Prepare your next client call with a clearer view of customer feedback. Connect Facebook Review to Catchr, then use ChatGPT or Claude through Catchr MCP to explore ratings, recommendations and review text.
Start by discovering the available columns for your selected account. Use those fields to investigate feedback and build a client summary with links to the original reviews.
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Explore how customers rate a client, what they recommend and what they say. Facebook Review uses a live schema, so confirm the available columns before choosing the fields for each analysis.
Use Average Rating and Review Count, where available, to give clients a numerical overview of their reviews. Keep individual Rating values separate from the overall average, and account for reviews that have no star rating.
Select Account ID when reporting across client accounts so each result stays attached to the right account. Confirm the scope of aggregate metrics before presenting them as figures for a selected period.
Explore Review Text alongside Recommendation Status to understand what reviewers describe. Ask for recurring themes, supporting excerpts and examples that deserve a closer look before a client meeting.
Use Review ID and Review URL to make each example traceable. Keep recommendation status distinct from Rating: a recommendation should not be treated as a star score.
Use Comments Count to identify reviews with more discussion, then read their Review Text and Recommendation Status for context. A high comment count shows activity; it does not establish whether the discussion is positive or negative.
Where available, select Review Date to focus on a reporting period and Review URL to open the original review. Confirm date coverage and available date groupings before comparing periods.
A focused feedback investigation, a recurring client report and a question through Catchr MCP serve different needs. Choose the method that fits the work you need to deliver.
Use focused analysis to investigate feedback and reports to present it consistently. Catchr MCP gives freelancers and agencies another way to work with connected Facebook Review data: ask a question, examine the supporting reviews and refine the answer for a client conversation.
Connect Facebook Review in Catchr using API-key authentication and select the relevant client account. Choose ChatGPT or Claude as your AI destination and connect through Catchr MCP.
Begin by asking for the available Facebook Review columns. Select the rating, recommendation, text and date fields needed for your task, then confirm that the requested period can be queried.
Use these prompts after connecting your client's account. Each starts with field discovery so the analysis uses columns available for that account.
Using Catchr, what does the available Facebook Review data show about ratings and review volume for [account]? Discover the columns first, then use the available Average Rating, Review Count and Rating fields I select. Explain the scope of the aggregate figures, distinguish individual ratings from the overall average and identify missing star ratings. Return a concise client briefing without summing repeated aggregate values.
Copy promptUsing Catchr, what recurring themes appear in Facebook reviews for [account] between [start date] and [end date]? Discover the available columns and confirm date filtering, then use the Review Text, Recommendation Status, Review Date, Review ID and Review URL columns I select. Group the feedback into themes, support each with short excerpts and review links, and distinguish explicit recommendations from your interpretation of the text. State any coverage limits.
Copy promptUsing Catchr, which Facebook reviews for [account] have at least [comment threshold] comments during [start date] to [end date]? Discover the available columns and confirm date filtering, then use the Comments Count, Review Text, Recommendation Status, Review Date and Review URL columns I select. Sort matching reviews by comment count and summarize the review text for each. Do not infer the content or sentiment of comments from their count.
Copy promptUsing Catchr, how does Facebook Review feedback for [account] differ between [first period] and [second period]? Discover the available columns and confirm date coverage, then use the Review ID, Review Date, Recommendation Status, Rating and Review Text columns I select. Count distinct returned reviews in each period, compare the observed recommendation-status distribution and summarize changes in themes. Report missing ratings separately and explain whether incomplete coverage limits the comparison.
Copy promptAvailable fields can include Average Rating, Review Count, individual Rating, Comments Count, Recommendation Status and Review Text, plus review dates, IDs and links. Discover the live schema for your selected account before choosing the columns for a query.
Connect Facebook Review in Catchr using API-key authentication, select the relevant account and connect your AI destination through Catchr MCP. Start by discovering the available columns, then ask a question using the fields you select.
No. Recommendation Status indicates whether the reviewer recommends the service. Rating is the star rating, if available. Report them separately and leave missing ratings unscored rather than converting recommendations into stars.
Use Review Date or an available date grouping after confirming the account's columns and queryable date coverage. Compare reviews returned for each period, and check the scope of Average Rating and Review Count before treating them as period-specific metrics. Do not assume complete historical coverage.
Connect your sources to Catchr, add the MCP server to your AI assistant, and ask about the work that matters now.
