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Connect Youtube Analytics to ChatGPT

Connect Youtube Analytics 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 Youtube Analytics to ChatGPT ?

Three steps to your first source-aware prompt.

Step one

Authorize the Youtube Analytics account in Catchr

Select Youtube Analytics, sign in, and choose the client or business accounts you want to connect.

Client A · Connected sources
5 sources ready
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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 Youtube Analytics 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
Multi-Client Channel Morning Pulse
Using the Catchr MCP, pull YouTube data for [List of Client Channel IDs] over [Current Period, e.g., yesterday or month to date] and [Comparison Period]. For each channel, review Views, Estimated Minutes Watched, Average View Duration, Average View Percentage, Subscribers Gained, Subscribers Lost, Likes, Comments, and Shares against [Client-Specific KPI Targets]. Label each channel Healthy, Watch, or Critical, trace every material change to Video Title and Video ID where available, rank the accounts that need attention, and give the consultant one evidence-based action plus the metric to recheck for each affected client.
Client-Ready Content and Audience Review
Using the Catchr MCP, analyze [Client Channel ID] for [Reporting Period] versus [Comparison Period]. Break down Views, Estimated Minutes Watched, Average View Duration, Average View Percentage, Likes, Comments, Shares, Videos Added To Playlists, and net subscriber change by Video Title, Video Published At, Creator Content Type, Insight Traffic Source Type, Subscribed Status, Country, Age Group, Gender, and Device Type where populated. Produce a client-ready report covering the strongest and weakest videos, the audiences and discovery sources driving the result, confirmed findings versus hypotheses, and three prioritized content actions with a success KPI for each.
Portfolio Anomaly and Publishing Risk Monitor
Using the Catchr MCP, analyze daily YouTube data for [List of Client Channel IDs] over [Analysis Period] against [Baseline Period]. Detect material spikes, drops, or discontinuities in Views, Estimated Minutes Watched, Average View Percentage, Subscribers Gained, Subscribers Lost, Likes, Comments, and Shares, then localize each anomaly by Channel Title, Video Title, Video ID, Insight Traffic Source Type, and Device Type where supported. Also flag actionable operational risks from Channel Audit Overall Good Standing, Video Upload Status, Video Processing Status, Video Privacy Status, or Video Rejection Reason; quantify the impact, separate confirmed evidence from hypotheses, and return a ranked consultant action plan with the exact validation check for each issue.
Daily Client Channel Priority Queue
Using the Catchr MCP, pull month-to-date YouTube data for [List of Client Channel IDs] and compare each channel with [Client Monthly Targets] and [Previous-Month-to-Date Period]. Use the target relevant to each client, such as Views, Estimated Minutes Watched, Average View Percentage, Subscribers Gained, net subscriber change, Likes, Comments, or Shares, and calculate progress against the share of the month elapsed. Rank clients by urgency and business impact, identify the Video Title or Insight Traffic Source Type causing the largest measurable gap, and tell the freelancer which client to handle first with one concrete action and follow-up KPI per off-track account.
Monthly YouTube Client Performance Story
Using the Catchr MCP, create a client-ready YouTube report for [Client Channel ID] covering [Reporting Month] versus [Previous Month]. Summarize Views, Estimated Minutes Watched, Average View Duration, Average View Percentage, Subscribers Gained, Subscribers Lost, Likes, Comments, Shares, Videos Added To Playlists, and Estimated Revenue where relevant, then explain the most important changes by Video Title, Video Published At, Creator Content Type, Insight Traffic Source Type, Country, and Subscribed Status. Write in plain English with an executive summary, what worked, what declined, evidence for each conclusion, any unavailable or incomplete data, and three priorities for [Next Month].
Video Optimization Backlog
Using the Catchr MCP, analyze [Client Channel ID] over [Analysis Period] by Video Title and Video ID, using Video Published At, Video Duration, Views, Estimated Minutes Watched, Average View Duration, Average View Percentage, Likes, Comments, Shares, Subscribers Gained, Card Click Rate, and Videos Added To Playlists. Apply [Minimum Days Live and View Threshold], classify videos as scale, refresh, repurpose, or retire, and diagnose whether each weak result is most consistent with low reach, poor retention, weak engagement, or an ineffective call to action. Return a ranked backlog with the supporting metrics, a specific title, thumbnail, opening-hook, structure, or card change, and the KPI to review after [Test Window].
Product Video Intent Funnel
Using the Catchr MCP, analyze YouTube content for [Store Channel ID] over [Period] versus [Comparison Period], focusing on videos linked to [Product, Collection, or Campaign]. By Video Title and Video ID, review Views, Average View Percentage, Estimated Minutes Watched, Card Impressions, Card Clicks, Card Click Rate, Annotation Impressions, Annotation Clicks, Annotation Click Through Rate, Videos Added To Playlists, and Shares. Apply [Minimum View or Card Impression Threshold], rank videos by progression from viewing to measurable on-platform intent, identify the largest engagement or click-through leak, and recommend the next title, thumbnail, hook, card, or call-to-action test with a validation KPI; clearly state that these YouTube fields do not prove store purchases.
Product Audience Fit Map
Using the Catchr MCP, pull YouTube performance for [Store Channel ID] over [Period] for [Product Video Set or List of Video IDs]. Compare Views, Estimated Minutes Watched, Average View Duration, Average View Percentage, Likes, Comments, Shares, Subscribers Gained, and Videos Added To Playlists across Age Group, Gender, Country, Device Type, Operating System, Subscribed Status, and Insight Traffic Source Type where available. Require [Minimum Audience Volume], identify which audience segments retain and engage most strongly with each product theme, flag segments with high views but weak watch quality, and return a prioritized content and distribution plan with one experiment and success metric per segment.
Commerce Content Publishing and Refresh Queue
Using the Catchr MCP, audit [Store Channel ID] over [Period] at Video Title and Video ID level using Video Published At, Video Duration, Video Has Custom Thumbnail, Video Caption, Video Tags, Video Category ID, Video Embeddable, Video Privacy Status, Video Upload Status, Views, Average View Percentage, Subscribers Gained, Card Click Rate, and Shares where populated. Identify product videos that are unpublished, restricted, incomplete, or underperforming after [Minimum Days Live and View Threshold], distinguish publishing or metadata issues from weak audience response, and produce a ranked queue of fixes and refreshes with the exact field evidence, recommended action, owner, and KPI to review after [Test Window].
YouTube Analytics Integrity Audit
Using the Catchr MCP, audit YouTube data for [Channel ID or All Connected Channels] over [Period] at Date, Channel ID, and Video ID level. Review Views, Estimated Minutes Watched, Average View Duration, Average View Percentage, Subscribers Gained, Subscribers Lost, Likes, Comments, Shares, Card Impressions, Card Clicks, and Card Click Rate. Flag missing dates or identifiers, duplicate keys, negative counts, Average View Percentage or click rates outside their valid range, clicks exceeding impressions, abrupt metric discontinuities, and material inconsistencies between estimated watch time and views multiplied by average view duration. Return a reproducible exception table with observed values, failed rule, severity, confidence level, and the exact extraction or source-system validation step.
Daily Channel and Video Outlier Monitor
Using the Catchr MCP, pull at least [Lookback Period, e.g., 90 days] of daily YouTube data for [Channel ID or All Connected Channels], grouped by Date, Channel ID, Video ID, and Insight Traffic Source Type where available. For Views, Estimated Minutes Watched, Average View Duration, Average View Percentage, Subscribers Gained, Subscribers Lost, Likes, Comments, and Shares, compare each day with its trailing [Baseline Window, e.g., 28 days] and flag changes beyond [Threshold, e.g., 2 standard deviations or 30%]. Apply [Minimum Volume Threshold], distinguish probable extraction or tracking breaks from publishing cadence, traffic-source shifts, audience response, or genuine content performance changes, and provide the evidence plus the next validation query for every outlier.
Audience and Discovery Coverage Audit
Using the Catchr MCP, assess analytics coverage for [Channel ID or All Connected Channels] over [Period] using Age Group, Gender, Country, Province, Device Type, Operating System, Subscribed Status, Insight Traffic Source Type, Sharing Service, Video ID, Views, Estimated Minutes Watched, Average View Percentage, and Viewer Percentage. For each dimension, quantify blank, unknown, or unclassified values and reconcile segmented Views and watch time with the corresponding unsegmented channel totals within [Tolerance]. Identify dimensions or dates with incomplete or unstable coverage, distinguish expected privacy or reporting limitations from likely extraction issues, and return a prioritized data-quality report with affected scope, magnitude, confidence, and the exact check needed before the fields are used in dashboards.
Replace [variables] Facts ≠ hypotheses Action + follow-up metric

Youtube Analytics to ChatGPT FAQs

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

What Youtube Analytics data can ChatGPT analyze through Catchr?

ChatGPT can query connected Youtube Analytics data for content, reach, engagement, audience, follower, traffic, and video reporting.

Representative measures include Views, Estimated Minutes Watched, Average View Duration, Subscribers Gained, and Estimated Revenue. Useful breakdowns include Date, Country, Device Type, Insight Traffic Source Type, and Subscribed Status. The exact field set depends on the selected dataset and compatible reporting reporting level.

How granular can Youtube Analytics analysis be in ChatGPT?

The available detail depends on the fields returned for the selected dataset. Useful breakdowns include Date, Country, Device Type, Insight Traffic Source Type, and Subscribed Status.

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

Can ChatGPT identify the content that performs best in Youtube Analytics?

Yes. ChatGPT can rank posts, videos, or formats by the engagement and reach signals that matter to the channel. Relevant fields include Views, Estimated Minutes Watched, Average View Duration, Subscribers Gained, and Estimated Revenue.

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

Can ChatGPT analyze audience growth and publishing patterns in Youtube Analytics?

Yes. ChatGPT can compare audience, timing, format, discovery, or follower trends across a consistent period. Useful breakdowns include Date, Country, Device Type, Insight Traffic Source Type, and Subscribed Status.

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 Youtube Analytics analysis?

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

  • Monitor: “Multi-Client Channel Morning Pulse”
  • Diagnose: “YouTube Analytics Integrity Audit”
  • Find opportunities: “Product Audience Fit Map”
  • Report: “Client-Ready Content and Audience Review”

Can I combine Youtube Analytics with other data sources in ChatGPT?

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

Yes, provided each one is connected and available through Catchr MCP. Ask for separate results first, then create the combined view.

Specify the account, audience, content format, timezone, period, and objective. This keeps one large entity or a definition mismatch from distorting the comparison.

What do I need to connect Youtube Analytics to ChatGPT with Catchr?

You need access that can authorize and view the relevant Youtube Analytics 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 Youtube Analytics 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 published-content, audience, or reporting date, together with the timezone, requested period, and any missing intervals before interpreting a trend.

Can ChatGPT change anything in Youtube Analytics through Catchr?

No. Catchr MCP provides Youtube Analytics data for analysis; it does not give ChatGPT permission to publish content, reply to users, or change profile and channel settings.

Use the result to prepare an action plan, then make operational changes in Youtube Analytics. 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. 

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