Connect Adform to ChatGPT

Multi-Client Programmatic Pulse

Using the Catchr MCP, pull Adform data for [List of Client Account Names/IDs] over [Period] and compare it with [Comparison Period]. Build a one-page portfolio health table using Cost, Tracked Ads, Clicks, CTR (%), eCPM, Conversions, eCPA, Sales, Sales/Cost, and Viewable Rate (%) for IAB Viewability. Judge each client against [Client KPI Targets], label it on track, watch, or at risk, and rank the accounts that need attention. For every at-risk account, drill down by Campaign and Line Item to identify the main driver and give the consultant one concrete next action plus a client-safe explanation. Clearly mark unavailable metrics instead of inferring them.

Client Delivery and Viewability Debrief

Using the Catchr MCP, analyze Adform delivery for [Account Name/ID] over [Period] against [Booked Plan or Target]. Report Booked, Delivered, Delivered (%), Delivered Cost (%), Delivered Impressions (%), Delivered Clicks (%), and Delivered Conversions (%), then assess quality with Measurable Rate (%), Viewable Rate (%) for IAB Viewability, Avg. Viewability Time (sec.), Blocked Impressions (%), Avg. Frequency, CTR (%), and eCPA. Break material underdelivery, overdelivery, or quality issues down by Campaign, Line Item, and RTB Inventory Source. Produce a client-ready debrief with a concise executive summary, three evidence-based insights, and prioritized actions for the next period.

Cross-Account Inventory Risk Audit

Using the Catchr MCP, audit programmatic inventory across [List of Client Account Names/IDs] for [Period]. Break results down by Client, Campaign, RTB Inventory Source, RTB Domain, and Pre-bid Brand Safety Features, using Cost, Tracked Ads, Blocked Impressions (%), CTR (%), eCPM, Measurable Rate (%), Viewable Rate (%) for IAB Viewability, Conversions, eCPA, and Sales/Cost. Flag domains or inventory sources with meaningful spend and weak quality or outcomes relative to each account's baseline and [Risk Thresholds]. For each finding, show the supporting metrics, affected clients, estimated Cost exposure, and a specific recommendation such as review, exclusion, bid adjustment, or controlled retest.

Daily Client Priority Queue

Using the Catchr MCP, pull month-to-date Adform data for [List of Client Account Names/IDs] and compare each account with [Client Targets] and the expected pacing for [Current Date]. Use Cost, Delivered (%), Delivered Cost (%), Conversions, eCPA, Sales, Sales/Cost, CTR (%), Avg. Frequency, and Viewable Rate (%) for IAB Viewability. Rank the clients by urgency, explain in one sentence why each account is on track or at risk, and identify the Campaign or Line Item driving every material gap. End with a short today-only action list the freelancer can complete in priority order.

Monthly Client Performance Story

Using the Catchr MCP, create a client-ready Adform report for [Account Name/ID] covering [Period] versus [Comparison Period]. Explain changes in Cost, Tracked Ads, Clicks, CTR (%), eCPM, Avg. Frequency, Conversions, eCPA, Sales, Sales/Cost, Measurable Rate (%), and Viewable Rate (%) for IAB Viewability. Attribute the most important movements to Campaign, Line Item, Banner/Adgroups, or RTB Inventory Source, and quantify their contribution. Write in plain English with an executive summary, what worked, what did not, why the data suggests it happened, and three practical next steps; distinguish facts from interpretations.

Creative Fatigue and Visibility Check

Using the Catchr MCP, analyze daily Adform trends for every Banner/Adgroups combination on [Account Name/ID] over [Period]. Use Ad Creative Type, Banner Size, Avg. Frequency, CTR (%), eCPC, eCPM, Measurable Rate (%), Viewable Rate (%) for IAB Viewability, Avg. Viewability Time (sec.), Conversions, and eCPA. Flag creatives that meet [Minimum Volume Threshold] and show fatigue, visibility problems, or both compared with their earlier performance and the account median. For each flagged creative, show the trend evidence, state the likely issue cautiously, and recommend whether to refresh the creative, change its format, inspect inventory, or continue monitoring.

Commerce Efficiency Guardrail

Using the Catchr MCP, pull Adform performance for [Account Name/ID] over [Period] and compare it with [Comparison Period] and [Sales/Cost or eCPA Target]. Summarize Cost, Conversions, Sales, Sales/Cost, Cost/Sales, eCPA, Clicks, CTR (%), and eCPC, then identify whether commercial efficiency is improving or deteriorating. Break the change down by Campaign, Line Item, Country, and Device Type, quantify which segments contributed most to the movement, and recommend where to protect, reduce, or reallocate spend. Separate observed data from hypotheses and flag any missing conversion or sales data.

Product Retargeting Creative Scorecard

Using the Catchr MCP, evaluate product-retargeting performance for [Account Name/ID] over [Period]. Break results down by Product Retargeting, Banner/Adgroups, Ad Creative Type, and Banner Size, using Product Retargeting Item Views, CTR (Product Retargeting item, %), Clicks, Cost, Avg. Frequency, Conversions, Sales, eCPA, and Sales/Cost. Rank creatives by business outcome while enforcing [Minimum Volume Threshold], flag combinations with rising frequency and weakening CTR or Sales/Cost, and distinguish likely creative fatigue from poor format or placement performance. Return a keep, refresh, test, or pause recommendation for each material creative with the metrics that justify it.

Post-Click Revenue Leakage Finder

Using the Catchr MCP, map the post-click journey for [Account Name/ID] over [Period] using Clicks, Clicks to Landing Page, Visits, Bounce Rate (%), Conversions, Sales, eCPA, and Sales/Cost. Calculate the observable step rates from click to landing page, landing page to visit, visit to conversion, and conversion to sales value, and compare them with [Comparison Period]. Break the largest losses down by Campaign, Device Type, Country, Website Section, and Website Subsection. Identify the segments responsible for most leakage and give prioritized actions for landing-page, targeting, or campaign review without claiming causes the data cannot prove.

Ad Delivery Reconciliation Monitor

Using the Catchr MCP, reconcile the Adform delivery and conversion chain for [Account Name/ID or List of Accounts] over [Period]. By Date and Campaign, pull Eligible Impressions, Tracked Ads, Rendered Impressions, Verified Tracked Ads, Measurable Impressions, Viewable Impressions for IAB Viewability, Clicks, Clicks to Landing Page, Visits, Conversions, and Sales. Calculate each observable transition rate, monitor null coverage and abrupt discontinuities, and flag breaches of [Data Quality Thresholds]. Classify each issue as likely collection, delivery, viewability-measurement, or post-click tracking risk, show the affected dates and entities, and provide the exact validation check the data team should run next.

Statistical Outlier Early Warning

Using the Catchr MCP, pull daily Adform data for [Account Name/ID or All Connected Accounts] over [Period, e.g., the last 90 days]. For Cost, Tracked Ads, Clicks, CTR (%), eCPM, Conversions, eCPA, Sales, RTB Win Rate (%), RTB Loss Rate (%), Blocked Impressions (%), Measurable Rate (%), and Viewable Rate (%) for IAB Viewability, compare each day with its trailing 30-day mean and standard deviation. Flag deviations beyond [Threshold, e.g., 2 standard deviations], then drill down by Campaign, Line Item, and RTB Inventory Source to locate the contributor. Separate probable data-quality incidents from plausible delivery or performance events, state the evidence for the classification, and output a severity-ranked alert table.

RTB Supply and Fee Quality Model

Using the Catchr MCP, assess Adform supply quality for [Account Name/ID or List of Accounts] over [Period]. Break results down by RTB Inventory Source, RTB Domain, Programmatic Buy Type, Deal Name, and Country; analyze RTB Bids, RTB Win Rate (%), RTB Loss Rate (%), Cost, RTB Media Cost, DMP Data Cost (DSP), RTB Trading Desk Fee, RTB Custom Third-Party Fee, Tracked Ads, CTR (%), Viewable Rate (%) for IAB Viewability, Conversions, eCPA, Sales, and Sales/Cost. Calculate fee share of Cost and outcome efficiency where inputs are present, rank supply paths by scale, quality, and commercial return, and flag expensive or low-quality paths for investigation. Include methodology, missing-data caveats, and a reusable output table suitable for BI ingestion.

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

Connect Adform to ChatGPT

How to connect Adform to ChatGPT

Authorize the Adform account in Catchr

Install the Catchr app in ChatGPT

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.

See it in ChatGPT

Twelve Adform prompts for analyzing real account data.

Multi-Client Programmatic Pulse

Client Delivery and Viewability Debrief

Cross-Account Inventory Risk Audit

Multi-Client Programmatic Pulse

Adform to ChatGPT pricing

Starter

Growth

Scale

Adform to ChatGPT: FAQ

What Adform data can ChatGPT analyze through Catchr?

How granular can Adform analysis be in ChatGPT?

Can ChatGPT find efficiency and budget opportunities in Adform?

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

What types of prompts work best for Adform analysis?

Can I combine Adform with other data sources in ChatGPT?

Can I analyze multiple accounts or campaigns together?

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

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

Can ChatGPT change anything in Adform through Catchr?

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