Post-Deployment Optimization (Learning Phase)
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Last updated
Deploying a new campaign structure created using Karsa Labelizer to Google Ads is a significant step. After switching the clusterization to and properly setting up your campaigns (whether Standard Shopping or Performance Max), it is key to understand what happens next, and how to approach subsequent optimization. One of the most important concepts is the learning phase of Google Ads algorithms.
When you launch a new campaign or make a fundamental change to an existing campaign that uses Google Ads automated bidding strategies (such as Target ROAS - tROAS, Maximize Conversion Value, etc.), the system needs time to "learn" how to best achieve your goals. During this time:
Algorithms collect data: Google analyzes impressions, clicks, conversions, and other signals associated with your new campaign structure.
Various bids are tested: The system experiments with different bid levels to find out what works best for a given segment of products.
Performance may fluctuate: During the learning phase, campaign performance may be unstable – you may notice fluctuations in ROAS, conversion volume, or costs. This is normal and expected behavior.
Generally, count on a learning phase lasting approximately 2 to 4 weeks from the launch of new/significantly changed campaigns.
MOST IMPORTANT RULE: Avoid fundamental changes in campaign settings during these first 2-4 weeks!
Frequent or large changes can disrupt, prolong, or even restart the learning process, which delays achieving stable and optimal performance. Changes you should avoid include:
Changes to bidding strategy goals: For example, frequent adjustments to the target ROAS value.
Significant changes to daily budget: Avoid abrupt increases or decreases (small adjustments of +/- 20% are usually okay, but with caution).
Changes to campaign structure or ad groups/asset groups.
Extensive changes in targeting (geographic, demographic, etc.).
Adding a large number of new negative keywords (add only those clearly irrelevant).
What you can do:
Monitor performance: Track key metrics to stay informed, but don't make hasty conclusions from short-term fluctuations.
Check feed quality: Make sure your product feed in GMC is in order and error-free.
Ensure proper conversion measurement: Accurate measurement of conversions with their values is absolutely crucial for the functioning of automated bidding.
Once the initial learning phase has passed and campaign performance begins to stabilize, you can proceed with gradual optimization:
Look at the actual ROAS, cost per conversion, conversion volume, and their total value for individual campaigns (clusters).
If you started with a different strategy (e.g., Maximize Conversion Value without a target), and now have enough conversion data (ideally 15-30+ over the last 30 days for a given campaign), you can switch to the Target ROAS strategy.
Setting the initial tROAS target:
Be realistic: Don't set the tROAS target too high beyond what the campaign was actually achieving. Too high a target can significantly limit impressions and spending.
Base it on current performance: A good starting point is to set the tROAS target close to the actual ROAS achieved in recent weeks, or slightly above your break-even ROAS.
Example: If the campaign was achieving a ROAS of 400% and your long-term goal is 600%, start with a tROAS of, for example, 350-450% and gradually increase.
Gradual adjustments to the tROAS target:
Change the tROAS target slowly and in small steps (e.g., by +/- 10-20% of the value).
If the campaign consistently exceeds the tROAS target: You may consider slightly lowering the target to potentially gain more conversions and volume (even at the cost of slightly lower efficiency).
If the campaign consistently fails to reach the tROAS target: You may consider slightly increasing the target (making it stricter) to improve efficiency, or look for problems elsewhere (feed quality, prices, competition, technical issues on the website).
Give it time: After each tROAS adjustment, wait at least 1-2 weeks before evaluating the impact and making another change. The algorithm needs time to adapt.
Change the daily budget slowly, ideally not more than +/- 20% every few days (e.g., once every 5-7 days). Avoid sudden large jumps.
Increase the budget for campaigns that meet or exceed the tROAS target and have potential to grow (e.g., they are not losing impression share due to budget).
Consider reducing the budget for campaigns that consistently fail to meet the tROAS target and other optimization steps are not helping.
Search queries: Regularly check the search query report in Google Ads and add irrelevant terms as negative keywords.
Feed optimization: Continuously work on the quality of data in your product feed in GMC (names, descriptions, images, prices, availability, etc.).
By following these procedures – from respecting the learning phase to gradual, data-supported adjustments – you maximize the chance of successful and long-term sustainable results for your campaigns structured using Karsa Labelizer.
Analyze the collected performance data for the past few weeks (ideally at least 30 days with a sufficient number of conversions – see ).
Karsa dynamic movements: Remember that if you have dynamic movements enabled, Karsa Labelizer will continuously optimize product placement. Monitor the .