The monthly AI search report: what we send and what we leave out

Most AI search reports are too long and say too little. They show twelve charts, a table of prompts and a paragraph of adjectives. The reader closes the file without knowing what to do.

Here's the structure we use for the monthly report, and the things we've learned to leave out.

One page, four questions

Every report answers four questions in plain language:

Are engines naming us? Visibility and Share of Voice, against the previous period and against named competitors.
Are the right pages cited? Page-level citations, and which pages gained or lost.
Did traffic arrive? AI-referred visits and conversions.
What did we do, and what's next? The actions taken, the actions queued.

If a chart doesn't help answer one of those, it goes in an appendix or gets cut.

Open with a verdict

The first lines are a short assessment in ordinary words. "Visibility rose on ChatGPT and Perplexity and fell on Gemini. The Gemini drop traces to a retired product page that engines still cite. We've replaced it and expect to see the effect next month."

Don't write "expect to see growth." Say what you know, what you did and what you'll check. Commit to actions, not outcomes.

Section: visibility

Show three things: Visibility Score or Share of Voice this period and last, the same for two or three competitors, and a per-model breakdown. Use the same prompt panel as the previous month. If you've changed the panel, say so at the top and don't compare directly.

Promptwatch's A/B period comparison and heatmaps make this quick. Include a sentence explaining any change larger than normal noise. We have no sourced rule for what counts as noise, so we judge from each client's own history.

Section: citations

List the pages that gained and lost citations, with a note on why where known. Mention new third-party sources that began citing the brand, and any inaccurate ones found.

Citation analytics and Citation Trends give the raw material: per-page rates, first cited, ramp-up days, peak and decay half-life. For the report, translate them. "The comparison guide has held its citation rate for three months. The pricing explainer is fading and is first in the refresh queue."

Section: traffic

AI-referred visits and conversions from visitor analytics, shown as a floor, with a note on known attribution gaps. We explain the limits in why AI referral traffic gets misattributed. Never present AI traffic as exact.

If conversions are low in absolute terms, say so. Credibility compounds, and an honest small number beats an inflated one.

Section: technical health

One line each on crawler access, errors and anything that changed. "No new crawl errors for GPTBot, OAI-SearchBot or ChatGPT-User. One 403 spike from a firewall rule, fixed on the 14th." Agent Analytics logs make this simple to write.

Section: actions

A table with three columns: what we did, what we'll do next month, what we need from you. Keep each to a line. The Action Board in Promptwatch keeps this list live, with assignees and comments, so the report is a view of work already tracked.

What we leave out

Vanity totals. Raw mention counts with no context.
Screenshots of single answers. They invite arguments about one run.
Sentiment charts without commentary. Include sentiment only with an explanation of the lowest responses.
Competitor trivia. Name competitors only when they affect a decision.
Forecasts. We don't have grounds for promising numbers.

Delivery

Promptwatch can produce PDF reports from any dashboard, schedule PDF reports and export to Excel or CSV. Custom reports and the Looker Studio connector come on Professional and all agency plans. We send a PDF with a short cover note, and keep a live dashboard available for people who want to explore.

White-label PDF exports and a client portal are available for agencies per the product's own description. We don't attach a plan to that, so check with Promptwatch before you assume.

Automating the boring parts

Weekly digests and scheduled reports save time. Promptwatch also offers an MCP server and an API, and TreeHouse's published case study describes automating weekly reporting with the MCP. We use similar automation to draft the data sections, then write the verdict and actions by hand. People want judgment, and a template can't provide it.

One review habit

Before sending, read the report as the recipient. Would they know what we did? Would they know what to approve? If not, cut a section.

Build the report once in Promptwatch, schedule the data pages and spend your time on the verdict and the next actions. A short report that leads to a decision does more for the client than a long one that gets filed.