I frequently get asked about the KPI’s (key performance indicators) that we use for measuring ad campaign performance.
As a performance marketing team, our goal is to grow sales at efficient CAC’s (customer acquisiton costs).
Unfortunately, this answer is not that helpful in guiding our agency partners towards strong results. Our partners primarily work within the ad platforms themselves (Meta, Google Ads, Impact, etc) and they do not have clear visibility into our topline metrics or how they are trending.
We created this write up to help our partners understand how the in-platform metrics ladder up to our topline business results and how to use secondary data sources (Google Analytics, MTA tools, post-purchase surveys, etc.) to further validate their campaign optimizations.
TLDR for partners: Focus on improving the in-platform metrics (sales and CAC), but also validate performance through secondary sources like GA4, an MTA tool, and post-purchase surveys to better understand how incremental the campaigns are.
The performance teams primary goal
Our primary goal is to grow gross sales with respect to the blended CAC targets.
It doesn’t matter if the Meta Ads platform reports a 10x ROAS (return on ad spend) if our Shopify order volumes are flat YoY (year over year).
At the end of the day, we need to drive incremental order growth as efficiently as we can as seen in our Shopify orders numbers.
We do this best by driving down funnel website behavior from our campaigns (site traffic, email captures, add to carts and purchases). The sales and CAC metrics found within ad platforms are helpful for understanding efficiency for that platform over time, but they are not our “only source of truth”.
How to operate with the in-platform ad metrics
The in-platform sales and CAC metrics are the metrics that agency partners should operate against.
They can also operate against your multi-touch attribution tool (MTA) if you have that setup, but in most cases they will need to use the in-platform metrics and validate their efforts with secondary metric checks.
It’s important to keep in mind the following when validating campaign performance:
- Which campaigns are driving down funnel website behaviors (causal) like website traffic, email captures, add to carts, and click based conversion data vs..
- Which campaigns are showing high conversions in-platform, but show minimal amounts of down funnel events
Beware of any platform that reports heavily on view through conversions in-platform (Meta, OTT/CTV, display networks) as these platforms may be inflating their importance of driving down funnel events in your marketing mix.
The secondary metrics for proving incrementality
GA4
GA4 is a helpful free tool to check how effective campaigns are at driving down funnel events like website traffic, email captures, add to carts, and click based conversions.
This is important to do on the campaign level that way you can map your spend data to the GA4 user metrics to see which campaigns are driving on site behavior efficiently.
You will need to set up UTM parameters on the ad URL level to help GA4 properly bucket traffic by campaign. You can find Google’s support article for setting up UTM’s here.
MTA tools
An MTA tool like Northbeam is helpful for understanding the incrementality of campaign performance across channels and campaigns.
Some of the MTA based metrics that I check inside of Northbeam include:
- 7 day clicks only CAC
- Total visitor counts
- Cost / visitor
- % new visitor
These metrics can help provide a deeper understanding of campaign performance beyond whats reported in-platform. Other MTA tool options to explore include Triple Whale and Rockerbox.
Post-purchase surveys
Post-purchase surveys can also be used to help guide marketing efforts. You should see correlations between whats reported in your post-purchase survey and how much you are spending across channels.
If you see a heavy mismatch between post-purchase results and spend percentage by channel, then you may be overly investing in a channel that is not driving purchases.
Incrementality examples
Non-incremental example
If we see an in-platform CAC that is $150 (vs $750 all other paid channels), but the cost/visitor number is $75 (vs $10 all other paid channels), then we know that this channel is not that incremental.
The cost/visitor number is too high when compared to our evergreen channels to be driving such a low CAC.
There are probably a ton of view-through conversions being picked up in this scenario as in-platform conversions, but the campain itself is doing a poor job of driving down funnel behaviors that lead to purchases.
Incremental example
On the other hand, if we see an in-platform CAC that is $600 (vs $750 all other paid channels) and the cost/visitor number is $12 (vs $10 all other paid channels), then we know that this channel is at least driving onsite behaviors and probably an incremental effort worth investing in.
The cost/visitor number is in alignment with our other evergreen channels.
I hope this helps, cheers!
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Metrics Breakdown
- Topline blended CAC:
- = total media spend / total orders in Shopify
- In-platform CAC:
- = ad platform spend / ad platform conversions
- GA4 users:
- unique website traffic visitors
- Northbeam (MTA Tool)
- 7 day clicks only CAC
- = spend / 7 day transactions
- New visitors
- Visits to your website from new visitors, as determined by the Northbeam Pixel.
- Cost / new visitors
- = spend / new visitors
- % New Visits
- Percentage of visits to your website that are from new visitors, as determined by the Northbeam Pixel.
- 7 day clicks only CAC
Continue reading: How to improve Meta (Facebook) Ads performance