rate on the landing page.
Below is an example of a Grammarly promo email from when I still had the reins:
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