What the Learning Health Status Means for Your Performance Groups
Every new or updated Performance Group automatically gets assigned “Learning” health status. Learning lasts for 7 days. In this time, Adspert analyzes your campaigns and prepares a strong optimization base for your chosen goal.
Here’s what you need to know.
What “Learning” Health Status Means
Learning is a short period (7 days) where Adspert analyzes your campaigns and aligns its bidding decisions with your chosen goal.
While your Performance Group (PG) health status is “Learning”, Adspert needs stable conditions to understand your data accurately. After Learning finishes, the PG’s Health Status updates automatically.
How to Know When PG Health Status Is “Learning”
Go to Control > select Performance Groups & Goals. Look at the Health column (first from the left). If you see a gear icon on the left from your Performance Group, this means it’s health status is Learning.
If you’re not sure, hover over the icon. Or start the product tour - click the hand icon from the top right side of the navigation bar.
When Does a Performance Group Enter Learning?
Performance Group’s health status turns to Learning when you:
Create a new Performance Group
Apply a major change (change goals, add or remove campaigns)
Accept a recommendation from the Assistant
Update key settings (goals, Min Bid, Max Bid, bidding strategy, or such)
This ensures Adspert can readjust properly to your business strategy.
One of the most common adjustments that triggers Learning status is when you change your PG’s goal. You can see that from Performance Groups & Goals > Locate your PG > See “Last goal change” information under its name.
What NOT to Change During Learning
To keep your advertising performance stable, avoid the following when you PG’s status is Learning:
Do not change the PG goal
Do not add or remove campaigns
Do not make major structural changes to your PG
Do not offer coupons
Do not add discounts
Do not make major price changes to your advertised products
These actions disrupt Learning and can delay optimal results.
What You CAN Change During Learning
Small improvements to your product detail pages are fine, such as:
Improving images
Updating product titles
Adjusting descriptions
In Adspert you can and should also:
Approve or reject Budget Suggestions
Approve or reject Criterion Hub suggestions from Suggestions Review
These actions do not interfere with the Learning process.
What Happens When Learning Status Ends
After the 7-day period, Adspert finishes learning about your new or updated Performance Group and automatically updates its Health status.
So you can immediately see which PGs are working well and which ones need your attention.
There are 5 health statuses:
🟢 Green = All good
🟡 Yellow = Needs some attention
🔴 Red = Critical issues are holding back performance
⚙️ Learning = New PGs or recent changes, Adspert is still learning
⚪️ Empty = PG is paused or inactive
The best part? Adspert doesn’t just flag Performance Groups that need attention. It helps you fix them. That’s where the Assistant comes in.
Use Assistant to Improve Your Performance Groups
Right below the Health indicator, you’ll see a ⚡ lightning icon and a number showing how many ready-to-go recommendations Adspert has. Click it to open the Assistant: a focused list of improvements based on your actual ad performance.
Adspert shows you where the problem is, and points you to the fix – along with actionable improvement suggestions.
Check If You Need to Adjust Your PG
After Learning status for your PG is finished, you can adjust it. But even though you can, it doesn’t mean you should.
After the learning phase is finished, we recommend you to pick one of these three options:
Leave your Performance Group structure as it is
Adjust your Performance Group’s goal value
Restructure your initial Performance Group
Keep in mind that when it comes to the Performance Group structure, it’s best to keep it as simple and stable as possible.
A simple structure does not only keep your input manageable, but in most cases also returns the best results.
To learn more about the three options listed above, read Examples on how to structure Performance Groups