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What does a quarterly reputation review look like?

Quick answer

A quarterly reputation review is a structured strategic-adjustment session covering four areas of the program across a three-month window: SERP composition and AI narrative trends, Wikipedia activity, peer benchmarks, and a full work-completed inventory with key wins, risks, and next-quarter recommendations. It sits between the monthly operational report and the annual planning cycle and is typically presented to the chief communications officer and senior stakeholders.

Quarterly reviews serve a strategic-adjustment function rather than an operational one. They aggregate three months of data to surface directional shifts that are not visible in any single monthly report, and they set or revise priorities for the quarter ahead. The typical meeting involves the chief communications officer and any senior stakeholders the client wants included.

Quarterly reputation review cadence: three monthly data points (SERP snapshot, AI engine check, Wikipedia edits, peer scores) feeding.
Each month produces an operational report; at the end of the quarter, three months of data aggregate into the QBR — the strategic-adjustment session that sets priorities for the quarter ahead.
SERP composition trends
A cross-quarter view of where the picture has improved, deteriorated, or held steady. The goal is to identify directional movement, not just a snapshot of the current state, so that patterns invisible in a single month become clear over the three-month arc.
AI narrative shifts
How engine responses have moved across the quarter, with specific examples drawn from the eight engines AIQ currently tracks: ChatGPT, Copilot, Gemini, AI Overview, Perplexity, Grok, Claude, and Google AI Mode. This section highlights whether the brand narrative in AI is converging or diverging with the search narrative.
Wikipedia activity summary
A concise account of any major Talk-page work, edits accepted, edits reverted, and the current article state. Wikipedia’s SERP prominence and its role as a primary source for AI engines make its quarterly trajectory a material reputational data point.
Peer benchmark snapshot
Where the client now stands relative to the named peer set on the metrics the program tracks. A quarterly benchmark reading shows whether the relative position is improving or eroding, independent of absolute score movement.
Work completed
A clear inventory of what was executed during the quarter against the agreed program objectives, providing accountability and a factual basis for the wins-and-risks discussion that follows.
Key wins and risks
Wins worth noting for executive attention and risks worth flagging before they compound. This section is deliberately brief and signal-focused, not a comprehensive recap of every activity.
Next-quarter recommendations
Proposed adjustments to scope, focus, or tactics based on what the quarter’s data has shown. These recommendations are grounded in the trends and benchmarks reviewed earlier in the meeting, not produced in isolation.

Last reviewed: 19/05/2026

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