This article covers tips on how to provide actionable feedback for revising Variants. With your help and input, we can refine our language and learnings to best fit your brand voice.
Specific and Contextual
Our AI is rule-based, so the more specific and contextual your feedback, the better results we can produce. Provide context about why and when certain content should be avoided. Even though we use AI, our team is heavily involved in ensuring content quality and catches things that fall outside of the AI’s capabilities.
Examples of helpful feedback:
“Open ASAP” is too aggressive for this campaign type – can we ban “ASAP” for any campaign other than “last chance” promos?
This headline is a claim. We need to avoid mentioning A, B or C for compliance reasons, but can say X, Y or Z.
We refer to our customers as clients. Please replace “customer” with “client” in Variants 4, 8, 12, 16.
Examples of less helpful feedback:
This feels off brand.
Too loud.
Down market.
Replace ‘last chance.’
Provide an ALT.
The more specific you can be about why an element of the Variant isn’t working, the higher the chance we can find a more effective solution and avoid similar language in the future.
Lastly, consider how feedback may apply to the control. The control message should be held to the same standard as Variants. If feedback applies to the control, the Persado team may ask for an updated version of the control.
Variety of Language
Be sure to test a wide variety of language in the Variants. After editing, you want to make sure they don’t all sound too similar to one another. Testing a wider array of language and emotional elements gives the test more elasticity. More elastic tests means a higher chance of reaching statistical significance and opportunities to gain insights. If all the language sounds too similar, it’s harder to learn what worked and what didn’t.
Aggregate Feedback
You can make edits to Variants yourself in Portal. However, if you need the assistance of the Persado team, please submit feedback in a single request to help reduce the number of rounds of revisions.
Tips for Experiments (Not Applicable to Predictive Content)
Approval in Exploration
If you’re conducting an Experiment, it’s important to only approve content in Exploration that you’d feel comfortable deploying to a broader audience in Broadcast. Language tested in Exploration is often used to create high-performing content in Broadcast.
Updates to Variants
Please keep in mind that changes to 1 Variant may affect 4 (or more) Variants. Because we implement experimental design in our Variant creation process for Experiments, revisions to a single Variant could invalidate our test design. In Portal, hover over language to see which Variants would be affected.