Use case

AEO for agencies

Track AI visibility for every client and report it under your own brand, on an AI visibility platform you can run at agency scale.

Agencies tend to feel the shift to AI search first, because clients start asking why a competitor shows up in ChatGPT and they do not. AEO turns into a service line: measure each client's presence across the answer engines, find the gaps, and show the work.

The hard part is doing that across many clients without paying per seat for each one. A platform with white-label support changes the math, so the dashboards carry your brand instead of a vendor's.

Prompts that matter here

  • best [client category] companies
  • [client] vs [competitor]
  • is [client] worth it

What to do

  1. 1

    Run a prompt set per client

    Build a focused list of the questions each client's buyers actually ask, and track it on a schedule so changes stand out.

  2. 2

    Benchmark against named competitors

    Share of voice against specific rivals is the metric clients understand. Show who gets cited instead of them, and on which prompts.

  3. 3

    Turn gaps into a retainer

    Every prompt where a client is missing is a concrete content brief. That is the bridge from reporting to billable work.

  4. 4

    White-label the dashboards

    Put the reporting under your own brand and domain so the visibility data looks like part of your service, not a third-party tool.

Where AEOTrace fits

AEOTrace has white-label support, so you can run one instance for an entire book of clients, brand the dashboards as your own, and skip the per-seat pricing that does not scale across an agency.

FAQ

Common questions

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