Connect Outbrain DSP to ChatGPT

Multi-Account DSP Health Command Center

Using the Catchr MCP, pull Outbrain DSP data for [List of Client Account Names/IDs] over [Period] and compare it with [Comparison Period]. For each account, report Account Delivery Status, Total Spend, Impressions, Clicks, CTR, Avg. CPC, Avg. CPM, Visits, Bounce Rate, and % Viewable Impressions. Flag accounts with stopped or limited delivery, material performance deterioration, weak post-click quality, or low viewability against [Client Targets or Historical Baseline]. Rank the accounts by urgency and give the consultant one evidence-based action for every account requiring attention.

Client-Ready Native Inventory Review

Using the Catchr MCP, analyze Outbrain DSP performance for [Client Account Name/ID] over [Period], broken down by Campaign Name, Publisher, Placement, Placement Type, Device, and Environment. Compare Total Spend, Impressions, Clicks, CTR, Avg. CPC, Avg. CPM, Visits, Bounce Rate, Pageviews per Visit, and % Viewable Impressions with [Comparison Period]. Identify the inventory combinations driving efficient reach and engaged visits, isolate placements consuming spend with weak engagement or viewability, and produce a plain-English client brief with wins, risks, and three prioritized optimization actions.

Budget, Bid and Delivery Risk Scan

Using the Catchr MCP, review Outbrain DSP campaigns and ad groups across [List of Client Accounts] as of [Review Date] and over [Performance Period]. Use Campaign Delivery Status, Ad Group Delivery Status, Ad Group State, Ad Group Daily Budget, Ad Group Bid, Ad Group Bidding Type, Ad Group Start Date, Ad Group End Date, Ad Group Frequency Capping, Total Spend, Yesterday Spend, Impressions, Clicks, and CTR. Identify stalled delivery, pacing risk, spend concentration, bids that appear misaligned with delivery, and groups nearing their end date without sufficient activity. Return a client-by-client alert list with severity, supporting evidence, and the next action to take.

Morning Client Priority Queue

Using the Catchr MCP, pull Outbrain DSP results for [List of Client Account Names/IDs] for [Today or Month to Date] and compare them with [Baseline Period]. For each client, review Account Delivery Status, Campaign Delivery Status, Total Spend, Yesterday Spend, Impressions, Clicks, CTR, Avg. CPC, Visits, Bounce Rate, and % Viewable Impressions. Flag stopped delivery, abnormal spend, engagement decline, and viewability risk, then rank clients by urgency and budget exposure. Give me one sentence on what changed and the first task I should complete today for each priority client.

Monthly Client DSP Performance Story

Using the Catchr MCP, pull Outbrain DSP data for [Client Account Name/ID] for [Reporting Period] and [Previous Period]. Summarize Total Spend, Impressions, Clicks, CTR, Avg. CPC, Avg. CPM, Visits, Bounce Rate, Pageviews per Visit, Avg. Cost per Non-Bounced Visit, and % Viewable Impressions, then explain the most important changes by Campaign Name, Publisher, Placement Type, and Device. Write a concise client-ready report covering what improved, what declined, the evidence behind each conclusion, and the optimization priorities for [Next Period], without claiming conversion or revenue outcomes that are not present in the connector.

Video Creative Completion Optimizer

Using the Catchr MCP, analyze Outbrain DSP video activity for [Client Account Name/ID] over [Period] by Campaign Name, Ad Group Name, Creative Title, Creative Video Asset Id, Publisher, Device, and Environment. Use Video Start, Video Progress 3s, Video First Quartile, Video Midpoint, Video Third Quartile, Video Complete, Avg. CPV, Avg. CPCV, Total Spend, Impressions, and % Viewable Impressions. Calculate progression and completion rates where denominators are available, identify the stages and creatives with the largest audience drop-off, and create a prioritized test plan covering hooks, length, format, placement, and device targeting.

Post-Click Shopping Quality Diagnostic

Using the Catchr MCP, analyze Outbrain DSP traffic for [Account Name/ID] over [Period] and compare it with [Comparison Period]. Break down Total Spend, Clicks, CTR, Visits, New Users, Returning Users, Bounce Rate, Non-Bounced Visits, Pageviews, Pageviews per Visit, Time on Site, Avg. Cost per Visit, Avg. Cost per Non-Bounced Visit, and Avg. Cost per Pageview by Campaign Name and Ad Group Name. Rank campaigns by their ability to generate engaged site visits, flag paid traffic that is cheap but low quality, and recommend specific budget, audience, or landing-page tests. Do not infer purchases, revenue, or ROAS because those fields are not available in this connector.

Native Creative Engagement Winner Finder

Using the Catchr MCP, compare Outbrain DSP creatives for [Account Name/ID] over [Period] using Creative Title, Creative Description, Creative Call To Action, Creative Brand Name, Creative Type, Creative Image Url, Creative Image Width, Creative Image Height, Ad State, Impressions, Clicks, CTR, Visits, Bounce Rate, Pageviews per Visit, and Time on Site. Apply [Minimum Impression or Spend Threshold] before judging performance, separate proven winners, promising tests, and underperformers, and identify recurring title, CTA, image-format, and creative-type patterns. Recommend which creatives to scale, refresh, or stop and propose three concrete native-ad tests.

Publisher and Device Traffic Quality Map

Using the Catchr MCP, pull Outbrain DSP data for [Account Name/ID] over [Period], segmented by Publisher, Placement, Placement Type, Device, Operating System, Environment, Country, and State / Region. Compare Total Spend, Impressions, Clicks, CTR, Avg. CPC, Visits, Bounce Rate, Pageviews per Visit, Avg. Cost per Non-Bounced Visit, and % Viewable Impressions across segments. Build a traffic-quality map that highlights where engaged shoppers are being acquired efficiently and where spend is producing low-viewability or high-bounce visits, then recommend exclusions, bid adjustments, or budget reallocations with the data behind each action.

DSP Extraction and Record Integrity Audit

Using the Catchr MCP, audit Outbrain DSP data for [Account Name/ID or All Connected Accounts] over [Period] using Extracted Date, Date, Account Id, Campaign Id, Ad Group Id, Ad Id, Creative Id, Campaign Delivery Status, Total Spend, Impressions, Clicks, CTR, Visits, and Pageviews. Detect stale extraction timestamps, missing dates or identifiers, duplicate dimensional records, gaps in daily coverage, negative metrics, Clicks above Impressions, and CTR values that do not reconcile with clicks and impressions within [Tolerance]. Return an exception table with account, date, entity IDs, failed rule, observed values, severity, and recommended validation step.

Viewability Reconciliation Monitor

Using the Catchr MCP, validate Outbrain DSP viewability for [Account Name/ID or All Connected Accounts] over [Period], grouped by Date, Campaign Name, Publisher, Placement, Placement Type, Device, and Environment. Reconcile Impressions with Measurable Impressions and Not-Measurable Impressions, then reconcile Measurable Impressions with Viewable Impressions and Not-Viewable Impressions. Compare those counts with % Measurable Impressions, % Viewable Impressions, Impression Distribution (Viewable), Impression Distribution (Not-Viewable), and Impression Distribution (Not-Measurable) within [Tolerance]. Flag missing, impossible, or inconsistent values and quantify the affected spend and impression volume for each issue.

Daily DSP Outlier Detection

Using the Catchr MCP, pull at least [Lookback Period, e.g., 90 days] of daily Outbrain DSP data for [Account Name/ID or List of Accounts], segmented by Account Name, Campaign Name, Publisher, Placement Type, Device, and Country. Monitor Total Spend, Impressions, Clicks, CTR, Avg. CPC, Avg. CPM, Visits, Bounce Rate, Pageviews per Visit, and % Viewable Impressions. Compare each day with its trailing [Baseline Window, e.g., 28-day] mean and standard deviation, flag deviations beyond [Outlier Threshold, e.g., 2 standard deviations], and classify each outlier as likely data-quality, delivery, inventory-mix, or genuine performance change with the supporting cross-metric evidence and recommended investigation.

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

Connect Outbrain DSP to ChatGPT

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How to connect Outbrain DSP to ChatGPT ?

Authorize the Outbrain DSP 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 Outbrain DSP prompts for analyzing real account data.

Outbrain DSP to ChatGPT FAQs

What Outbrain DSP data can ChatGPT analyze through Catchr?

How granular can Outbrain DSP analysis be in ChatGPT?

Can ChatGPT find efficiency and budget opportunities in Outbrain DSP?

Can ChatGPT diagnose targeting, creative, or conversion issues in Outbrain DSP?

What types of prompts work best for Outbrain DSP analysis?

Can I combine Outbrain DSP with other data sources in ChatGPT?

Can I analyze multiple accounts or campaigns together?

What do I need to connect Outbrain DSP to ChatGPT with Catchr?

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

Can ChatGPT change anything in Outbrain DSP 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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