AI Visibility Proposal & SOW Template for Agencies
A reusable structure for AI visibility proposals and statements of work — the scope lines, deliverables, and success criteria that close deals without promising rankings you cannot control.
An AI visibility proposal should follow a fixed structure: the problem framed with a real baseline, the scope broken into named deliverables, the success criteria written as presence and trend goals, and terms that explicitly avoid guaranteeing citations. The baseline from a Domain Check is the most persuasive part of the whole document.
What makes an AI visibility proposal different
A standard SEO proposal can lean on familiar promises — rankings, traffic, leads. AI visibility cannot, because no one controls whether a model cites a given query. That constraint is actually an advantage: it forces a proposal built on a verifiable baseline and honest, delivery-based success criteria, which is exactly the kind of proposal sophisticated buyers trust.
The single strongest move you can make is to open with a real baseline. Run a free Domain Check on the prospect’s domain and show them, in the proposal, the queries they are already cited or mentioned on — and the ones competitors own that they do not.
The proposal structure
Use the same skeleton every time so proposals get faster to produce and easier for clients to read.
- Situation: the prospect’s current AI visibility, shown with the baseline, not asserted.
- Opportunity: the gap of queries competitors are cited on that the prospect could pursue.
- Approach: how you will work — baseline, query bank, monitoring, reporting.
- Scope & deliverables: the named, verifiable outputs.
- Success criteria: framed as delivery and direction, never guaranteed placements.
- Cadence & terms: reporting rhythm, length, and what is out of scope.
- Investment: pricing presented as tiers.
Scope lines: what to put in the SOW
Every scope line should be something the client can later confirm was delivered. Pair each deliverable with the success criterion that proves it happened.
| Scope line | Deliverable | How success is measured |
|---|---|---|
| Baseline audit | Query-level snapshot of current presence | Audit delivered and accepted by the client |
| Query bank | Curated, intent-tagged query list | Bank built and maintained each period |
| Monitoring | Scheduled refresh of cited / mentioned queries | Data refreshed on the agreed cadence |
| Competitive tracking | Competitors on shared queries | Competitive view updated each report |
| Reporting | Monthly summary + quarterly review | Reports delivered on schedule |
| Iteration | Recommendations tied to real queries | Recommendations shipped per the agreed scope |
Writing success criteria you can stand behind
The temptation is to promise a number of citations or a guaranteed query. Do not. Frame success around things you control and can prove:
- The baseline is established and maintained as a reference point.
- The query bank grows and stays tagged by intent.
- Reports are delivered on the agreed cadence with real, traceable numbers.
- The trend of distinct queries the domain is cited or mentioned on is tracked over time — described as a direction of travel, not a guaranteed figure.
- Competitive context is refreshed each period.
This framing protects both sides: the client gets accountability on delivery, and you never sign up to control model behavior you cannot control.
Terms and exclusions to spell out
- No guarantee of any specific AI citation, ranking, or placement.
- What counts as in-scope iteration versus a change order.
- Who owns the monitored projects and reporting accounts.
- How tooling cost is handled — absorbed or passed through.
- The reporting cadence and what triggers an out-of-cycle update.
From proposal to delivery
The proposal should hand off cleanly into the rest of the engagement. The scope lines become the first week of your 30-day onboarding plan, the pricing follows your pricing framework, and if you are selling a repeatable offer, the whole thing slots into a productized GEO service. To compare what backs the deliverables, compare the platforms.