Prepare data before every question.
- Export files from the marketing platform
- Reformat and reconcile columns
- Rebuild the analysis for each follow-up
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Meta Ads
3 advertising accounts
Connected
Google Ads
2 advertising accounts
Connected
Google Analytics 4
1 web property
Connected
HubSpot
1 CRM portal
Connected
Configure the Catchr remote MCP connection in ChatGPT using the connector details from Catchr.
Replace account, period, KPI target, and threshold variables before you ask ChatGPT.
“Why did CPA rise?” sounds simple. The answer is usually buried across exports, formulas, filters, and tabs before the analysis can even start.
Choose the right account, date range, breakdowns, and fields. Then wait for the file and do it again when the question changes.
Rename columns, fix formats, join tabs, and check formulas before you can trust the comparison.
Turn the numbers into a client-ready answer, then repeat the whole process for the inevitable follow-up.
Catchr MCP gives ChatGPT access to the marketing accounts you select, so each follow-up starts with the same marketing context instead of a new manual export.
Choose your role, open a workflow, then replace the bracketed variables before pasting the prompt into ChatGPT. Every prompt asks for evidence, limits, and a concrete output.
Using the Catchr MCP, pull Facebook Pages data for [List of Client Page Names/IDs] over [Current Period, e.g., the last 7 days] and [Comparison Period]. For each page, review Page Media View, Page total media view unique, Page post engagement, Followers count, Page Fan add total, Page CTA click logged in unique, and CTA Go to website where populated. Label every client Healthy, Watch, or Critical against [Client Targets or Recent Baseline], quantify the main change, identify the page or post-level signal behind each Watch or Critical status, and return a ranked morning action list with one evidence-based recommendation per affected client. Do not treat missing fields as zero.
ChatGPT can query connected Facebook Pages data for content, reach, engagement, audience, follower, traffic, and video reporting.
Representative measures include Organic media views, Post clicks, Post engagement rate, Comments, and Reactions. Useful breakdowns include Post ID, Post Type, Post Created Date, and Post Message. The exact field set depends on the selected dataset and compatible reporting reporting level.
The available detail depends on the fields returned for the selected dataset. Useful breakdowns include Post ID, Post Type, Post Created Date, and Post Message.
Ask ChatGPT to state the reporting level it used and keep incompatible levels separate before calculating totals, rates, or comparisons.
Yes. ChatGPT can rank posts and formats by site-directed clicks, engagement, and organic media views. Relevant fields include Organic media views, Post clicks, Post engagement rate, Comments, and Reactions.
Set the business target, comparison period, and minimum volume before requesting priorities or recommendations.
Yes. ChatGPT can identify the posts, themes, and formats responsible for changes in reach, clicks, or engagement. Useful breakdowns include Post ID, Post Type, Post Created Date, and Post Message.
Ask it to separate observed data, possible explanations, and the next validation step so an unusual value is not presented as a proven cause.
Strong prompts name the action, account or entity, date range, comparison, and KPI or threshold.
Yes, when the other sources are also connected to Catchr. Useful combinations include advertising, analytics, commerce, or CRM sources.
Align dates, currencies, identifiers, and definitions first. If the sources cannot be joined reliably, ask for a side-by-side comparison rather than a single attributed result.
Yes, provided each one is connected and available through Catchr MCP. Ask for separate results first, then create the combined view.
Specify the account, audience, content format, timezone, period, and objective. This keeps one large entity or a definition mismatch from distorting the comparison.
You need access that can authorize and view the relevant Facebook Pages data, a Catchr workspace with the source connected, and Catchr MCP enabled in ChatGPT.
After selecting the required entities, you can ask questions in natural language without preparing a new CSV export for each analysis.
ChatGPT analyzes the records returned through the connected Catchr source; it should not assume the data is real time. Freshness and historical coverage can vary by dataset, field, selected period, and source API limits.
Ask it to state the latest published-content, audience, or reporting date, together with the timezone, requested period, and any missing intervals before interpreting a trend.
No. Catchr MCP provides Facebook Pages data for analysis; it does not give ChatGPT permission to publish content, reply to users, or change profile and channel settings.
Use the result to prepare an action plan, then make operational changes in Facebook Pages. Review the supporting figures before acting on the recommendation.
Our team is always here to answer any questions you may have about our data connector.
Connect yout marketing platform to ChatGPT with Catchr MCP and start investigating current campaign performance.