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Connect The Trade Desk to ChatGPT

Connect The Trade Desk to ChatGPT and ask about any metrics or dimensions using current integrations data. No CSV exports or manual campaign summaries.

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How to connect The Trade Desk to ChatGPT ?

Three steps to your first source-aware prompt.

Step one

Authorize the The Trade Desk account in Catchr

Select The Trade Desk, 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

Add the Catchr MCP from official ChatGPT store

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

Twelve The Trade Desk 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
Morning Programmatic Account Triage
Using the Catchr MCP, pull The Trade Desk data for [List of Client Advertiser Names/IDs] for [Current Period, e.g., yesterday or month to date] and [Comparison Period]. At Advertiser Name, Campaigns Name, Campaigns Channel Type, and Ad Groups Name level, compare Spend In Advertiser Currency, Budget Spent Percent, Impressions, Clicks, Ctr, Cpm In Advertiser Currency, Conversions, Cpa In Advertiser Currency, Revenue, and Roas Advertiser Currency against [Client Budget and KPI Targets]. Label each client Healthy, Watch, or Critical, rank the accounts requiring attention today, trace every issue to the campaign or ad group driving it, and provide one concrete action with the metric and [Recheck Time] needed to confirm recovery; keep advertiser currencies separate and flag sparse conversion data.
Client-Ready Programmatic Media Review
Using the Catchr MCP, pull The Trade Desk performance for [Client Advertiser Name/ID] over [Reporting Period] and [Comparison Period]. Build a client-ready review by Campaigns Name, Campaigns Objective, Campaigns Channel Type, Ad Groups Name, Creative Name, Creative Type, and Device Type. Report Spend In Advertiser Currency, Impressions, Clicks, Ctr, Cpm In Advertiser Currency, Conversions, Cpa In Advertiser Currency, Revenue, Roas Advertiser Currency, Viewability, In View Rate, Video Completion Rate, Unique Persons, and Unique Households where populated. Explain the strongest results, material risks, and confirmed drivers in plain English, distinguish click-through from view-through impact using the populated 01-06 conversion fields, and close with three actions for [Next Period] plus the KPI used to validate each one.
Portfolio Bid and Budget Reallocation Plan
Using the Catchr MCP, analyze The Trade Desk delivery for [List of Client Advertiser Names/IDs] over [Analysis Period] using Campaigns Name, Campaigns Current Flight Budget In Advertiser Currency, Campaigns Current Flight Flight Elapsed Percent, Campaigns Pacing Mode, Ad Groups Name, Ad Groups Budget Total, Ad Groups Base Bid CPM In Advertiser Currency, and Ad Groups Max Bid CPM In Advertiser Currency. Compare Spend In Advertiser Currency, Budget Spent Percent, Bids, Win Rate, Bid Cpm Advertiser Currency, Cpm In Advertiser Currency, Impressions, Conversions, Cpa In Advertiser Currency, Revenue, and Roas Advertiser Currency against [Pacing and Efficiency Targets]. Flag underdelivery, overspend risk, low auction competitiveness, and inefficient winning, then return a client-by-client plan showing the budget or bid change to test, source and destination ad groups where relevant, supporting evidence, expected KPI effect, risk, and [Review Date]; treat low-volume recommendations as experiments.
Daily Client Flight Priority Queue
Using the Catchr MCP, pull month-to-date The Trade Desk data for [List of Client Advertiser Names/IDs] and compare each client with [Monthly Budget and KPI Targets] and the share of its active campaign flight elapsed. Use Campaigns Name, Campaigns Current Flight Budget In Advertiser Currency, Campaigns Current Flight Flight Elapsed Percent, Campaigns Current Flight Days Remaining, Spend In Advertiser Currency, Budget Spent Percent, Impressions, Win Rate, Conversions, Cpa In Advertiser Currency, Revenue, and Roas Advertiser Currency. Rank clients by urgency, trace the largest delivery or efficiency gap to Ad Groups Name, and give one task to complete today plus the exact KPI and [Recheck Time] needed to confirm improvement; separate confirmed issues from low-volume warnings.
Monthly Client Programmatic Performance Story
Using the Catchr MCP, pull The Trade Desk data for [Client Advertiser Name/ID] for [Reporting Month] and [Previous Month]. Summarize Spend In Advertiser Currency, Impressions, Clicks, Ctr, Cpm In Advertiser Currency, Conversions, Cpa In Advertiser Currency, Revenue, Roas Advertiser Currency, Viewability, Video Completion Rate, Unique Persons, and Unique Households. Explain the largest changes by Campaigns Name, Campaigns Channel Type, Ad Groups Name, Creative Name, Creative Type, and Device Type, and describe click-through versus view-through attribution using only populated 01-06 conversion fields. Write a client-ready report in plain English covering what worked, what did not, the evidence-backed reasons, measurement limits, and three priorities for [Next Month].
Two-Hour Bidding and Creative Optimization Sprint
Using the Catchr MCP, inspect [Client Advertiser Name/ID] over [Analysis Period] and build a The Trade Desk optimization plan that fits [Available Time, e.g., two hours]. At Campaigns Name and Ad Groups Name level, compare Ad Groups Base Bid CPM In Advertiser Currency, Ad Groups Max Bid CPM In Advertiser Currency, Bids, Win Rate, Bid Cpm Advertiser Currency, Cpm In Advertiser Currency, Spend In Advertiser Currency, Conversions, Cpa In Advertiser Currency, Revenue, and Roas Advertiser Currency; then use Creative Name, Creative Type, Device Type, Ctr, Viewability, and Video Completion Rate to locate execution issues. Apply [Minimum Data Threshold] and return tasks ordered by expected value with the exact bid, budget, or creative test, supporting evidence, estimated effort, risk, and follow-up KPI for each.
Commerce ROAS and Attribution Guardrail
Using the Catchr MCP, pull The Trade Desk data for [E-commerce Advertiser Name/ID] over [Current Period] and [Comparison Period], grouped by Campaigns Name, Campaigns Objective, Campaigns Channel Type, and Ad Groups Name. Compare Spend In Advertiser Currency, Conversions, Cpa In Advertiser Currency, Revenue, and Roas Advertiser Currency with [Target CPA, ROAS, and Revenue]. Use the populated 01-06 Click Conversion, View Through Conversion, Conversion Touch, Time Weighted Decay Conversion, and corresponding Revenue fields to show how attributed outcomes differ by method without adding overlapping conversion totals together. Identify the campaigns causing any efficiency or revenue decline, classify each as Scale, Hold, Fix, or Pause, and recommend one immediate action with a validation metric; disclose missing conversion slots or attribution ambiguity.
Audience Reach and Retargeting Efficiency Map
Using the Catchr MCP, evaluate The Trade Desk audience delivery for [E-commerce Advertiser Name/ID] over [Period] by Ad Groups Audience Name, Ad Groups Audience Settings Strategy, Ad Groups Funnel Location, Campaigns Channel Type, and Device Type. Use Spend In Advertiser Currency, Impressions, Unique Persons, Unique Households, Clicks, Ctr, Conversions, Cpa In Advertiser Currency, Revenue, and Roas Advertiser Currency. Calculate impression frequency per Unique Person or Unique Household only where the matching reach metric is populated, apply [Minimum Spend or Impression Threshold] and [Target CPA or ROAS], and identify scalable prospecting groups, retargeting groups showing saturation, and audience-device combinations wasting budget. Return a prioritized scale, bid-adjustment, exclusion, or recency-window test plan with evidence and a [Validation Window].
Creative and Channel Revenue Scorecard
Using the Catchr MCP, pull The Trade Desk results for [E-commerce Advertiser Name/ID] over [Period] and [Comparison Period], grouped by Campaigns Channel Type, Ad Groups Name, Creative Name, Creative Type, and Device Type. Compare Spend In Advertiser Currency, Impressions, Clicks, Ctr, Conversions, Cpa In Advertiser Currency, Revenue, Roas Advertiser Currency, Viewability, In View Rate, Player Starts, Player 25% Complete, Player 50% Complete, Player 75% Complete, Player Completed Views, and Video Completion Rate where relevant. Apply [Minimum Volume Threshold] and [Business KPI Targets], rank creatives and channel-device combinations by both media quality and attributed revenue efficiency, explain where video engagement or conversion performance breaks down, and recommend which assets to scale, adapt, refresh, or retire.
Conversion Attribution Integrity Audit
Using the Catchr MCP, audit The Trade Desk conversion data for [Advertiser Name/ID or All Connected Advertisers] over [Period], grouped by Date, Advertiser Id, Campaigns Id, Ad Groups Id, and Creative Id. For every populated 01-06 conversion slot, compare Click Conversion, View Through Conversion, Conversion Touch, Time Weighted Decay Conversion, and their Revenue fields without summing attribution models together. Review Advertiser Attribution Click Lookback Window, Advertiser Attribution Impression Lookback Window, Advertiser Click Dedupe Window In Seconds, Advertiser Conversion De Dupe Window In Seconds, and Campaigns Custom CPA/ROAS settings. Flag missing dates or identifiers, conversion or revenue breaks, impossible negative values, abrupt attribution-mix shifts, and configuration changes that could explain discontinuities; return an exception table with severity, evidence, likely cause, and a reproducible next validation step.
Entity and Currency Rollup Reconciliation
Using the Catchr MCP, validate The Trade Desk reporting consistency for [Advertiser Name/ID or All Connected Advertisers] over [Period]. Build independent rollups of Impressions, Clicks, Conversions, Revenue, Spend Advertiser Currency, Spend Partner Currency, Spend Usd, Advertiser Cost in each currency, Media Cost in each currency, and TTD Cost in each currency at Advertiser, Campaigns Name/ID, Ad Groups Name/ID, and Creative Name/ID grain. Reconcile each hierarchy and currency view separately rather than summing overlapping segmented extracts, test for duplicate keys, null-heavy identifiers, missing dates, clicks above impressions, spend with zero impressions, and discrepancies beyond [Absolute or Percentage Tolerance]. Return a reconciliation table, documented grain and currency assumptions, confidence rating, and the exact follow-up query for every unresolved exception.
Auction, Delivery, and Media Quality Outlier Monitor
Using the Catchr MCP, pull at least [Lookback Period, e.g., 90 days] of The Trade Desk data for [Advertiser Name/ID or All Connected Advertisers], grouped by Date, Advertiser Name, Campaigns Name, Campaigns Channel Type, Ad Groups Name, and Device Type. For Bids, Win Rate, Bid Cpm Advertiser Currency, Spend In Advertiser Currency, Impressions, Clicks, Conversions, Revenue, Sampled Tracked Impressions, Sampled Viewed Impressions, Viewability, and Video Completion Rate, compare each day with its trailing [Baseline Window, e.g., 30-day] mean and standard deviation. Derive rate metrics from compatible summed base fields where possible, require [Minimum Volume Threshold], flag deviations beyond [Z-score Threshold, e.g., 2], and classify each as likely data quality, bidding pressure, delivery or mix shift, measurement coverage change, or genuine performance change with a reproducible investigation step.
Replace [variables] Facts ≠ hypotheses Action + follow-up metric

The Trade Desk to ChatGPT FAQs

Clear answers for marketers comparing connectors, data sources, reporting workflows, and dashboard setup.

What The Trade Desk data can ChatGPT analyze through Catchr?

ChatGPT can query connected The Trade Desk data for campaign delivery, spend, conversion, and revenue reporting.

Representative measures include Revenue, Clicks, Conversions, Ctr, and Media Cost Usd. Useful breakdowns include Ad Groups Campaign Name, Ad Groups Campaign Status, Ad Groups Campaign Objective, Ad Groups Campaign Channel Type, and Ad Groups Campaign Start Date. The exact field set depends on the selected dataset and compatible reporting reporting level.

How granular can The Trade Desk analysis be in ChatGPT?

The available detail depends on the fields returned for the selected dataset. Useful breakdowns include Ad Groups Campaign Name, Ad Groups Campaign Status, Ad Groups Campaign Objective, Ad Groups Campaign Channel Type, and Ad Groups Campaign Start Date.

Ask ChatGPT to state the reporting level it used and keep incompatible levels separate before calculating totals, rates, or comparisons.

Can ChatGPT find efficiency and budget opportunities in The Trade Desk?

Yes. ChatGPT can rank campaigns, products, audiences, or placements against your efficiency and volume targets. Relevant fields include Revenue, Clicks, Conversions, Ctr, and Media Cost Usd.

Set the business target, comparison period, and minimum volume before requesting priorities or recommendations.

Can ChatGPT diagnose targeting, creative, or conversion issues in The Trade Desk?

Yes. ChatGPT can isolate the campaign, creative, audience, placement, product, or search term behind a performance change. Useful breakdowns include Ad Groups Campaign Name, Ad Groups Campaign Status, Ad Groups Campaign Objective, Ad Groups Campaign Channel Type, and Ad Groups Campaign Start Date.

Ask it to separate observed data, possible explanations, and the next validation step so an unusual value is not presented as a proven cause.

What types of prompts work best for The Trade Desk analysis?

Strong prompts name the action, account or entity, date range, comparison, and KPI or threshold.

  • Monitor: “Creative and Channel Revenue Scorecard”
  • Diagnose: “Conversion Attribution Integrity Audit”
  • Find opportunities: “Portfolio Bid and Budget Reallocation Plan”
  • Report: “Client-Ready Programmatic Media Review”

Can I combine The Trade Desk with other data sources in ChatGPT?

Yes, when the other sources are also connected to Catchr. Useful combinations include analytics, commerce, CRM, or other advertising 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.

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. This keeps one large entity or a definition mismatch from distorting the comparison.

What do I need to connect The Trade Desk to ChatGPT with Catchr?

You need access that can authorize and view the relevant The Trade Desk 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.

How recent is the The Trade Desk data, and how much history can I analyze?

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 campaign or reporting date and the attribution window used, together with the timezone, requested period, and any missing intervals before interpreting a trend.

Can ChatGPT change anything in The Trade Desk through Catchr?

No. Catchr MCP provides The Trade Desk data for analysis; it does not give ChatGPT permission to change campaigns, bids, budgets, targeting, or ads.

Use the result to prepare an action plan, then make operational changes in The Trade Desk. Review the supporting figures before acting on the recommendation.

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

Catchr MCP is included in every standard plan—there is no separate fee for the ChatGPT integration. The Starter plan begins at $20 per month when billed annually, or $24 when billed monthly.

It includes 3 platforms, 10 accounts, unlimited users, and unlimited requests. Larger plans increase the number of platforms and accounts available. See Catchr pricing

‍Can I try the ChatGPT integration before choosing a plan?

Yes. Catchr offers a 14-day free trial with no credit card required.

You can use the trial to connect your marketing sources, authorize Catchr MCP in ChatGPT, and test questions using your own data before subscribing.

Still have a question ? 

Our teams is always here to responds to any question you could have about our data connector. 

Ask the account question before building another export.

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