Avouch

//.citations

The mentions an engine actually trusts.

AI doesn't recommend from your homepage. It pulls from everywhere else.

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FIG. 01What AI says

User prompt: Who do people rate for wealth advice in Surrey?

ChatGPT
Based on community discussion and review platforms, Harbourview Wealth comes up for work with business-owning families. …

★ CITED FROM OFF-SITE, NOT YOUR OWN PAGE

Illustrative example — not a real client
//.the_problem_001

Off-site is no longer just about backlinks.

The highest-value work is often off your own site entirely. Engines weight unlinked brand mentions across many independent sources — research shows near-zero correlation between backlinks and AI citation. So the job isn't link-building; it's earning the mentions the engines lean on when they answer.

//.how_we_work_002

How we work

  1. Find where the engines look

    We reverse-engineer which sources the engines actually cite in your sector — YouTube, Reddit, Wikipedia, directories, reviews, trade press — and in what priority.
  2. Earn the mention

    Genuine presence in the places that matter: long-form explainers, real participation in the right communities, trade-press placements, review-platform standing.
  3. Mentions before links

    We work mentions-first, because that's what the engines weight — links follow, they don't lead.
//.what_you_get_003

What you get

A citation-source map

The specific off-site sources the engines cite in your sector, ranked by how much each one moves the answer.

Earned placements

Real mentions in the sources that count — built, not bought — on a steady cadence.

A review & community footprint

Standing on the review platforms and in the communities your buyers (and the engines) actually read.

//.the_work_004

The work, in order

  1. Citation mining

    Which domains and platforms the engines pull from when they answer your buyers' questions.
  2. Gap analysis

    Where rivals are cited and you're absent — ranked by the influence of each source, not its domain authority.
  3. Earn placements

    Long-form, community presence, trade press and reviews, worked in priority order.
  4. Track appearance

    We watch the lag from a placement landing to a citation appearing, per engine.
//.the_framework_005

Signal Intelligence → Deployment → Tracking

Off-site runs in three moves: find the sources that matter, earn presence there, and track what shows up.

Signal Intelligence

The off-site sources the engines actually cite in your sector.

Signal Deployment

Earned mentions across those sources, mentions before backlinks.

Signal Tracking

Placement-to-citation lag, measured per engine — closed loop.

//.how_we_differ_006

How we’re different

DimensionAvouchTypical agency or tool
The aimMentions the engines citeBacklinks for a domain score
Source choiceRanked by AI influenceRanked by domain authority
MeasurementPlacement → citation lag, per engineLinks acquired, then silence
//.the_tooling_007

Mapped by the Citation Intelligence Platform.

The platform mines which sources the engines cite in your sector and tracks the lag from a placement landing to a citation appearing — so off-site work is aimed, and provable.

See the platform →

Runs through the retainer alongside the content engine — the two together are what earns the citation.

//.questions

Citations questions

Is this link-building?
No. Links are a small part of it. The engines weight unlinked brand mentions across many independent sources far more heavily, so we work mentions-first — earned presence in the places the engines actually cite.
Which sources matter most?
It varies by sector, but YouTube, Reddit, Wikipedia, trade press and review platforms recur. We don't guess — the platform mines which sources the engines cite for your buyers' questions and we work them in priority order.
Do you buy placements?
No. Mentions are earned through genuine presence and contribution. Bought or fake signals are exactly what the engines (and regulators) are built to discount.

AI can't recommend what it doesn't know.

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