Hi,
I’d like to analyse my previous campaigns and see what attributes/properties the profiles that converted (and also those that didn’t convert) have in common, so that I can create better segments for my future campaigns. I know I can do this manually, but does anyone know of any easier methods or third party tools to achieve this?
Thanks in advance!
Solved
Finding Common Attributes Between Profiles That Converted
+1Best answer by KatherineB
Hey
There are a few third-party tools that may achieve what you’re after. Omniconvert Reveal lets you put users in buckets based on RFM metrics and syncs those audiences to Klaviyo.
Peel Insights analyzes data for what drives LTV
Lifetimely is another LTV app and also shows which marketing efforts and driving or reducing LTV.
Hope any of these solutions help!
+31Hey
+1Hey
Hi Kaila
For example, let’s say I have 5,000 profiles that converted from my previous campaigns. I’d like to find the common attributes between these profiles so that I can make better segments for my campaigns.
Below is a hypothetical output of this analysis just so you know what I mean:
Based on the analysis of past 5,000 profiles that converted, their common attributes might be:
-Mainly returning customers
-Mainly living in the East Coast USA
-Have previously opened more than 10 emails
-Have abandoned cart more than 2x in the past 90 days
+31Oooh, fabulous question. Of course, you could do this manually, but automated? Hmm. I don’t know of any tools the off the top of my head but let me loop in some of our Champions who might have some ideas for you:
+23Hey
There are a few third-party tools that may achieve what you’re after. Omniconvert Reveal lets you put users in buckets based on RFM metrics and syncs those audiences to Klaviyo.
Peel Insights analyzes data for what drives LTV
Lifetimely is another LTV app and also shows which marketing efforts and driving or reducing LTV.
Hope any of these solutions help!
+27This is a great idea, and something I wish was easier to accomplish in Klaviyo without manual work!
Warmly,
Gabrielle
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