Search Term Report Miner
A Search Term Report from a mature account is 50,000+ rows. Sellers download it,
open Excel, scroll for 20 minutes, find 4 negatives, give up. Meanwhile real
money leaks: terms with 30+ clicks and 0 orders, exact-match converters stuck
in broad campaigns, and dead clusters that drain $200/day. This skill carves
the file into 4 surgical buckets and outputs a Bulk Operations upload ready to
submit.
When to use this
- Monthly PPC review and you want a clean negative sweep
- Account spending $3K+/month on PPC with ACoS drift
- New product 60 days post-launch ready for the first harvest pass
- Pre-Q4 cleanup. Push wasted spend out before peak
The framework. The Four Buckets
Pull the Search Term Report (60-day window). For every search term, route to
exactly one bucket based on click and order thresholds.
| Bucket | Filter | Action |
|---|
| 1. Negative Exact | Clicks >= 10, Orders = 0, ACoS = blank | Add as Negative Exact at campaign |
| 2. Negative Phrase | 3+ terms share root, combined clicks >= 25, orders <= 1 | Add root as Negative Phrase |
| 3. Exact Harvest | Orders >= 2, ACoS < target ACoS, term not already exact | Move to new exact-match campaign |
| 4. Hero Scale | Impressions >= 1000, CVR well above your account average, ACoS < target | Increase budget + bid +20% |
Anything else: leave alone.
A note on the Hero gate: there is no universal "good" CVR. It varies hugely by
category, price, and product. Do not hardcode a fixed number like 12%. Instead,
compare each term to YOUR account or category baseline. A practical hero gate is
roughly 1.5x to 2x your average CVR for that product. Compute your baseline
first, then set the gate from it.
Step by step
-
Download the STR. Advertising > Reports > Sponsored Products > Search Term
Report. Date range: last 60 days. Format: CSV.
-
Set the target ACoS. Usually 25-35% depending on margin. This is the
threshold for bucket 3 and 4.
-
Apply Bucket 1 filter. Clicks >= 10 AND Orders = 0. Export the search
term column. Format as Negative Exact rows for Bulk Operations.
-
Cluster for Bucket 2. Group remaining 0-1 order terms by shared 2-word
root. If a root cluster has 25+ combined clicks, add the root as Negative
Phrase.
-
Apply Bucket 3 filter. Orders >= 2 AND ACoS < target. Check each term is
not already an exact keyword in any campaign. Format as new exact-match
campaign rows.
-
Apply Bucket 4 filter. Impressions >= 1000 AND CVR well above your
account average (roughly 1.5-2x your baseline for that product) AND ACoS <
target. These are scale candidates. Generate bid +20% rows.
-
Build the Bulk Operations file. 4 sheets, one per bucket. Use Amazon
Bulk Sheet template columns.
-
Run the quality check, then upload to Campaign Manager.
Output format
## STR Mining Output. [Account] [date range]
**Summary**
- Total search terms analyzed: [N]
- Bucket 1 (Negative Exact): [N] terms, wasted spend last 60d: $[X]
- Bucket 2 (Negative Phrase): [N] roots
- Bucket 3 (Exact Harvest): [N] terms, projected exact-match orders/month: [N]
- Bucket 4 (Hero Scale): [N] terms
**Bulk Operations file structure**
Sheet 1: Negative Exacts
Campaign | Ad Group | Negative Keyword | Match Type
[rows]
Sheet 2: Negative Phrases
[rows]
Sheet 3: Exact Match Harvest. New campaigns
Campaign | Ad Group | Keyword | Match Type | Bid
[rows]
Sheet 4: Hero Scale. Bid increases
Campaign | Ad Group | Keyword | Old Bid | New Bid
[rows]
Worked example (illustrative)
The figures below are an example to show how the buckets shake out, not a
benchmark to expect. Your term counts, CVR, ROAS, and savings depend entirely
on your account.
Account: home goods seller, 42 SKUs, $8,400/month PPC spend. 60-day STR has
38,200 unique search terms. After parsing:
Bucket 1: 184 negative exact candidates. Wasted spend = $1,847 over 60 days,
or $924/month immediately saved.
Bucket 2: 12 phrase roots like "cat", "for dogs", "wholesale". 412 clicks, 8
orders. Adding negative phrases blocks 200+ wasted clicks/month.
Bucket 3: 67 exact-match harvest candidates. In this example the harvested
terms convert well above the account average and move to exact campaigns at
1.2x bid. The incremental-orders and ROAS figures you would model here are
account-specific. do not assume a fixed order count or a particular ROAS. run
the projection off your own term-level CVR and AOV.
Bucket 4: 14 hero terms. +20% bid aims to move them from mid page 1 toward the
top of search.
Total projected impact in this scenario combines the negative-keyword savings
with the harvested-term upside. Both are illustrative. compute your own numbers
from your account data rather than carrying these over.
Quality check
- Date range is 60 days, not 30 (need volume for cluster math)
- Target ACoS set before bucketing, not after
- Bucket 3 harvest terms confirmed not already exact in any campaign
- Negative phrases checked for accidental brand cannibalization
- Bulk file uses correct column headers per Amazon template
Common mistakes
- 30-day STR. Not enough volume per term. Bucket 2 cluster math breaks down.
- No target ACoS. Bucket 3 and 4 lose their gate, you scale unprofitable terms.
- Adding negative phrases without checking brand terms. Easy to accidentally negative-match your own brand variant.
- Harvesting terms that already exist as exact. Creates internal bid wars.
- Skipping Bucket 4. Most sellers focus on cutting waste and miss the scale upside, which is often the larger lever.
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