Ever feel like your new Facebook ads don't get many views or clicks at first? There's a reason for that - it's called the learning phase. When your ad first starts running, Facebook's advertising system takes some time to figure out the best audience and placement for it. During this learning period, performance might seem low as the system experiments to optimize your ad. With some patience and testing, you'll guide your ads out of the learning phase so they can start showing more people and getting better results.
What Is the Learning Phase in Facebook Ads?
The learning phase refers to the initial period when Facebook's ad delivery system is gathering data and optimizing a new ad set. When an ad, ad set, or edit is made within an existing Facebook ad campaign, it triggers the learning phase. During this time, Facebook's machine learning algorithm serves the ads to different segments of the target audience to determine the optimal combination of timing, placement, audiences, and ad enhancements to achieve the campaign goals and performance targets.
Key aspects of the learning phase:
- Facebook gathers insights on ad performance over time by analyzing data signals such as time of day, placements, demographics, device types, and engagement rates. The more an ad is served, the more optimization data Facebook collects.
- Performance metrics like cost-per-action (CPA) or return on ad spend (ROAS) usually decline temporarily before improving. This is due to Facebook's testing different variants to find the best match between ad creative, target audience, and delivery parameters.
- Day-to-day performance fluctuates more wildly in the learning phase than during regular delivery. Some days have strong results followed by days with very high CPAs or no conversions. This variability smoothens out once the algorithm has optimized delivery.
- On average, campaigns do not perform as well during the learning period as they do after it ends. However, Facebook does not guarantee that a campaign will achieve its specific goals even after optimization. Performance depends on many factors.
Why Is the Learning Phase So Important?
Understanding what's happening behind the scenes during the learning phase is critical for advertisers. Here are four key reasons you should not only accept but embrace this period:
Improved Ad Optimization
The overarching purpose of the learning phase is to improve optimization. Each time an ad is shown, the ads delivery system measures and optimizes targeting, placements, bidding, and other factors that improve performance.
The more your ad is shown, the more optimized your ad is because Facebook ads have more data to learn from. In a study by Meta, Advertisers may experience a 20-30% increase in performance metrics like conversion rates or cost-per-conversion.
Cost Efficiency
As Facebook gathers more conversion data during the learning period, the platform becomes remarkably adept at allocating your budget for maximum ROI. The system learns to spend more on placements, audiences, and times of day driving conversions and less on underperforming elements.
This efficiency gain means your money goes further over time. You'll generally see a declining Cost Per Result (CPR) as the learning phase progresses and Facebook eliminates waste. Through Facebook Ads Help Center or Meta Business Resources, During the learning phase, Facebook's ad system tests and learns to find the best audience and ad combinations. As the system gathers more data, CPR (Cost per Result) tends to decline. On average, advertisers see a 20-30% drop in CPR after the learning phase is complete.
Avoiding the Pitfalls of Premature Optimization
Eager advertisers often make the mistake of manually optimizing campaigns too early. This over-correction can severely limit the reach and performance of ads. Turning off Facebook ads before the learning phase finishes or making frequent changes can reset the process, undoing the work Facebook’s algorithm has already done.
Facebook's algorithm includes an initial automated learning phase that optimizes targeting, placements, creatives, audiences and other elements. 68% of advertisers who make manual changes during this learning period actually saw a decrease in conversion rate.
Optimizing too early without enough Facebook data will have a negative impact on performance. Please be patient and do it step by step to help the algorithm work its magic before making major changes.
Expecting Performance Variability
During the initial learning period, fluctuations in cost per result and conversion rates are completely normal. The highs and lows you see can feel alarming for advertisers.
However, recognizing that this variability in ad results is an inherent part of Facebook's optimization process can set appropriate expectations. The algorithm tests different permutation and will necessarily see varying outcomes. In one sample campaign, conversion rate fluctuated between 2.8% and 8.5% during the phase.
Once the learning phase reaches completion, results typically stabilize around a target cost and conversion rate. But getting anxious about daily fluctuations during this experimentation window can lead to rash decisions that disrupt the intended optimizations.
Signs Your Ad Is Still in the Learning Phase
One of the most common questions advertisers ask is, "How can I tell if my Facebook ad is still in the learning phase?" There are a few telltale signs that your ad is still in this phase:
Fluctuating Performance Metrics
If your ad’s performance shows increases one day of 50% in click-through rate (CTR), followed by a 30% drop the next day, and then another 60% jump in CTR the following day, this kind of extreme volatility likely means you are still in the learning phase. Facebook's algorithm is testing many different ad delivery combinations which leads to spikes both up and down.
Learning Phase Status in Ads Manager
In your Facebook Ads Manager, you can check the status of each ad set. If it shows "Learning (83% complete)" under the “Delivery” column, this means you are still in the learning phase, with just 17% of the phase left to go. Once this status changes to "Active" or "Completed," the learning period is over.
Higher CPA Than Expected
If you expected a cost-per-acquisition of $25 based on past campaigns, but you are currently seeing CPAs of $38, this 50% increase could indicate that Facebook’s algorithm is still learning which audience segments will convert most efficiently. During the learning phase where the algorithm is less precise, costs per result can be 35-75% higher in some cases before optimizations take effect.
How to Minimize Learning Phase Issues and Optimize Ad Performance
While Facebook's learning phase allows its sophisticated algorithms to determine optimal ad delivery, advertisers can take certain steps to help guide this process smoothly:
Set Realistic Conversion Benchmarks
To complete learning efficiently, Facebook's AI benefits from consistent conversion event data flow. Set expectations around at least 50 conversions per ad set over the initial 7-14 day learning period.
Unrealistically low conversions goals slows learning and delays eventual optimization. Monitor goal progress in Ads Manager and adjust targets if needed.
Minimize Optimization Disruption
Making frequent changes to ad creative, targeting, bidding or budget during the learning phase can significantly slow or even reset progress.
Avoid tweaking elements under active experimentation until notifications confirm learning is complete. Incrementally adapt thereafter to prevent re-triggering initialization.
Gradual Budget Increases
Boosting budgets radically overnight can shock campaigns out of their incremental learning rhythm. Instead, gradually scale budgets 10-20% weekly allowing additional data absorption without disruption.
This smooth expansion keeps learning algorithms aligned while spend scales up or down. Significant variances require restart adaptation.
Isolate Testing in Structured Ad Sets
When introducing new creative concepts or audiences, fork tests off into separate structured ad sets apart from ongoing optimization in main campaign.
This siloed testing workflow allows new learning phases to occur independently without interfering with existing momentum. Preserve continuity.
Embrace the Full Learning Timeline
Have patience as the algorithm crunches numbers determining high-performance configurations for each campaign objective.
Unless diagnosed issues, avoid adjusting elements during fluctuations in learning and allow full 7-14 day optimization cycle to benefit end performance.
With the right go-to-market strategy focused on minimal disruption, advertisers guide Facebook's sophisticated learning phase to efficiently optimize each ad campaign for maximum results.
The learning phase in Facebook ads is a critical process for ensuring your campaigns are optimized for success. Renting a Facebook ad agency account from Rent Ads Agency allows tapping into expert guidance optimizing through rocky learning phases. We have a team of staff with 10 years of experience in Facebook ads who will definitely support you a lot. Trust us your process will be significantly improved.
Mohamed Fouad is a full-stack web developer and an entrepreneur who's really into advertising. He is the CEO of Rent Ads Agency, a company that helps businesses reach more customers through advertising. He graduated from Stanford University in 2018 and has over 4 years of experience in the tech industry.
