Navigating Facebook data post-iOS14

🤔 The media buyer’s dilemma

In the wake of iOS14.5, relying solely on Ads Manager as a central source of truth for your media buying is a dicey play.

Beyond the discrepancies we reported on in Monday’s issue, Meta’s conversion modeling is delayed in real-time, meaning it can be difficult for media buyers to make confident day-to-day decisions about optimizing and scaling campaigns.

❤️‍🩹 Trust issues

As someone who uses Meta as an ad platform, you must recognize that you no longer can trust platform-specific data alone without referencing additional “sources of truth,” specifically Shopify and Google Analytics.

Of course, your Ads Manager dashboard can still give you a decent sense of what ads are working, and for some stores the discrepancy between what Meta reports, and what Shopify reports is small.  

However, many stores are seeing a 20-50% drop in conversions due to underreporting. More importantly, they’re witnessing a significant reduction in prospecting conversions from the top of their funnel.

Because you can’t always rely on data based on past behavior, it’s important to plan a more active approach to your media buying.

🐻 Poke the bear, then pin it

They say not to poke the bear, but those people have never had to figure out paid social.

Rather than reading campaign data on Ads Manager and reacting with changes, we’re using a more active approach, which we call “poking the bear.”

In this analogy, the bear is Meta’s ads algorithm, and by poking it with a targeted spend, and then using Shopify and Google Analytics as your “sources of truth” to pinpoint where to increase your ad spend to see the most real lift.

👇 Confused? Let's break this down…

This concept of active performance media buying can be applied across campaigns, creatives, geo, and more, but essentially it boils down to:

The poke: Think of each poke as an ad spend with an isolated hypothesis. You can poke to test any variable, creative, or campaign configuration. The golden range for the 'poke' is between 5-15% based on the store's confidence in the revenue they plan to receive from the ads' return.

The step back: Assess the results: first look at Shopify to see the revenue truth. From there you can compare to Google Analytics to get more granularity about your campaign, via the UTM codes you’re using on all your links. With this data, you can process the trend lines caused by your campaigns.

The pin: When you isolate a winner using your source of truth and see your spend’s incremental impact on your Shopify results. You go in for the pin and get more aggressive with your ad spend (or as Pilothouse called it in last week’s podcast “slam spend.”)

🥜  Poke the bear strategy TL/DR

  • Look at eROAS, which consists of ad spend vs. Shopify revenue
  • Lean into Google Analytics UTM data to look at certain trendlines to form decisions.
  • If things look fine and dandy, poke the bear harder and increase your ad-spend
  • If things aren’t looking so great, pull back and step away from the bear, evaluate the available signals, and restructure your next poke

In the coming weeks, we’ll be writing more on best practices for post iOS14.5 optimizing on meta, including the amazing world of third-party tracking.

If you're interested in learning how not to be Leo DiCaprio from The Revenant, check out the All Killer No Filler podcast with the Pilothouse Facebook team. 🚨

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