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When an AI model answers a category question, it doesn’t just pick one brand — it typically produces a short list. Every position on that list is held by someone. Peakmark’s competitor analysis shows you who holds each position in your category, how often, and across which models — turning what used to be an invisible competitive dynamic into a daily-updated dataset you can act on. Understanding your competitor’s share of voice isn’t about benchmarking for its own sake; it’s about knowing exactly which gap to close, on which model, with which type of content or coverage.

What competitor share of voice means

Share of voice (SOV) in AI answers measures how often a brand is mentioned in AI responses to category-relevant prompts, expressed as a percentage of all prompts tracked. If Peakmark sends 100 prompts and your top competitor appears in 62 of the AI responses, their SOV is 62%. Your number might be 24%. That 38-point gap is the competitive picture. SOV is tracked per brand and per model, because AI models form their recommendations from different sources and behave differently. A competitor might dominate on ChatGPT while you’re nearly tied with them on Perplexity — a pattern that points directly to where leverage exists.

What the competitor dashboard includes

Brand list and setup

During onboarding, you define the competitors you want to track. You can add or adjust this list at any time. Most customers track between three and eight direct competitors alongside their own brand.

Share of voice: table and chart view

The competitor dashboard presents SOV two ways. The table gives you the precise numbers — every brand, every model, every day — so you can track exact changes. The chart visualizes the relative positions over time, making it easy to spot when competitive positions are shifting.

Trend lines per competitor

Each competitor’s SOV is plotted as a trend line over time. A rising line tells you a competitor is gaining AI trust — and that you should investigate why. A falling line can signal an opportunity to take share. Flat lines often mean the competitive landscape is stable, which is either good news or a sign that nobody is actively doing GEO work.

Citations tied to competitor mentions

The competitor dashboard connects directly to the Citations view. When you see a competitor with high SOV, you can click through to see which sources and web pages AI models cited when recommending them. This is where competitor analysis becomes a direct action plan.

How to use the data

Find the model with the largest gap

Not all models are equally important for your category, and your competitive position differs across them. Start by identifying the model where the gap between you and the SOV leader is largest — that’s where targeted GEO effort returns the most because the delta you can close is biggest.

Trace competitor success back to its sources

A competitor with 60%+ SOV on ChatGPT earned that position by appearing in the sources ChatGPT trusts. Open the Sources & Citations view and filter for competitor-associated citations. The domains and pages that appear most often are the publications you need a presence in.

Monitor competitor spikes

A sharp upward move in a competitor’s SOV is almost always traceable to a specific event: a major press piece, a product launch that generated coverage, a viral Reddit thread, or a high-authority listicle placement. Catching these spikes early — and understanding what caused them — tells you what works in your category before you have to discover it yourself.
When a competitor’s share of voice rises sharply, check the Sources & Citations tab to see what new coverage drove the change.

Share of Voice concept

Understand how SOV is calculated and what makes a meaningful change in your score.

Sources & Citations

See which web pages and publications AI models cite when recommending brands in your category.