What is competitive reputation benchmarking?
Competitive reputation benchmarking runs identical queries and AI prompts for an entity and each peer over the same time windows, then compares them across four dimensions - search composition, AI narratives, source quality, and share of voice - so standing is measured in context, not in isolation.
Competitive reputation benchmarking measures an entity against its peers with the same instruments and the same questions. Reputation is relative, and an absolute number means little without context. The method runs identical queries – the same branded and category terms, the same AI prompts – through the monitoring tools for the entity and each peer, over the same time windows, so the comparison is like-for-like and not distorted by different methods or different moments.
The four dimensions compared
For every entity in the peer set, the same query is scored across four dimensions. Read the table across a row to see how the entity stacks up against each competitor on that dimension.
| Dimension | What it measures | Read across the peer set as… |
|---|---|---|
| Search composition | What occupies the results on the shared branded and category queries – owned, authoritative, neutral, or hostile content. | Side-by-side result mixes for the entity and each peer. |
| AI narratives | The story each entity receives in AI answers to the same prompts. | Whose narrative is stronger, more accurate, or more favorable. |
| Source quality | The authority and type of sources each entity’s presence rests on. | Who is anchored on stronger, more credible sources. |
| Share of voice | How much of the contested territory each entity’s own and aligned content occupies. | Who dominates and who is losing ground in the shared space. |
Why it is done this way
- Reputation is relative. Absolute improvement tells only half the story. Stakeholders judge an entity against its competitors, so the benchmark has to show whether it is gaining or losing ground against them.
- The method is held constant. The same queries, the same prompts, and the same time windows apply to every entity, so differences reflect real standing and not measurement noise.
The instruments
Five Blocks runs peer benchmarking with IMPACT™ across search and AIQ™ across the AI engines, holding the queries and time windows constant. AIQ tracks what the major AI models say across eight AI engines – ChatGPT, Copilot, Gemini, AI Overview, Perplexity, Grok, Claude, and Google AI Mode. IMPACT’s search analysis covers 500 locations across 69 countries in 23 languages, so the same benchmarking runs consistently across markets.
Last reviewed: 20/05/2026