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Send Time Optimization (STO) with Motiva AI and Eloqua

One useful tool in the marketing toolbox is paying close attention to campaign response data in order to improve send times and maximize performance. Done well, you can dramatically increase campaign performance by using that response data to configure time slots to optimally map to audience preferences. This post is about using Motiva AI Cloud for Eloqua to automatically determine those optimal send times within a campaign.

 

Send Time Optimization (STO) works whenever you run a Motiva AI Email Optimizer step on the canvas. As a refresher the Motiva EO is functionally like Eloqua's Send Email step, except that it accepts any number of message variations and automatically finds and invests in the best candidates to maximize response rates. It's multivariate, adaptive message optimization backed by machine learning. You can read more about that here or our Getting Started Guide.

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Once you've configured the Motiva AI Email Optimizer, you can choose to restrict send times (just like the Eloqua Send Email step), or you can leave it wide open - it's your choice. Like this:

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As Motiva runs its messaging experiments over a given audience and period of time, it also gathers response data (opens, clicks, etc.) from that step in your campaign.  Over the course of the campaign and as long as you leave the Motiva EO running, it will gather more and more response data, and automatically generate a report that represents audience behavioral responses over 7x24 grid. That's all seven days for all hours of each day. It looks like this (click on the image to enlarge):

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The report will update itself each time a new Motiva AI experiment happens - which is configurable, but most users leave to the default one experiment per day.

 

With this report you can quickly get a sense of the volume of emails you're sending in a given hour-by-day window and how people are responding. Larger diameter circles mean that you sent relatively lots of emails in that period, and the color shading is response rate.  You can toggle between Unique Open Rates and Potential Lead Rate (which is like CTR, but more tightly defined as unique clicks - unsubscribes / total of emails successfully delivered).

 

tl;dr: Big Circles / Light Color = Not Good; Big circles / dark color = Good! But there are lots of situations where we're in between the two extremes. Look for relatively small volume / high response slots and where shifting send times from other slots might make a difference.

 

Here's where it gets interesting. Take a look at this chart. Where are opportunities for send time improvement?

 

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Or how about this one?  Note that this campaign has Motiva AI running experiments and sending waves of emails essentially 24/7.

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Once you're confident in the response patterns you're seeing - usually over a couple of weeks - you can use this feedback to optimize send time restrictions on the canvas easily. At the same time, it also helps you have a data-driven conversation about what's working with your campaign and what's not with your colleagues and teams.  Data ftw!

 

Try it for yourself.

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