Blog
GEO

AI monitoring for agencies: managing multiple clients, prompts and competitors in one place

Agency AI monitoring needs separate client projects and a shared working standard. Organize prompts, competitors, observations and tasks so findings inform decisions while each brand’s data stays separate.

AI monitoring for agencies: managing multiple clients, prompts and competitors in one place

Start with a client record

One workflow can organize many projects, but each client needs its own scope. Record the brand, domains and aliases, market, language, offering, project owner and analysis objective. Separate brand-awareness questions from supplier-selection questions. Centralization means shared working rules; it does not mean combining different clients’ answers.

Share intent templates, maintain separate prompt sets

Your team can share question templates, then adapt them to each client’s actual offering. “Which supplier installs furniture in Kraków?” tests a different issue from “Does brand X offer installation?”. Group questions by problem, comparison, purchase and constraints. Give every set a version, date and reason for changes. Keep a stable core for comparisons over time.

AI monitoring budget: choosing questions, systems and review frequency

Define competitors and comparison conditions

The client’s competitor list may differ from the brands AI mentions. Keep both lists and record their origin. Compare brands within the same answers and identical scope. Record the AI system, country, language, date and available settings. Do not compare a client measured using generic questions with a competitor tested only through questions containing its name.

Check if AI sees your business

Run a free audit

Turn an answer into a task

A mention, recommendation and source citation are separate events. Open the answer and check the cited URL before choosing an action. Every task needs evidence, an existing URL, an owner, a deadline and an acceptance condition. Brand absence may reflect a content gap, an accessibility problem or a poorly matched question; the score alone cannot identify the cause.

Did updating your article improve AI visibility? How to plan a before-and-after test

Example: three projects, one standard

Hypothetical example: a shop needs clearer delivery terms, a service business needs coverage information, and a SaaS provider needs an integration description. The agency uses the same task record with different sources and owners. Acceptance means approving accurate information and a working URL. Any subsequent visibility change needs separate measurement; completing a task does not demonstrate an AI effect.

One standard, separate client actions. Example organisation of three agency projects. Hypothetical example. Each action: owner + deadline + acceptance.

Use Semly within the agency workflow

Semly supports analysis of prompts, answers, competitors and sources. Before implementation, check multi-brand support, available systems and your plan’s limits. Keep the task register and client approvals in an agreed workspace. Do not assume automatic task assignment, advanced permissions or white-label reporting without confirming those features.

Blog and knowledge base without cannibalisation: how to divide topics for SEO and AI

Check if AI sees your business

Run a free audit

Assign responsibility and access boundaries

Name the people responsible for project configuration, answer analysis, change approval and client communication. Separate client data in filenames and exports; check the correct brand before sharing a report. A common standard does not require identical access for everyone. If the tool lacks the necessary permission separation, arrange it in the process and storage location. Record who may change prompts and approve scope changes in the project profile.

Introduce a review cycle and change log

Before each analysis, check measurement completeness and changes to the client's offering. Then review recurring errors, new sources and competitor differences. Select a manageable number of evidence-backed actions with owners. Log prompt, competitor or system changes with dates and reasons; label old and new series separately. Regularity supports comparability, while frequency should match change speed and team capacity. Do not increase question counts at the expense of quality control.

FAQ

Should every client use identical prompts? No: intent structures can be shared, but questions must match the offering. Can client averages be compared? Only with consistent definitions and scope; project-specific diagnosis is usually more useful. When should monitoring expand? When the team can act on current findings and has a justified need for additional coverage.

Sources and methodology

Semly Help Center

Share:

Read other articles about AI
GEO

Visibility in ChatGPT or paid ads?

Most online stores base sales on Google Ads and Meta Ads. This works, but the cost per click goes up and the margin goes down. At the same time, customers are increasingly asking ChatGPT, Gemini or Perplexity instead of clicking on ads. Google AI Overviews are also appearing, which reduce classic traffic from the search engine. This article shows how e-commerce can gradually shift budget from ads to GEO, SEO and AI visibility, without risking lost sales and without abruptly shutting down campaigns.

eCommerce

Is ChatGPT the new Google?

Answer engines (ChatGPT, Google AI Overviews, Perplexity, Copilot, Amazon Rufus) are changing search: fewer clicks, more direct answers and recommendations in chats. For e-commerce, it's a signal to prepare data and content so that it can be understood by LLM and readily cited. Structured product information (schema.org, GTIN), content, clear policies and conscious management of AI bot access become key - because visibility in responses shortens the path to the cart and increases conversions.

eCommerce

E-commerce architecture under GenAI: APIs, data and JSON

Learn how to prepare your online store architecture for generative AI. In this article, we discuss optimizing JSON structures, designing efficient APIs for AI agents, and technical aspects of product data management that eliminate the hallucination of LLM models.

AEO

Brand image in AI search: how to avoid ChatGPT hallucinations

Learn how to effectively manage your brand image in a world dominated by language models. From this article, you'll learn how to minimize the risk of ChatGPT hallucinations, ensure the integrity of information in AI search, and build lasting visibility where users are looking for answers today.

Check if AI ChatGPT sees your brand

Get your first AI visibility report in minutes.