Connect Google Ads to ChatGPT

Daily Cross-Account Channel Triage

Using the Catchr MCP, pull today's Google Ads data for [List of Client Account Names/IDs] and compare it with [Baseline Period, e.g., the previous 7 comparable days]. At Account, Campaign Name, and Advertising Channel level, review Cost, Impressions, Clicks, CTR, Avg. CPC, Conversions, Cost / conv., Total conv. value, and ROAS against [Client KPI Targets]. For affected Search campaigns, inspect Search Lost IS (budget) and Search Lost IS (rank); for Display, inspect Active View viewable impr. / measurable impr.; and for Shopping, drill into Product Title and Product Group. Label every account Healthy, Watch, or Critical, explain the evidence, and return a ranked morning action queue with one concrete next step per client.

Client-Ready Search, Display, and Shopping Review

Using the Catchr MCP, pull Google Ads performance for [Client Account Name/ID] over [Reporting Period] and [Comparison Period]. Split results by Campaign Name and Advertising Channel, then show Cost, Impressions, Clicks, CTR, Avg. CPC, Conversions, Conv. rate, Cost / conv., Total conv. value, and ROAS. Add channel-specific sections using Search Impr. share and Impr. (Top) % for Search, Active View viewable impressions and View-through conv. for Display, and Product Title, Brand, and Item Id for Shopping where populated. Produce a client-ready dashboard and plain-English update covering wins, risks, confirmed drivers, data limitations, and the three actions planned for [Next Period].

Portfolio Growth and Waste Allocator

Using the Catchr MCP, analyze [List of Client Account Names/IDs] over [Analysis Period] and [Comparison Period] to find where budget can be protected or expanded. Rank Account, Campaign Name, and Advertising Channel combinations by Cost, Conversions, Cost / conv., Total conv. value, and ROAS, applying [Minimum Cost or Conversion Threshold] and [Client Efficiency Targets]. Trace Search waste to Search term, Keyword, and Keyword Match type; Display waste to Domain and Active View viewable impr. / measurable impr.; and Shopping opportunities to Product Title, Product Group, Brand, and Item Id. Return a client-by-client reallocation plan with the amount or percentage to move, the evidence supporting it, the expected KPI to monitor, and a clear separation between observed facts and hypotheses.

Morning Client Priority Queue

Using the Catchr MCP, pull month-to-date Google Ads performance for [List of Client Account Names/IDs] and compare each account with [Monthly Cost and KPI Targets] and the share of the month elapsed. At Account and Advertising Channel level, use Cost, Conversions, Cost / conv., Total conv. value, and ROAS, then trace the largest gap to Campaign Name. Check Search Lost IS (budget) versus Search Lost IS (rank) for Search, Active View viewable impr. / measurable impr. for Display, and Product Title performance for Shopping where relevant. Rank clients by urgency, explain why each off-track account needs attention, and give one task to complete today plus the KPI to recheck.

Monthly Client Performance Story

Using the Catchr MCP, pull Google Ads data for [Client Account Name/ID] for [Reporting Month] and [Previous Month]. Summarize Cost, Impressions, Clicks, CTR, Avg. CPC, Conversions, Conv. rate, Cost / conv., Total conv. value, and ROAS, then explain the largest changes by Campaign Name and Advertising Channel. Include one concise Search insight using Search term or Search Impr. share, one Display insight using Active View viewable impressions or View-through conv., and one Shopping insight using Product Title or Product Group when those channels are present. Write a client-ready report in plain English with results, likely drivers supported by data, unresolved questions, and three priorities for [Next Month].

Three-Hour Optimization Sprint

Using the Catchr MCP, inspect [Client Account Name/ID] over [Analysis Period] and create a prioritized Google Ads work plan that fits [Available Time, e.g., three hours]. For Search, evaluate Search term, Keyword, Keyword Match type, Ad Group Quality score, Search Lost IS (budget), and Search Lost IS (rank); for Display, evaluate Domain, Ad ID, Ad type, Active View viewable impr. / measurable impr., and View-through conv.; for Shopping, evaluate Product Title, Item Id, Product Group, and Brand. Use Cost, Clicks, Conversions, Cost / conv., Total conv. value, and ROAS to score impact, require [Minimum Data Threshold], and return tasks ordered by expected value with the evidence, exact action, estimated effort, and follow-up metric for each.

Shopping Product Profitability Matrix

Using the Catchr MCP, pull Google Ads Shopping performance for [Account Name/ID] over [Period] and [Comparison Period], grouped by Product Title, Item Id, Product Group, Brand, and Product type (1st level). Evaluate Cost, Impressions, Clicks, CTR, Avg. CPC, Conversions, Cost / conv., Total conv. value, and ROAS against [Target ROAS or CPA] and [Minimum Data Threshold]. Classify each product as Scale, Hold, Fix, or Exclude, quantify the change versus the comparison period, identify products consuming cost without sufficient return, and provide a prioritized merchandising or campaign action for the top [Number] opportunities.

Search Term Waste and Demand Miner

Using the Catchr MCP, analyze Search term performance for [Account Name/ID] over [Period], grouped by Campaign Name, Ad group, Keyword, Keyword Match type, Query Match type, and Added/Excluded. Use Cost, Impressions, Clicks, CTR, Avg. CPC, Conversions, Cost / conv., Total conv. value, and ROAS, with [Minimum Click or Cost Threshold] and [Target CPA or ROAS]. Return three evidence-based lists: terms to add as keywords, terms to exclude as negatives, and promising demand themes for new ad groups or Shopping feed alignment. For every recommendation, show the supporting metrics and flag low-volume cases as tests rather than conclusions.

Cross-Channel Revenue Guardrail

Using the Catchr MCP, pull daily Google Ads results for [Account Name/ID] over [Current Period] and [Comparison Period], split by Advertising Channel and Campaign Name. Track Cost, Conversions, Conv. rate, Cost / conv., Total conv. value, and ROAS against [Daily or Monthly Revenue Target]; add Search Impr. share for Search, Active View viewable impr. / measurable impr. and View-through conv. for Display, and Product Title for Shopping. Identify the exact channel, campaign, or product causing any revenue or efficiency decline, distinguish a volume loss from a conversion-efficiency loss, and recommend one immediate action plus the metric and [Review Window] needed to validate recovery.

Conversion Tracking and Attribution Audit

Using the Catchr MCP, audit Google Ads data for [Account Name/ID or All Connected Accounts] over [Period], grouped by Normalized Date, Account, Campaign ID, Campaign Name, Conversion name, Conversion category, and Conversion source. Compare Conversions with All conv., Total conv. value with All conv. value, and review Cross-device conv. and View-through conv. separately. Flag missing dates or identifiers, spend with prolonged zero conversions, conversions with zero value where value is expected, abrupt breaks by conversion action, negative or impossible values, and suspicious changes in attribution mix. Return an exception table with the failed rule, observed values, severity, whether the evidence is conclusive or only suspicious, and the next validation step outside Catchr when required.

Ninety-Day Performance Outlier Monitor

Using the Catchr MCP, pull at least [Lookback Period, e.g., 90 days] of Google Ads data for [Account Name/ID or All Connected Accounts], grouped by Normalized Date, Account, Campaign Name, Advertising Channel, and Device. For Cost, Impressions, Clicks, Conversions, and Total conv. value, compare each day with its trailing [Baseline Window, e.g., 30-day] mean and standard deviation; derive CTR, Avg. CPC, Conv. rate, Cost / conv., and ROAS from the summed base values when aggregating. Flag deviations beyond [Z-score Threshold, e.g., 2] only after [Minimum Volume Threshold] is met, trace each outlier to Search, Display, or Shopping dimensions where possible, and classify it as likely data quality, mix shift, auction pressure, or genuine performance change with a recommended investigation.

Channel Rollup and Segmentation Reconciliation

Using the Catchr MCP, validate Google Ads reporting consistency for [Account Name/ID or All Connected Accounts] over [Period]. Build independent rollups of Cost, Impressions, Clicks, Conversions, Total conv. value, and ROAS by Account and Campaign Name, then reconcile them separately against Advertising Channel, Device, and Network breakdowns; do not sum overlapping segmentation extracts together. For Search, test Search term and Keyword coverage; for Display, test Domain coverage and compare Active View measurable impr. with Active View viewable impressions; for Shopping, test Item Id and Product Title coverage. Report absolute and percentage discrepancies beyond [Tolerance], missing or duplicate keys, null-heavy fields, and a reproducible remediation plan that preserves raw extracts and documents every assumption.

Replace [variables] Facts ≠ hypotheses Action + follow-up metric

Connect Google Ads to ChatGPT

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How to connect Google Ads to ChatGPT ?

Authorize the Google Ads account in Catchr

Add the Catchr MCP from official ChatGPT store

Choose, adapt, and run a prompt.

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

Pull another CSV

Rebuild the context

Summarize it by hand

Ask the account. Get to the explanation.

Prepare data before every question.

Connect once. Keep asking.

Twelve Google Ads prompts for analyzing real account data.

Google Ads to ChatGPT FAQs

What Google Ads data can ChatGPT analyze through Catchr?

How granular can Google Ads analysis be in ChatGPT?

Can ChatGPT find efficiency and budget opportunities in Google Ads?

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

What types of prompts work best for Google Ads analysis?

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

Can I analyze multiple accounts or campaigns together?

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

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

Can ChatGPT change anything in Google Ads through Catchr?

How much does it cost to connect marketing data to ChatGPT with Catchr?

‍Can I try the ChatGPT integration before choosing a plan?

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