Search Query, Keyword & Negative Governance

Every query needs exactly one owner, yet many accounts have never made that decision.

Broad match, Smart Bidding, and years of ad hoc keyword additions can leave the same query matching several keywords while negative lists grow only after waste is noticed. We review the search terms report, assign one owner to each query cluster, and establish the negative and match-type rules needed to maintain that ownership. You end up with a query system where you can name which keyword owns any search term, and what stops the ones that shouldn't spend. Accounts running broad or mixed match types with real query volume see the most from this. A small exact-match account where every term is already reviewed by hand rarely needs it.

A specialist routing a stream of search queries into labeled owner lanes and a tiered negative-keyword filter

Some of the 500+ brands we've worked with

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  • EY
  • Yves Rocher
  • Zorlu PSM
  • Isuzu
  • Hotiç
  • Sportive
  • Amazon
  • BMW
  • Shell
  • Hyundai
  • PepsiCo
  • Red Bull
  • Decathlon
  • MediaMarkt
  • Bayer
  • Sanofi
  • KPMG
  • GE
  • 3M
  • Domino’s
  • Lexus
  • Trendyol
  • Hepsiburada
  • Yandex

How the work runs

Raw queries become a governed system

Each record can be checked against the live search terms report. AI can cluster, flag, and draft. It cannot add a negative keyword, change a match type, or move budget.

How we hold ourselves to it

  • Every query gets exactly one owner
  • Every negative addition is logged with its reason
  • Broad match earns its reach through negative discipline
  • The search terms report gets reviewed on a schedule

  1. Mine and classify the queries

    Pull the search terms report and bucket every query by intent and theme, marking which are covered on purpose and which arrived by accident. The paid-search lead confirms the intent buckets before anything changes.

    Classified search-term set with each query bucketed by intent and theme, and intentional coverage separated from accidental.

  2. Detect internal competition

    Find every query matching more than one active keyword or ad group, and decide which one should actually own it going forward. The strategy lead assigns the single owner for each contested query.

    Internal-competition list naming every query matched by more than one active keyword or ad group.

  3. Build the negative architecture

    Decide what belongs at the account level, since that tier applies automatically across Search, Performance Max, Shopping, and more, what belongs in a shared list, and what stays campaign-specific. The client owner approves account-level exclusions before they apply broadly.

    Tiered negative architecture assigning each exclusion to account, shared-list or campaign level.

  4. Set the match-type policy

    Decide, tier by tier, where broad match earns its reach and where phrase or exact match still holds the line. The paid-search lead signs off on the policy before it is applied.

    Match-type policy stating, tier by tier, where broad, phrase or exact match applies.

  5. Apply and route

    Push the negative lists and match-type changes, and record which ad group or campaign now owns each previously contested query. A named human applies every live change to keywords and negatives.

    Applied negative lists and match-type changes with the new owner recorded for each contested query.

  6. Run the recurring audit

    Set the cadence for reviewing new search terms, refreshing negative coverage, and catching new internal competition before it spends much. The paid-search lead reviews and closes each cycle.

    Audit calendar naming the review cadence, the cycle owner and the open queue carried forward.

What lands with your team

A system that holds up between reviews

The map, register, and policy work together to keep the account from drifting back into the state we found it in.

  • Query-owner map

    Which keyword or ad group owns each query cluster, with the reasoning behind contested calls.

  • Tiered negative keyword register

    Every negative sorted into account, shared, or campaign level, with its source, owner, and date added.

  • Match-type policy sheet

    Which keyword tiers run broad, phrase, or exact match, and the reasoning behind each tier's policy.

  • Recurring audit calendar

    The review cadence, the owner for each cycle, and the open queue carried from the last review.

Before the work starts

When this work is the right next step

More query reach requires stronger controls. Broad match is built to find more of the query space than phrase or exact match, and Google's own guidance pairs it with Smart Bidding. That reach only pays off if something is filtering what comes with it. Without a negative architecture underneath, the same junk term gets added to one campaign's list and keeps showing up in every other campaign that never got the memo.

A good fit when

  • Broad match widens the query space, but nobody reviews the search terms report on a recurring schedule.
  • The same search query matches multiple active keywords or ad groups, so nobody can explain which one should own that intent going forward.
  • Several people add keywords and negatives across campaigns, yet the account has no tiered register showing the source, level, and owner of each exclusion.
  • The same query matches two or more active keywords, and nobody assigned it there on purpose.
  • Negative keywords get added campaign by campaign, so a term excluded in one place keeps spending in another.
  • Broad match was turned on for the bidding benefit, but the search terms report hasn't been reviewed since.
  • A negative meant to block a whole category only catches the one exact phrase someone happened to type.

Better handled as other work when

  • The account is small and exact-match only, while every visible search term is already reviewed by hand and no ownership conflict appears in the report.
  • Nobody on the team can open the search terms report, so a negative-keyword decision would rest on guesswork instead of classified query evidence.
  • Negative-keyword additions have no approver or recorded owner, so account-level exclusions cannot meet the method's human-approval rule.

People who own a single channel

Paid Search, Paid Social, CRO, and Programmatic each run under a named owner at Zeo. The consultants below are matched to the channel this page is about, so you can see who you'd actually work with.

Content we've produced on this topic

Articleby Metehan Urhan6 Reasons To Focus on Long Tail Keywords

Tools we use

Tools behind this work

  • Adalysis

    mines the search terms report and flags two keywords fighting for the same query

  • Airtable

    the ownership record that says which person is accountable for which query cluster

Keep query conflicts from returning

Give every search query a clear owner

Start with the current search terms report. We map contested queries, set negative tiers, and document the match-type rules that govern the next review.
Clean up your query governance

The questions we hear most

Doesn't Smart Bidding make manual negative-keyword work pointless?

No. Smart Bidding optimizes within the query space it is allowed to compete in. Negative keywords set that boundary, and automation still needs a clean space to work inside, especially under broad match.

How many negative keyword lists do you actually maintain?

As few as the tiering supports. Account-level exclusions apply broadly, shared lists cover repeatable waste across several campaigns, and campaign-specific negatives stay narrow on purpose.

Who decides a query is waste instead of a slow-building signal?

A named strategy lead uses the query's volume, cost, and early conversion signal. Ambiguous queries stay open for another review cycle while the evidence develops.

Can an AI agent add negative keywords on its own?

No. Agents can cluster queries, flag contested terms, and draft the negative list for review. A named human approves every negative addition and every match-type change before it goes live.