Labelizer groups products into performance buckets so you can quickly see which products are above, near, or below the target you set.
Each Labelizer project has its own target, settings, runs, and results.
What buckets mean
Labelizer compares each product against the target you configured during setup.
Typical bucket groups are:
Over-index: products performing clearly above the target.
Index: products performing around the target.
Near-index: products close to the target but not clearly above it.
Under-index: products performing below the target.
No index: products without enough usable data for a performance label.
The exact result depends on your selected metric, target, date range, conversion lag, and filters.
ROAS and CPA targets
If your project uses ROAS, higher values are usually better.
If your project uses CPA, lower values are usually better.
Labelizer uses the selected target to decide whether a product is performing above, near, or below expectation.
Why products can end up in No index
A product may be placed in No index when Labelizer cannot calculate a reliable bucket.
Common reasons are:
The product has too little traffic.
The product has no conversions in the selected date range.
The product does not match the feed or campaign filters.
The product was not active during the selected period.
Conversion lag means recent conversions are not counted yet.
No index does not always mean something is wrong. It often means there is not enough data for a confident label.
Review run results
Open the Labelizer project and review the latest run.
Check:
When the run started and finished.
Whether the run succeeded or failed.
How many products were processed.
How products were distributed across buckets.
Whether the results match the account and filters you expected.
What to do with the results
Use the buckets to decide which products need attention.
For example:
Over-index products may deserve more budget or visibility.
Under-index products may need bid, feed, price, or landing page review.
No index products may need more data before you act.
Do not treat the buckets as a replacement for campaign context. Use them as a starting point for product-level decisions.