When a competitor gain deserves attention

Competitor Benchmarking & Regression Alerts

A competitor alert fires only after its lead clears the agreed variance threshold across the matched prompt set, with the source difference attached.

Each brand faces the same questions, platforms, markets and run conditions. Reviewers inspect the sources behind any gap to distinguish a persistent displacement from category drift, source changes or an isolated answer. You get an alert only when a competitor's gain survives normal answer variance, with the exact sources behind the shift named. Category and brand leads who need to know whether a competitor's AI-answer gain persists before reacting to it.

Figure watching two brand lines cross on a monitoring panel with an alert bell

Some of the 500+ brands we've worked with

See all references
  • Marks & Spencer
  • Apsiyon
  • CHIP Online
  • HangiKredi
  • İstanbul Gedik Üniversitesi
  • Doritos
  • GS Store
  • Amazon
  • BMW
  • Shell
  • Hyundai
  • PepsiCo
  • Red Bull
  • Decathlon
  • MediaMarkt
  • Bayer
  • Sanofi
  • EY
  • KPMG
  • GE
  • 3M
  • Domino’s
  • Lexus
  • Trendyol

From governed set to a justified alert

An alert has to clear the variance threshold

Comparable brands, eligible questions, event definitions, and repeat rules are fixed before cross-brand answers and sources are collected.

How we hold ourselves to it

  • Same questions, same conditions
  • Gap adjusted for variance
  • Sources checked before copying
  • No single category rank

  1. Normalize the comparison set

    We agree competitor roles, category boundaries, market scope, aliases and explicit exclusions for each question family. The client category owner approves who is comparable for each prompt family and market.

    Governed competitor register with rationale and owner.

  2. Stratify prompts by intent and market

    We build a matched prompt panel and freeze event definitions, platforms, modes, markets and repeat policy. The measurement lead approves comparability, denominators and holdouts.

    Comparable opportunity matrix naming the eligible brands and the runs each share is counted against.

  3. Capture repeated platform results

    Repeated answers and exact sources are collected for every eligible brand-question pair. An operator audits matrix completeness and applies the same validity rule to every brand.

    Cross-brand answer corpus with complete run conditions.

  4. Classify presence and source portfolios

    Reviewers classify mention, recommendation and citation events and resolve the exact source portfolio. The calibrated analysts approve ambiguous events and exact-page resolution.

    Brand-event table and cited-source inventory.

  5. Benchmark source portfolios and event shares

    We compare source relevance, credibility, concentration, support and coverage alongside event shares. Source and domain reviewers approve classification and challenge weak evidence.

    Category source-portfolio benchmark with explainable gaps.

  6. Translate gaps into ethical opportunities

    We adjust conclusions for observed variance and turn persistent, controllable differences into bounded tests. Zeo and client owners approve only controllable opportunities with an explicit stop rule.

    Stability-adjusted opportunity map with action and non-action decisions.

The regression brief you get

A regression brief that says who moved, where, and with what evidence

The handoff shows persistent displacement, source-portfolio shifts, category changes, and the bounded tests worth running, plus the gaps too weak to act on.

  • Category visibility benchmark

    A like-for-like category baseline sliced by platform, prompt family, market and event type.

  • Competitor citation portfolio

    Where each brand is mentioned, recommended and cited across the matched opportunity set.

  • Stability-adjusted opportunity brief

    A stability-adjusted set of gaps with bounded tests, expected learning and explicit non-actions.

  • Ethical source and content action plan

    The domains and exact pages supporting category answers, including concentration and support quality, paired with the approved source and content actions.

  • Platform-specific mention share

    Use only within the matched opportunity set. Mention share is not recommendation share.

Before the team follows a rival

A competitor gain needs comparable evidence

Rivals may appear more often while your brand drops out of familiar questions. This method establishes whether the movement survives matched conditions and an honest count of the runs behind it.

A good fit when

  • A competitor gap is visible but unexplained — Question coverage, recommendation context, sources, and ordinary volatility are still mixed together.
  • The comparison mixes unlike brands or prompts — Category membership, eligible questions, or market conditions differ across the brands being compared.
  • Visible tactics are being copied without evidence — A competitor uses a format or source, but no controlled comparison shows that it explains the observed gap.
  • Competitor roles differ by prompt family — We name direct, alternative, and reference competitors and record why each belongs.
  • Every brand faces the same eligible questions — We hold platform mode, market, repeat policy, and event definitions constant.
  • One category rank hides different events — We compare mention share, recommendation coverage, and citation exposure before reading one category rank.
  • The exact sources behind the gap remain ungrouped — We group cited domains and pages by type, credibility, relevance, diversity, concentration, and support.

Better handled as other work when

  • You want one category rank from incomparable evidence — We withhold the league table when prompt eligibility, run conditions, brand roles, or sample strength differ.
  • You need one guaranteed rank across platforms — Each engine, prompt family, and source pool keeps its own result because cross-platform evidence is not one rank.

People who watch how AI cites a brand

GEO work starts with recording what AI answers actually say about a brand today, then moves to the parts you can influence. The consultants below work on the specific capability this page covers.

Tools we use

Tools behind this work

  • Peec AI

    runs every tracked competitor against the identical prompt panel and conditions

  • Profound

    runs every brand in the register against the same panel, which is this page's matched condition

  • Semrush

    checks whether a rival's answer gain is matched by an ordinary search gain, or is specific to answers

  • SE Ranking

    tracks AI Overview appearances for the matched set, one of the surfaces the benchmark covers

  • Ahrefs

    surfaces a competitor's own cited sources, so a gap can be checked against a source change

  • Jupyter

    runs the variance-threshold check that decides whether a gap clears the bar for an alert

A gap that survives variance is worth a response

Decide whether the competitor gain merits a response

Name the competitors, question families and markets behind the concern. We will construct the matched set and show whether the gap outlasts ordinary variance before recommending an investigation.
Assess the competitor gap

Questions we hear

How do you choose competitors for an AI visibility benchmark?

We assign direct competitors, substitutes and reference organizations for each question family and market, then the client category owner reviews the rationale and exclusions.

Can one overall score summarize category leadership?

It would hide the distinctions needed for a decision. Mention, recommendation, citation, source support and stability answer different questions, so each one keeps the runs it was counted against.

Why adjust a competitor gap for stability?

Generative answers move between runs. We call a gap persistent only after it clears the repeated baseline range. The matched slice also needs enough observations. Until both conditions hold, it stays an open signal.

Should we copy the format or sources used by the leader?

First we test whether the visible difference corresponds to a relevant evidence or coverage gap. Correlation by itself cannot establish the ranking mechanism, so some apparent opportunities end with a deliberate decision to do nothing.