Introduction
Once you understand what the Google Ads learning phase is, the next logical question is: how do you get out of it faster? The truth is, while you can’t skip the learning phase entirely, there are smart strategies that can help you shorten it without messing up your campaign’s effectiveness.
In this second part of our Google Ads Learning Phase series, we’ll explore practical ways to minimise the time your campaigns spend learning. You’ll learn what to avoid, what to optimise, and how to give Google’s machine learning exactly what it needs to start delivering results, quicker.
Why Speeding Up Learning Matters
When a campaign is stuck in learning mode, results are often volatile and inefficient. You might see higher CPAs, fluctuating ROAS, or uneven spend patterns. This instability can delay decision-making and stall progress, particularly for businesses with tight marketing budgets.
Getting through the learning phase faster means your campaigns become more predictable and efficient, helping you hit your goals sooner. But doing it wrong, like making too many changes or setting unrealistic targets can keep you stuck in learning indefinitely.
1. Limit Major Changes
Every time you make a significant change, such as switching bid strategies, adjusting targets, or adding asset groups, you reset the learning clock. Try to:
- Bundle changes together so they trigger a single learning phase
- Avoid unnecessary edits during the first two weeks of launch
- Let campaigns stabilise before experimenting with settings
A good rule of thumb is: if a campaign is still learning, don’t touch it unless absolutely necessary.
2. Avoid Large Budget Jumps
Sudden budget changes are one of the biggest triggers for re-entering learning. Google’s system sees a large increase or decrease as a new campaign environment.
To avoid this:
- Keep budget changes below 20% at a time
- Scale gradually (e.g. increase budget by 10–15% every few days)
- Monitor results closely after each adjustment
For Performance Max or Shopping campaigns, which learn across multiple channels, gradual increases are especially important.
3. Set Realistic Targets
Setting an overly aggressive Target CPA or Target ROAS can stall performance during learning. If Google doesn’t believe it can hit your goal, it will reduce bidding — sometimes too much.
To help the algorithm learn:
- Start with Maximise Conversions or Maximise Conversion Value without a target
- Or, set your target close to your historical average
- Tighten targets later, once the campaign is delivering consistent conversions
Giving the algorithm more freedom early on leads to faster learning and better results long-term.
4. Use a Healthy Daily Budget
Google recommends setting a daily budget at least 3× your target CPA to ensure enough data flows through the system. Without sufficient daily budget, it may take weeks to gather enough conversions for reliable optimisation.
For example:
- If your target CPA is £20, aim for a budget of at least £60/day
- If that’s not feasible, consider consolidating campaigns to pool data
A healthy budget ensures the algorithm has enough opportunities to test and learn quickly.
5. Improve Conversion Tracking
The system learns based on your conversion data so poor tracking slows everything down. Make sure:
- Your primary conversion actions are set correctly
- You’re not tracking too many low-value conversions
- You’re using Enhanced Conversions and GA4 integration where possible
If your tracking breaks or changes mid-flight, Google will re-learn from scratch. Keep tracking stable, and ensure the data is meaningful.
6. Avoid Over-Segmenting Campaigns
Splitting your campaigns too finely can result in each one having too little data to learn efficiently. This is especially true for:
- Performance Max (multiple asset groups with low spend)
- Shopping campaigns (too many product groups)
Instead:
- Consolidate campaigns where possible
- Group similar products or services together
- Run fewer, more focused campaigns to speed up learning
7. Provide Strong Assets and Signals (For PMax)
Performance Max campaigns rely heavily on the quality and variety of your inputs. To accelerate learning:
- Upload multiple high-quality creatives (images, headlines, videos)
- Use Audience Signals (e.g. custom segments, customer lists, in-market audiences)
- Ensure assets follow Google’s best practices (clear offers, strong calls-to-action)
While Audience Signals don’t restrict targeting, they help Google find early wins faster.
8. Don’t Panic — Let the Data Come In
Perhaps the hardest part of the learning phase is resisting the urge to intervene too early. If you make a change every time metrics wobble, you’ll keep resetting the process.
Instead:
- Give your campaign at least 7–14 days of uninterrupted runtime
- Track performance, but don’t optimise daily
- Wait until the learning label disappears, then wait again for your full conversion cycle to pass
Patience isn’t just a virtue here it’s a strategy.
Conclusion
While you can’t entirely avoid the learning phase in Google Ads, you can absolutely make it shorter and less painful. By feeding Google the right data, avoiding disruptive changes, and scaling budgets carefully, you give the algorithm everything it needs to succeed sooner.
In Part 3 of this series, we’ll cover how to recover when a campaign goes back into learning and what to do if your results take a dip after a change.