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Schaun Wheeler
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A short time ago, we wrote about how message timing had a greater impact on conversions than the actual content of the message itself. So, if you can only optimize one thing—timing or copy—then you’re better off optimizing timing. (To be clear: you can and should optimize both. That’s why we built Aampe). 

However, that post left unanswered a critical question: How much of a difference does good timing make? 

As it turns out, a whole lot:

This is two months’ worth of messaging and response data from one of our customers, across three countries. The percentages aren’t click-through rates—oh, no—they’re completed checkout events. 

We’re talking revenue generation. Each value is the percentage of messages that resulted in a checkout within 24 hours of the message being sent, so, while the numbers by themselves look small, keep in mind that every bit of that is money in our customer’s pocket.

Now, we sometimes send messages to users at the wrong time. In fact, we do it all the time. 

Usually, it’s because we don’t (yet) know what the good time is: Maybe we just haven’t had enough opportunity to figure out a particular user’s preferences, or maybe the user doesn’t really have a preference for *any* time. 

Other times, we message users at a less-than-preferred time just to see if their preferences have changed—You’ll never know unless you try, right?  

At any rate, the “wrong time” column represents messages where the timing our system chose to use was a timing that our system, frankly, didn’t think was a very good bet. The “Right Time” column, on the other hand, represents messages where our system chose timings that it believed to be very good bets. 

The result: Messages sent at the right time performed 240-330% better than messages sent at the wrong time.

“Now wait a minute,” say those of you who don’t use Aampe, “how do I apply that to my situation? How do I know how many of my messages I’m sending at the wrong time? How do I know how many messages I’m sending at the right time?”

That’s the point: you don’t. 

If you send out a message “blast” (shudder), then several things are happening at once:

  • You’re bugging some of your users to do the thing that they were already going to do even if you never bugged them (If you’ve included a discount incentive in your message, then you’ve also thrown some money down the toilet for no reason).
  • You’re hitting some of your users at a time when, at best, they just don’t have the opportunity to respond. (At worst, you’re hitting them at a time when they resent being contacted). So you’ve left them confused, maybe disappointed, and possibly enraged. None of those are a good look for your app.
  • You’ve messaged some people at just the right time, when they’re open to engaging with your app, and when they might have engaged had you not reminded them to.

And you have no way of telling which users fit which conditions. 

Oh, and if you’re scattering your messages across lots of different times, then you’re just doing all three of the above things at random times, but not necessarily better times.

The value of Aampe isn’t just that you can get the timing right—and therefore get every bit of that 240-330% lift in ROI that’s coming to you—but you can also see evidence that that’s what you’re doing

You can be confident that you’re getting to your users at the times that work for them, and that’s what matters most for your bottom line.

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Talk to your users at times that work for them. It impacts your bottom line.

How much does good timing impact ROI?

A short time ago, we wrote about how message timing had a greater impact on conversions than the actual content of the message itself. So, if you can only optimize one thing—timing or copy—then you’re better off optimizing timing. (To be clear: you can and should optimize both. That’s why we built Aampe). 

However, that post left unanswered a critical question: How much of a difference does good timing make? 

As it turns out, a whole lot:

This is two months’ worth of messaging and response data from one of our customers, across three countries. The percentages aren’t click-through rates—oh, no—they’re completed checkout events. 

We’re talking revenue generation. Each value is the percentage of messages that resulted in a checkout within 24 hours of the message being sent, so, while the numbers by themselves look small, keep in mind that every bit of that is money in our customer’s pocket.

Now, we sometimes send messages to users at the wrong time. In fact, we do it all the time. 

Usually, it’s because we don’t (yet) know what the good time is: Maybe we just haven’t had enough opportunity to figure out a particular user’s preferences, or maybe the user doesn’t really have a preference for *any* time. 

Other times, we message users at a less-than-preferred time just to see if their preferences have changed—You’ll never know unless you try, right?  

At any rate, the “wrong time” column represents messages where the timing our system chose to use was a timing that our system, frankly, didn’t think was a very good bet. The “Right Time” column, on the other hand, represents messages where our system chose timings that it believed to be very good bets. 

The result: Messages sent at the right time performed 240-330% better than messages sent at the wrong time.

“Now wait a minute,” say those of you who don’t use Aampe, “how do I apply that to my situation? How do I know how many of my messages I’m sending at the wrong time? How do I know how many messages I’m sending at the right time?”

That’s the point: you don’t. 

If you send out a message “blast” (shudder), then several things are happening at once:

  • You’re bugging some of your users to do the thing that they were already going to do even if you never bugged them (If you’ve included a discount incentive in your message, then you’ve also thrown some money down the toilet for no reason).
  • You’re hitting some of your users at a time when, at best, they just don’t have the opportunity to respond. (At worst, you’re hitting them at a time when they resent being contacted). So you’ve left them confused, maybe disappointed, and possibly enraged. None of those are a good look for your app.
  • You’ve messaged some people at just the right time, when they’re open to engaging with your app, and when they might have engaged had you not reminded them to.

And you have no way of telling which users fit which conditions. 

Oh, and if you’re scattering your messages across lots of different times, then you’re just doing all three of the above things at random times, but not necessarily better times.

The value of Aampe isn’t just that you can get the timing right—and therefore get every bit of that 240-330% lift in ROI that’s coming to you—but you can also see evidence that that’s what you’re doing

You can be confident that you’re getting to your users at the times that work for them, and that’s what matters most for your bottom line.

This browser does not support inline PDFs. Download the PDF to view it.