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Connect Facebook Ads to ChatGPT

Connect Facebook Ads to ChatGPT and ask about spend, ROAS, CPA, and creative performance across every ad account you manage.

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Catchr MCP gives ChatGPT read access to the accounts you select, alongside Google Ads, GA4, and your other marketing sources. No CSV exports, no manual campaign summaries.

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How to connect Facebook Ads to ChatGPT

Authorize your Facebook Ads accounts in Catchr, install the Catchr app in ChatGPT, then ask your first question. Setup takes a few minutes and needs no code.

Step one

Authorize the Facebook Ads account in Catchr

Select Facebook Ads, sign in, and choose the client or business accounts you want to connect.

Client A · Connected sources
5 sources ready
Meta Ads 3 advertising accounts Connected
Google Ads 2 advertising accounts Connected
Google Analytics 4 1 web property Connected
HubSpot 1 CRM portal Connected
Step two

Install the Catchr app in ChatGPT

Configure the Catchr remote MCP connection in ChatGPT using the connector details from Catchr.

Step three

Choose, adapt, and run a prompt.

Replace account, period, KPI target, and threshold variables before you ask ChatGPT.

A simple client question should not trigger an hour of data prep.

“Why did CPA rise?” sounds simple. The answer is usually buried across exports, formulas, filters, and tabs before the analysis can even start.

Pull another CSV

Choose the right account, date range, breakdowns, and fields. Then wait for the file and do it again when the question changes.

Rebuild the context

Rename columns, fix formats, join tabs, and check formulas before you can trust the comparison.

Summarize it by hand

Turn the numbers into a client-ready answer, then repeat the whole process for the inevitable follow-up.

Ask the account. Get to the explanation.

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.

The hard way

Prepare data before every question.

  • Export files from the marketing platform
  • Reformat and reconcile columns
  • Rebuild the analysis for each follow-up
The Catchr way

Connect once. Keep asking.

  • Select the right accounts and data
  • Ask in the language your team already uses
  • Investigate with follow-up questions

See it in ChatGPT

Twelve Facebook Ads prompts for analyzing real account data.

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.

Agency promptCopy prompt

Daily Portfolio Health Check

Using the Catchr MCP, pull today's Facebook Ads data for [List of Client Account Names/IDs] and compare it with [Baseline Period, e.g., the previous 7-day daily average]. For each account, review Spend, Impressions, Clicks, CTR (all), CPC (all), CPM, Purchases, and Cost per website purchase; use [Client KPI Targets] where provided. Label every account Healthy, Watch, or Critical, identify the metric and campaign responsible for each Watch or Critical status, and return a ranked morning action list with one evidence-based diagnosis and one concrete next step per affected client.

Objective-Aligned Client Dashboard
Using the Catchr MCP, pull Facebook Ads performance for [Client Account Name/ID] over [Reporting Period] and [Comparison Period]. Use Campaign Objective and Campaign Name to group campaigns by business goal, then select the relevant available metrics: Website purchase ROAS, Purchases, Purchases Values, and Cost per website purchase for sales; Leads and Cost per website lead for lead generation; or Clicks, CTR (all), CPC (all), Impressions, Reach, and CPM for traffic or awareness. Build a client-ready dashboard with KPI totals, trends, top and bottom campaigns, and a concise narrative covering wins, risks, likely drivers supported by the data, and the three actions to take next.
Cross-Account Anomaly Investigator
Using the Catchr MCP, analyze Facebook Ads data for [List of Client Account Names/IDs] over [Analysis Period, e.g., the last 14 days] against [Baseline Period, e.g., the preceding 28 days]. Detect sudden changes in Spend, CPM, CTR (all), CPC (all), Frequency, Purchases, Cost per website purchase, and Website purchase ROAS; also compare Spend with Campaign Daily Budget or Campaign Budget Lifetime where available to identify pacing risks. Trace every anomaly to Account Name, Campaign Name, Adset Name, and Ad Name where the data supports it, quantify the deviation, distinguish confirmed evidence from hypotheses, and recommend a specific action such as budget reallocation, creative refresh, targeting review, or tracking validation.
Daily Client Objective Check-Up
Using the Catchr MCP, pull month-to-date Facebook Ads performance for [List of Client Account Names/IDs] and compare each account with [Monthly Spend and KPI Targets]. Use the target relevant to each client, such as Purchases, Website purchase ROAS, Cost per website purchase, Leads, Cost per website lead, Clicks, or CTR (all), and calculate progress versus the share of the month elapsed. Rank clients by urgency, flag overpacing and underdelivery, identify the campaign causing the largest gap, and tell me which client to prioritize today with one concrete action and the metric that should improve.
Monthly Client Performance Story
Using the Catchr MCP, pull Facebook Ads data for [Client Account Name/ID] for [Reporting Month] and [Previous Month]. Summarize Spend, Impressions, Clicks, CTR (all), CPC (all), CPM, Purchases, Purchases Values, Cost per website purchase, and Website purchase ROAS, then break the most important changes down by Campaign Name. Write a concise client-ready report in plain English that explains what improved, what declined, which data points support each conclusion, what remains uncertain, and the three priorities for [Next Month].
Creative Fatigue Action Queue
Using the Catchr MCP, analyze active ads for [Client Account Name/ID] over [Analysis Period, e.g., the last 21 days], grouped by Ad Name and Ad Created At. Track Frequency, CTR (all), CPM, Spend, Purchases, Cost per website purchase, Quality Ranking, Engagement Rate Ranking, and Conversion Rate Ranking where populated, comparing the first and most recent [Trend Window]. Flag ads with rising Frequency and weakening response or conversion efficiency, require [Minimum Spend or Impressions] before classifying fatigue, and return a ranked refresh queue with the evidence, likely issue, recommended creative change, and follow-up KPI for each ad.
ROAS and Revenue Pulse
Using the Catchr MCP, pull Website purchase ROAS, Purchases Values, Purchases, Spend, and Cost per website purchase for [Account Name/ID] over [Current Period] and [Comparison Period]. Confirm whether ROAS and purchase value are improving, stable, or declining against [ROAS Target], quantify every change, and break the result down by Campaign Name and Adset Name to show which segments are driving it. Finish with a prioritized recommendation for scaling, holding, or reducing spend, including the supporting metric and any data-volume caveat.
Daily Campaign Issue Detector
Using the Catchr MCP, pull today's Facebook Ads results for every campaign with Campaign Effective Status equal to active on [Account Name/ID], and compare them with [Recent Baseline, e.g., the previous 7 comparable days]. Use Campaign Objective to evaluate each campaign with the appropriate available metrics, including Spend, Impressions, Clicks, CTR (all), CPC (all), CPM, Purchases, Cost per website purchase, Website purchase ROAS, Leads, or Cost per website lead. Flag campaigns that are off target or materially outside their baseline, explain the exact evidence, and provide one immediate action plus the metric to recheck after [Review Window].
Conversion Funnel Leak Dashboard
Using the Catchr MCP, pull Views Content, Adds To Cart, Initiates Checkout, Purchases, Purchases Values, Spend, and Website purchase ROAS for [Account Name/ID] over [Period], with [Comparison Period] as a benchmark. Calculate View Content-to-Add to Cart, Add to Cart-to-Initiate Checkout, Initiate Checkout-to-Purchase, and overall View Content-to-Purchase conversion rates. Build a visual funnel dashboard showing volumes, step conversion rates, period-over-period changes, and the campaign responsible for the largest leak; then recommend the highest-priority funnel action while clearly noting that Facebook-attributed event counts may not represent unique users.
Tracking and Attribution Integrity Audit
Using the Catchr MCP, audit Facebook Ads data for [Account Name/ID or All Connected Accounts] over [Period]. At Account Name, Campaign Name, and Date Start level, review Spend, Purchases, Purchases Values, Website purchase ROAS, Conversions within 1 day of click, Conversions within 1 day of view, Conversions within 7 days of click, Conversions within 28 days of click, and their corresponding available conversion-value fields. Flag missing dates or identifiers, conversion gaps despite sustained spend, impossible negative values, abrupt breaks in event volume, and attribution-window relationships that fail expected monotonic checks. Return an exception table with observed values, failed rule, severity, whether the signal is conclusive or only suspicious, and the next validation step.
Daily Performance Outlier Monitor
Using the Catchr MCP, pull at least [Lookback Period, e.g., 90 days] of Facebook Ads data for [Account Name/ID or All Connected Accounts], grouped by Date Start, Account Name, and Campaign Name. For Spend, CPM, CTR (all), CPC (all), Frequency, Purchases, Cost per website purchase, and Website purchase ROAS, compare each daily value with its trailing [Baseline Window, e.g., 30-day] mean and standard deviation and flag deviations beyond [Z-score Threshold, e.g., 2]. Require [Minimum Volume Threshold] before evaluating rate metrics, classify each outlier as likely data quality, spend or mix shift, creative saturation, or genuine performance change, and output the evidence plus the recommended investigation.
Market-Level Portfolio Dashboard
Using the Catchr MCP, pull Facebook Ads data for [Market/Vertical List of Account Names/IDs] over [Reporting Period] and [Comparison Period]. Aggregate Spend, Impressions, Clicks, Purchases, Purchases Values, Website purchase ROAS, and Cost per website purchase across the market, using weighted calculations for rate and cost metrics rather than averaging account-level rates. Build a market dashboard with trends, contribution by account, and concentration risk; if performance declined, quantify which accounts and campaigns explain the change, separate volume effects from efficiency effects, and provide a prioritized validation and remediation plan.
Replace [variables] Facts ≠ hypotheses Action + follow-up metric

Facebook Ads to ChatGPT pricing

Choose your plan by the number of platforms and accounts you report on.

Starter

For freelancers and small teams.

$ 24 /mo

Billed monthly · cancel anytime

Platforms3
Accounts10
Start free trial

Growth

For agencies managing more clients.

$ 239 /mo

Billed monthly · cancel anytime

Platforms10
Accounts100
Start free trial

Scale

For teams reporting at scale.

$ 599 /mo

Billed monthly · cancel anytime

Platforms25
Accounts500
Start free trial

Facebook Ads to ChatGPT: FAQ

Does Meta have an official ChatGPT connector?

Yes. Meta provides an official ads MCP server that connects your Meta ad account to ChatGPT and other MCP-compatible assistants. It covers Meta data and can both report on the account and perform authorized actions, such as creating ads, editing budgets, or updating audiences.

Catchr MCP answers a different need: it puts Facebook Ads next to your other connected marketing sources in the same conversation, with read-only access to your advertising accounts.

What Facebook Ads data can ChatGPT analyze through Catchr?

ChatGPT can query the 440 metrics and 233 dimensions of the Catchr Facebook Ads connector, from spend, impressions, and CPM to purchases, purchase value, website purchase ROAS, leads, and cost per purchase. The exact fields depend on the dataset and reporting level you select.

View all Facebook Ads metrics and dimensions →

How granular can Facebook Ads analysis be in ChatGPT?

Down to the individual ad. ChatGPT can work at account, campaign, ad set, or ad level, by day, and split results by placement, publisher platform, country, or gender. Ask it to state the level it used, and to keep levels separate before adding up totals or rates.

Can ChatGPT find efficiency and budget opportunities in Facebook Ads?

Yes. ChatGPT can rank campaigns and ad sets against your ROAS or CPA target, compare spend with daily or lifetime budgets to spot pacing risks, and point to where budget should move. Set the business target, the comparison period, and a minimum volume first, so a campaign with three purchases does not top the list.

Can ChatGPT diagnose targeting, creative, or conversion issues in Facebook Ads?

Yes. ChatGPT can trace a drop in purchase efficiency to the campaign, ad set, or ad behind it, and check signals such as rising frequency or falling CTR on a creative. Ask it to separate what the data shows from possible explanations, and to name the next check, so an unusual value is not presented as a proven cause.

What types of prompts work best for Facebook Ads analysis?

Strong prompts name the action, the account, the date range, the comparison period, and the KPI or threshold. The twelve prompts above follow this pattern for agencies, freelancers, advertisers, and data teams.

Can I combine Facebook Ads with other data sources in ChatGPT?

Yes, when the other sources are also connected to Catchr: Google Ads, GA4, a CRM such as HubSpot, or an e-commerce platform such as Shopify. 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.

Can I analyze multiple accounts or campaigns together?

Yes, provided each one is connected and available through Catchr MCP. Ask for separate results first, then create the combined view. Specify the currency, timezone, objective, attribution window, and KPI target, so one large account or a definition mismatch does not distort the comparison.

What do I need to connect Facebook Ads to ChatGPT with Catchr?

Three things: a Facebook user with access to the ad accounts you want to analyze, a Catchr workspace with Facebook Ads connected, and a ChatGPT account where the Catchr app is available and installed.

Check app availability in your ChatGPT account and workspace before connecting. On ChatGPT Business or Enterprise, a workspace admin may need to enable the app first.

How recent is the Facebook Ads data, and how much history can I analyze?

ChatGPT works with the data Catchr returns at the moment you ask. Ask it to state the latest reporting date it received rather than assuming the data is real time.

Historical coverage is set by Meta and depends on the fields and breakdowns: up to 37 months for standard Insights data, 13 months for breakdowns of unique-count metrics and for hourly breakdowns, and 6 months for frequency breakdowns.

For a trend across January 12, 2026, use the same supported attribution window on both sides of that date. Meta stopped returning data for 7-day and 28-day view-through attribution windows on that date.

Can ChatGPT change my Facebook Ads campaigns through Catchr?

No. Catchr's Facebook Ads connection through MCP is read-only: ChatGPT can analyze your campaigns, bids, budgets, and ads, but it cannot change them. Every change still goes through Ads Manager, after someone has checked the figures.

Where supported by your ChatGPT app and workspace settings, you can also require approval before the app is used.

Still have a question?

Our team is always here to answer any questions you may have about our data connector.

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