Negative keyword strategy: stop wasted ad spend

What is a negative keyword and why does it matter more in 2026?

A negative keyword is an exclusion rule that stops your ads from showing on specific search terms. Used well, it keeps your ad away from the wrong person and stops you burning budget, it's the core tool for sculpting a campaign around the right intent. In 2026 this matters more because Google keeps pushing advertisers toward broad match and Performance Max: the wider the net, the greater the risk of falling into searches that are semantically related but commercially irrelevant.

The conclusion is simple: the broader the matching gets, the more important your negative keyword list becomes as a counterbalance. The good news is that most waste clusters in a few recurring terms, finding and cutting them is a fast win. The numbers here are illustrative; real waste varies by account.

A layered negative keyword architecture

Best practice is not to dump every negative into one list, but to split them into three layers:

• Account level. Terms that are never relevant: competitor names you don't want to bid on, unrelated industries, job-seeker queries (e.g. "jobs", "salary").
• Campaign level. Shapes cross-campaign traffic: such as stopping a brand campaign from cannibalizing non-brand. Since 2023 you can add these without Google Support; up to 10,000 negatives per campaign.
• Ad group level. Used sparingly for fine-tuning within theme-based structures; it clarifies overlap between groups.

The search terms report: weekly hygiene

A negative list isn't "set and forget." On high-spend accounts, review the search terms report at least once a week.

1. Open the last 7 days of the search terms report; sort by spend and conversions.
2. Flag terms that are irrelevant but spending; add them as negatives at the right layer (account/campaign/group).
3. Google now hides a significant share of terms behind privacy thresholds, fill the gap with landing-page analytics and GA4 channel breakdowns.
4. Tag each negative you add with a reason so the team can trace the decision back.

N-gram analysis: catch waste at the single-word level

Looking at full queries one by one is slow and misses the pattern. N-gram analysis breaks search terms into single words (1-gram), two-word phrases (2-gram) and three-word phrases (3-gram), then reviews performance at the fragment level. That way you see at a glance how a single word like "free" or "what is" burns budget across dozens of different queries, a pattern you'd never catch by reading full search terms.

The match-type trap: why broad negatives are dangerous

Negatives have match types too, and they behave differently from positives. A broad-match negative blocks the whole query no matter what order the word appears in, which is why it's overly aggressive. The classic mistake is making "free" a broad negative; that cuts the unwanted "free PDF" but also valuable queries like "free trial" and "free consultation."

The limit of negative keywords in Performance Max

Performance Max now natively supports campaign-level negative keywords (up to 10,000 per campaign), but there's a key limit: PMax negatives apply only to Search and Shopping inventory. Display, YouTube, Gmail and Discovery placements stay outside it.

• Independent analyses show negatives reduce PMax waste by only 15-25%, the large remainder goes unaddressed.
• Depending on the account, 40-70% of spend (the Display/YouTube side) can't be controlled with negative keywords.
• So in PMax, pair negatives with brand/content exclusions, account-level negative lists and tight conversion data.

How Ads Sensor finds negative keyword opportunities

Sweeping search terms by hand every week gets hard fast across multiple accounts. Ads Sensor unifies Google Ads and GA4 data in a single panel; it reads the search terms report in seconds, catches budget-wasting patterns (n-gram themes, irrelevant queries) and produces prioritized, reasoned negative keyword recommendations. With an approve-and-apply flow it applies them directly to the Google Ads API and automatically tracks the before/after impact of each exclusion. Open the panel to see the wasting terms on your own account. The numbers are illustrative; real savings vary by account.