How we're handling post-iOS 14.5 Meta ads testing and scaling
It's been over a year since Apple rolled out their mobile software upgrade iOS 14.5, which was a massive downgrade for all marketers. Also, Meta followed data privacy updates and a lot went south for a bit. Dig right into the article and find out how we adjusted and even managed to grow clients' revenue. And we’re not talking about the necessities like verifying the domain, prioritizing events, and so on... You will get some real advanced badass tips that are our bread and butter .💸
First, let's get some background and circle back to what happened in the last year and what were the reasons the performance started to drop.
1. Targeting 🎯
Since most of the iOS users opted out (+90%), the efficiency of retargeting significantly dropped, and the performance of the Lookalike audience based on data sources that weren't being tracked correctly, began to decline. Also, you are not able anymore to target some of the interests that relate to topics people may perceive as sensitive (health, race or ethnicity, political affiliation, religion, or sexual orientation).
2. Reporting 📊
The limitations are seen in breakdowns, where you can't breakdown and see performance for specific placement, gender, age, and region. Then there’s delayed attribution, which is not making it any easier, and overall all metrics are overreporting or underreporting since pixel can’t track all the data properly.
Apple limited Meta advertisers to only 8 conversion events per website, which provided a significantly lower amount of data points for an algorithm to learn from and properly optimize.
Now let’s get to the juicy stuff.
What's the META with your ads?
How we tackled it?
Strategically, of course!😎 We stuck our heads together, brainstormed for quite a while, and then started learning, testing, and optimizing our tactics.
Inefficient retargeting? Try re-engaging audiences ✅
Retargeting audiences are getting smaller and they don't include all people - wrong! That happens only with audiences where the customer leaves the Meta platform and visits your website. We are using re-engagement audiences, for example video viewers and engagers, which are based on the first-party data from Meta.
Poor performance of Lookalike audiences? Try Lookalikes based on customers list & engaged audiences on Influencers’ pages ✅
It's a fact that Lookalike audiences based on events outside Meta platform dropped in performance. We found that lookalikes based on re-engagement and re-engagement of our whitelist influencers outperform lookalikes based on events like add to cart, view content, or website visits, because of better data and bigger audiences. Also, try importing customers lists and make lookalikes from them.
Disabled interest targeting? Try dedicated creatives. ✅
The algorithm will work its way around disabled interest and still find your targeting audience. Based on your previous performance and activity, the algorithm can assume pretty well who you want to target. You can do that with dedicated copy, dedicated creatives, and dedicated captions or text in creatives. For example, if you target pregnant women, you need to craft a copy where you address them. The creative needs to be straightforward and show a pregnant woman in the ad and the algorithm will keep pushing the ad to the right audiences.
🚀 Reporting and scaling
Facing delayed attribution? Use 3rd party tracking tools. ✅
Testing a killer batch of creatives can be a pain in the ass when you get decent traction on metrics like ATCs, clicks, CPMs, but there are no purchases. You turn it off and in a few hours the sale comes in. With 3rd party tracking tools like Hyors, Triple Whale, Wicked reports, or Anytrack this doesn't happen. We gave them a try, and our golden combination is using Triple Whale and Hyros which turned out to give the most value. These tools also come in very handy when you are running time-sensitive offers and you need real-time data fast if you want to skyrocket your campaigns. You can also make rules that apply to 3rd party data, which can save you a lot of money.
Lost data from iOS opt-outs? Set up Offline conversions ✅
Since Meta pixel isn't collecting as much data as it did prior to privacy updates, sending offline conversion back to pixel is a must. This way pixel optimizes better for your desired events and also performs better. We found Integromat to be the easiest way to push these valuable pieces of data back to the Meta platform. It's completely automated and stress-free once you have connected the Meta platform and your website or CRM. You can also try to do this with Madgicx, Zapier automation, or other 3rd party apps.
These are some of the most popular tricks our team is using to deliver such awesome results. Do we think that everyone should implement them? Hell yeah!🤘
If you want to get more of these tricks let's jump on a call and let's see if we have the potential to work together and put them into action!
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