Connect X / Twitter Ads to ChatGPT

Multi-Client Paid Social Command Center

Using the Catchr MCP, pull X / Twitter Ads data for [List of Client Account Names/IDs] over [Period] and [Comparison Period]. For each account, summarize Spend, Impressions, URL Clicks, Engagements, Follows, and the conversion metric that matches [Client Objective, e.g., Conversion Purchases Total or Conversion Sign Ups Total]. Calculate link CTR, engagement rate, CPC, CPM, and cost per objective result from the available fields, then compare actual spend with [Budget or Pacing Target]. Label every account On Track, Watch, or At Risk, identify the Campaign Name or Ad Group Name driving each material issue, rank the clients that need the consultant's attention today, and give one evidence-based next action per flagged account.

Client Objective Performance Debrief

Using the Catchr MCP, analyze X / Twitter Ads performance for [Client Account Name/ID] over [Period] versus [Comparison Period]. Use Ad Group Objective and Ad Group Goal to select the right outcome metrics, then break Spend, Impressions, URL Clicks, Engagements, Follows, Video Total Views, Conversion Site Visits Total, Conversion Sign Ups Total, or Conversion Purchases Total down by Campaign Name and Ad Group Name as relevant. Calculate the corresponding efficiency rates, explain which campaigns caused the largest changes, and produce a client-ready debrief with an executive summary, three supported insights, risks, and prioritized actions. Clearly mark unavailable or non-applicable metrics instead of inventing results.

Cross-Account Creative and Targeting Watchlist

Using the Catchr MCP, review X / Twitter Ads creative and targeting performance across [List of Client Account Names/IDs] for [Period]. At Ad Name or Tweet Name level, compare Impressions, Spend, URL Clicks, Engagements, Likes, Replies, Retweets, Media Views, and the [Objective Conversion Metric]; segment material results by Audience, Interest, Keyword, Country, Age, or Gender where data is available. Apply [Minimum Impression or Spend Threshold], flag creatives or segments with weakening link CTR, engagement rate, or cost per result versus [Baseline], and return a client-by-client watchlist with the evidence, likely interpretation stated cautiously, budget exposure, and a specific action to scale, refresh, narrow, exclude, or retest.

Morning Client Priority Queue

Using the Catchr MCP, pull month-to-date X / Twitter Ads performance for [List of Client Account Names/IDs] and compare each account with [Monthly Objective], [Budget Target], and [Comparison Period]. For every client, use Spend, Impressions, URL Clicks, Engagements, and the conversion field aligned with Ad Group Objective; calculate pacing, link CTR, engagement rate, CPC, and cost per objective result. Identify the Campaign Name or Ad Group Name behind each material gap, rank clients by urgency based on performance deterioration and remaining budget or time, and give me a concise today-only task list with the first action to take for the top three accounts.

Monthly Client Results Narrative

Using the Catchr MCP, pull X / Twitter Ads data for [Client Account Name/ID] for [Reporting Period] and [Previous Period]. Summarize Spend, Impressions, URL Clicks, Engagements, Follows, Video Total Views, and the relevant [Objective Conversion Metric], then calculate link CTR, engagement rate, CPC, CPM, and cost per result. Break the most important movements down by Campaign Name, Ad Group Name, and Ad Name or Tweet Name. Write a concise client-ready report in plain English covering what improved, what declined, which entities drove the result, what remains uncertain, and the three actions planned for [Next Period].

Tweet Creative Action List

Using the Catchr MCP, compare all eligible X / Twitter Ads creatives for [Client Account Name/ID] over [Period] using Ad Name, Tweet Name, Promoted Tweet Approval Status, Spend, Impressions, URL Clicks, Engagements, Likes, Replies, Retweets, Media Views, and [Objective Conversion Metric]. Exclude creatives below [Minimum Volume Threshold], calculate link CTR, engagement rate, CPC, and cost per objective result, and compare recent performance with [Earlier Window]. Separate clear winners, promising tests, fatigued creatives, and tracking or approval issues; then produce a practical backlog showing what to scale, refresh, pause, or investigate, with a success metric and review date for each task.

Purchase Efficiency Guardrail

Using the Catchr MCP, pull X / Twitter Ads data for [Account Name/ID] over [Period] and [Comparison Period]. Report Spend, Impressions, URL Clicks, Conversion Purchases Total, Conversion Purchases Order Quantity, and Conversion Purchases Sale Amount by Campaign Name and Ad Group Name. Calculate link CTR, CPC, purchase conversion rate from URL Clicks, cost per purchase, and ROAS after normalizing Spend to the account currency unit. Compare results with [ROAS or CPA Target], identify the campaigns responsible for any deterioration, and recommend where to protect, reduce, or reallocate budget. Flag missing purchase tracking or sale amount rather than treating missing values as zero.

Paid Social Commerce Funnel Leak Finder

Using the Catchr MCP, map the measurable X / Twitter Ads commerce journey for [Account Name/ID] over [Period] using Impressions, URL Clicks, Conversion Site Visits Total, Conversion Purchases Total, Conversion Purchases Order Quantity, and Conversion Purchases Sale Amount. Calculate the observable rates from impression to URL click, URL click to tracked site visit, and site visit to purchase, then compare them with [Comparison Period]. Break the largest losses down by Campaign Name, Ad Group Name, Country, Platform, and Audience where available, quantify which segments contribute most to each leak, and provide a prioritized action plan for creative, targeting, landing-page, or tracking review without claiming causation the data cannot prove.

Video Creative Revenue Scorecard

Using the Catchr MCP, evaluate X / Twitter Ads video creatives for [Account Name/ID] over [Period] at Ad Name or Tweet Name level. Pull Spend, Impressions, Video Content Starts, Video 6s Views, Video 15s Views, Video Views 25%, Video Views 50%, Video Views 75%, Video Views 100%, Video CTA Clicks, URL Clicks, Conversion Purchases Total, and Conversion Purchases Sale Amount. Apply [Minimum Spend or Impression Threshold], calculate view-through progression, CTA click rate, link CTR, cost per purchase, and ROAS where inputs exist, then classify each creative as Scale, Iterate, Refresh, or Pause. Support every recommendation with observed metrics and propose three concrete next creative tests.

Paid Social Data Integrity Audit

Using the Catchr MCP, audit X / Twitter Ads data for [Account Name/ID or All Connected Accounts] over [Period] at Date, Campaign ID, Ad Group ID, and Tweet ID level. Check completeness and uniqueness of Account Id, Campaign ID, Campaign Name, Ad Group ID, Ad Group Name, Tweet ID, Ad Name, Date, and Extracted Date; validate that Spend, Impressions, Clicks, URL Clicks, Engagements, Conversion Purchases Total, and Conversion Purchases Sale Amount are non-negative. Flag duplicate keys, missing identifiers, stale extraction timestamps, Campaign Effective Status or Campaign Servable values that conflict with unexpected data gaps, URL Clicks above Clicks, and component metrics that exceed plausible parent totals. Return an exception table with account, date, entity, failed rule, observed values, severity, and the next validation step.

Daily Delivery and Outcome Outlier Monitor

Using the Catchr MCP, pull at least [Lookback Period, e.g., 90 days] of daily X / Twitter Ads data for [Account Name/ID or List of Accounts], segmented by Campaign Name and Ad Group Name. Monitor Spend, Impressions, URL Clicks, Engagements, Video Total Views, and [Objective Conversion Metric], and calculate link CTR, engagement rate, CPC, CPM, and cost per result. Compare every day with a trailing [Baseline Window, e.g., 28 days] and flag changes beyond [Outlier Threshold, e.g., 2 standard deviations or 30%]. Drill down by Ad Name or Tweet Name and available targeting dimensions, classify each alert as likely data quality, delivery, creative, audience, or conversion-tracking change based on cross-metric evidence, and output the date, affected entity, severity, evidence, and investigation step.

Conversion Attribution Split Audit

Using the Catchr MCP, analyze X / Twitter Ads conversion attribution for [Account Name/ID] over [Period] using Conversion Purchases Total, Conversion Purchases Post Engagement, Conversion Purchases Post View, Conversion Purchases Assisted, Conversion Purchases Sale Amount, Conversion Purchases Sale Amount Engagement, and Conversion Purchases Sale Amount View. Break the results down by Date, Campaign Name, Ad Group Name, and Conversion Tag, and compare them with [Comparison Period]. Calculate each attribution component's share of total purchases and sale amount, test whether available components reconcile with the reported totals, flag abrupt mix shifts, missing components, or inconsistent values, and produce a methodology note plus a remediation-ready issue table without interpreting attributed revenue as incremental revenue.

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

Connect X / Twitter Ads to ChatGPT

Trusted by marketing teams that talk to data everyday

How to connect X / Twitter Ads to ChatGPT ?

Authorize the X / Twitter 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 X / Twitter Ads prompts for analyzing real account data.

X / Twitter Ads to ChatGPT FAQs

What X / Twitter Ads data can ChatGPT analyze through Catchr?

How granular can X / Twitter Ads analysis be in ChatGPT?

Can ChatGPT find efficiency and budget opportunities in X / Twitter Ads?

Can ChatGPT diagnose targeting, creative, or conversion issues in X / Twitter Ads?

What types of prompts work best for X / Twitter Ads analysis?

Can I combine X / Twitter Ads with other data sources in ChatGPT?

Can I analyze multiple accounts or campaigns together?

What do I need to connect X / Twitter Ads to ChatGPT with Catchr?

How recent is the X / Twitter Ads data, and how much history can I analyze?

Can ChatGPT change anything in X / Twitter 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?

Still have a question ?

Ask the account question before building another export.