Connect Xandr to ChatGPT

Multi-Advertiser Programmatic Health Check

Using the Catchr MCP, pull Xandr data for [List of Client Accounts or Advertiser IDs] over [Period] and compare it with [Comparison Period] and [Client KPI Targets]. For each Advertiser Id, summarize Spend, Imps, Clicks, Ctr, Cpm, Total Convs, Ecpa, Total Revenue, View Rate, and Avg Bid Reduction, then drill down by Campaign Name, Line Item Name, and Bid Type for every material variance. Label each client Healthy, Watch, or Critical, rank the accounts the agency consultant should review first, and give one evidence-based bidding, budget-allocation, inventory, or measurement action per flagged account.

Client-Ready Programmatic Performance Debrief

Using the Catchr MCP, analyze Xandr performance for [Client Account or Advertiser ID] over [Reporting Period] versus [Previous Period]. Report Spend, Imps, Clicks, Ctr, Cpm, Total Convs, Ecpa, Total Revenue, Post Click Convs, Post View Convs, Post Click Revenue, Post View Revenue, View Measurement Rate, and View Rate. Break the most important changes down by Insertion Order Name, Campaign Name, Line Item Name, Deal Name, Publisher Name, and Supply Type; quantify which entities drove each change; and produce a client-ready debrief with an executive summary, three wins, three risks, and prioritized next actions. Separate measured facts from interpretations and do not present attributed conversions as proven incrementality.

Cross-Client Inventory and Deal Watchlist

Using the Catchr MCP, audit Xandr inventory quality for [List of Client Accounts or Advertiser IDs] over [Period]. Analyze Imps, Media Cost, Cpm, Ctr, View Measurement Rate, View Rate, Total Convs, Ecpa, and Total Revenue by Deal Name, Publisher Name, Seller Member Name, Placement Name, Supply Type, Media Type, and Geo Country Name. Apply [Minimum Impression or Spend Threshold] and compare each segment with [Quality and Efficiency Targets] plus [Comparison Period]. Flag expensive, low-viewability, low-conversion, or deteriorating inventory, identify the affected client, Campaign Name, and Line Item Name, and return a severity-ranked watchlist with evidence and a specific exclusion, bid adjustment, deal review, or controlled-retest recommendation.

Morning Client Optimization Queue

Using the Catchr MCP, pull month-to-date Xandr data for [List of Client Accounts or Advertiser IDs] and compare each client with [Expected Spend Pacing], [Client KPI Targets], and [Recent Baseline]. Use Spend, Imps, Ctr, Cpm, Total Convs, Ecpa, Total Revenue, View Rate, and Avg Bid Reduction, then identify the Campaign Name, Line Item Name, Bid Type, Deal Name, or Publisher Name driving every material gap. Rank clients by urgency, explain in one sentence why each is on track or at risk, and give the first bidding, inventory, creative, or tracking action the freelancer should take today.

Monthly Xandr Client Report

Using the Catchr MCP, create a client-ready Xandr report for [Client Account or Advertiser ID] covering [Reporting Period] versus [Previous Period]. Explain changes in Spend, Imps, Clicks, Ctr, Cpm, Total Convs, Ecpa, Total Revenue, Post Click Convs, Post View Convs, View Measurement Rate, and View Rate, and attribute the largest movements to Insertion Order Name, Campaign Name, Line Item Name, Creative Name, Deal Name, Publisher Name, or Supply Type. Write in plain English with an executive summary, what worked, what did not, the evidence behind each conclusion, and three prioritized actions for [Next Period], while describing attribution limitations explicitly.

Bid and Inventory Optimization Backlog

Using the Catchr MCP, analyze Xandr delivery for [Client Account or Advertiser ID] over [Period] by Campaign Name, Line Item Name, Bid Type, Venue, Deal Name, Publisher Name, Placement Name, Supply Type, and Creative Name. Compare Spend, Media Cost, Avg Bid Reduction, Imps, Cpm, Ctr, View Rate, Total Convs, Ecpa, and Total Revenue against [Client Targets or Baseline], applying [Minimum Volume Threshold]. Identify inefficient bids, weak inventory, underperforming creatives, and promising scale opportunities, then create a prioritized backlog with evidence, proposed change, expected business effect, success metric, effort level, and review date for each task.

Programmatic Revenue Efficiency Scorecard

Using the Catchr MCP, pull Xandr data for [E-commerce Advertiser ID] over [Period] and compare it with [Comparison Period] and [CPA or Revenue Return Target]. Summarize Spend, Imps, Clicks, Ctr, Total Convs, Conv Rate, Ecpa, and Total Revenue, and calculate attributed revenue return as Total Revenue divided by Spend only when both values are present and compatible. Break results down by Campaign Name, Line Item Name, Creative Name, Deal Name, and Supply Type, rank the segments that generate the strongest attributed revenue at meaningful scale using [Minimum Spend or Conversion Threshold], flag inefficient spend, and recommend where to scale, hold, test, or reduce investment.

Post-Click vs Post-View Revenue Analyzer

Using the Catchr MCP, analyze attribution for [E-commerce Advertiser ID] over [Period] versus [Comparison Period]. Compare Post Click Convs, Post View Convs, Post Click Revenue, Post View Revenue, Total Convs, and Total Revenue by Pixel Id, Campaign Name, Line Item Name, Creative Name, Publisher Name, and Deal Name. Calculate each path's share of attributed conversions and revenue, flag abrupt shifts in the post-click versus post-view mix or pixels with missing outcomes, and identify which campaigns and inventory sources drive those shifts. Finish with three measurement or media-allocation checks to run next, clearly stating that Xandr attribution does not by itself prove causal sales lift.

Commerce Inventory Expansion Planner

Using the Catchr MCP, evaluate programmatic inventory for [E-commerce Advertiser ID] over [Test Period] using Deal Name, Publisher Name, Seller Member Name, Placement Name, Supply Type, Media Type, Size, and Geo Country Name. Compare Spend, Imps, Cpm, Ctr, View Rate, Total Convs, Ecpa, and Total Revenue against [Control Period or Benchmark] after applying [Minimum Volume Threshold]. Identify inventory pockets with scalable attributed revenue, segments that are costly or poorly viewable, and creative-size or media-type mismatches. Return a prioritized expansion plan specifying the segment to scale or test, proposed bid or budget change, risk, success metric, and review window.

Conversion Attribution Integrity Audit

Using the Catchr MCP, audit Xandr attribution data for [Advertiser ID or All Connected Accounts] over [Period] by Date, Advertiser Id, Campaign Id, Line Item Id, and Pixel Id. Check null coverage and reconcile Total Convs with Post Click Convs plus Post View Convs, and Total Revenue with Post Click Revenue plus Post View Revenue, only where the metrics share a compatible reporting grain. Flag negative values, duplicate identifier-date rows, unexplained reconciliation gaps, abrupt changes in the click-view mix, and records affected by Adjustment Id. Return an exception table with the identifiers, failed rule, observed values, severity, and exact source or pipeline validation step required.

Daily Delivery and Bidding Outlier Monitor

Using the Catchr MCP, pull at least [Lookback Period, e.g., 90 days] of Xandr data for [Advertiser ID or All Connected Accounts], grouped by Date, Advertiser Id, Campaign Id, Line Item Id, Bid Type, and Supply Type. Monitor Spend, Media Cost, Imps, Cpm, Ctr, Avg Bid Reduction, View Measurement Rate, View Rate, Total Convs, Ecpa, and Total Revenue. Compare each daily value with its trailing [Baseline Window, e.g., 30-day] mean and standard deviation, flag deviations beyond [Threshold, e.g., 2 standard deviations] plus null or zero runs, and classify each anomaly as likely extraction, bidding-phase, inventory-mix, attribution, or genuine performance change with supporting evidence and the next validation query.

Programmatic Reporting Grain and Currency QA

Using the Catchr MCP, validate Xandr reporting for [Advertiser ID or All Connected Accounts] over [Period] by Date, Advertiser Id, Advertiser Currency, Insertion Order Id, Campaign Id, Line Item Id, Creative Id, Deal Id, Publisher Id, and Placement Id. Test identifier and dimension completeness, confirm Billing Period Start Date is not after Billing Period End Date, compare Spend with Spend Adv Curr and Ecpa with Ecpa Adv Curr only within a single Advertiser Currency, and verify that Imps, Clicks, Total Convs, Media Cost, Spend, and Total Revenue are non-negative. Detect duplicate or conflicting rows at [Expected Grain], quantify the affected spend and conversions, and return a BI-ready issue table with severity, suspected pipeline stage, and recommended remediation.

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

Connect Xandr to ChatGPT

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How to connect Xandr to ChatGPT ?

Authorize the Xandr 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 Xandr prompts for analyzing real account data.

Xandr to ChatGPT FAQs

What Xandr data can ChatGPT analyze through Catchr?

How granular can Xandr analysis be in ChatGPT?

Can ChatGPT find efficiency and budget opportunities in Xandr?

Can ChatGPT diagnose targeting, creative, or conversion issues in Xandr?

What types of prompts work best for Xandr analysis?

Can I combine Xandr with other data sources in ChatGPT?

Can I analyze multiple accounts or campaigns together?

What do I need to connect Xandr to ChatGPT with Catchr?

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

Can ChatGPT change anything in Xandr 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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