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Connect Instagram Public Data to ChatGPT

Connect Instagram Public Data 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 Instagram Public Data to ChatGPT ?

Three steps to your first source-aware prompt.

Step one

Authorize the Instagram Public Data account in Catchr

Select Instagram Public Data, 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 Instagram Public Data 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 Public Profile Pulse
Using the Catchr MCP, pull Instagram Public Data for [List of Client Profiles] over [Period] and compare it with [Comparison Period]. For each profile, use the latest Profile Followers, Profile Follows, Profile Post Count, Biography, and Website snapshot, then summarize posting volume, Media Likes, Comments, and the median visible interaction rate proxy per post, calculated as (Media Likes + Comments) / latest Profile Followers. Label each client Stable, Watch, or Priority against [Client Baseline or Target], explain the evidence behind every Watch or Priority label, and rank the profiles the consultant should review first. Clearly label the interaction rate as a public-data proxy rather than reach-based engagement.
Client Competitor Content Benchmark
Using the Catchr MCP, benchmark [Client Instagram Profile] against [List of Competitor Profiles] for [Period]. Deduplicate posts by Post ID, then compare posting frequency, Post Type mix, median Media Likes, median Comments, and the median visible interaction rate proxy (Media Likes + Comments) / latest Profile Followers. Use Post Caption, Post Hashtags, Post Hashtag Count, and Post Created to identify themes, formats, hashtag patterns, and publishing days associated with each profile's strongest posts. Produce a client-ready comparison with the client's advantages, gaps, three competitor patterns worth testing, and three concrete content actions, without claiming sales, reach, or causality.
Executive Organic Presence Brief
Using the Catchr MCP, analyze Instagram Public Data for [Client Profile] over [Reporting Period] versus [Previous Period]. Report changes in the latest Profile Followers and Profile Post Count snapshots, number of unique posts from Post ID, Post Type distribution, median Media Likes, median Comments, and top posts with Link To Post. Review Biography and Website for any observable positioning changes, and use Post Caption and Post Hashtags to explain the content patterns behind the strongest and weakest visible interactions. Write a concise client-facing brief covering wins, risks, notable posts, limitations of public data, and a prioritized 30-day action plan.
Morning Client Attention Queue
Using the Catchr MCP, pull Instagram Public Data for [List of Client Profiles] for [Recent Period] and compare it with [Baseline Period]. For each client, use the latest Profile Followers and Profile Post Count snapshots, count unique posts by Post ID, and compare median Media Likes, median Comments, Post Type mix, and posting recency from Post Created. Flag unusual inactivity, a decline in visible interactions, or a material profile change in Biography or Website, then return a ranked morning queue with what changed, why it matters, the supporting Link To Post where relevant, and the first action to take for each priority client.
Monthly Organic Client Report
Using the Catchr MCP, analyze Instagram Public Data for [Client Profile] for [Reporting Period] versus [Previous Period]. Deduplicate by Post ID and compare unique post count, Post Type distribution, median Media Likes, median Comments, and median visible interaction rate proxy using the latest Profile Followers. Highlight the best and weakest posts with Link To Post, and use Post Caption, Post Hashtags, Post Caption Length (without Hashtags), and Post Hashtag Count to explain recurring content patterns. Write a plain-English, client-ready report with achievements, concerns, public-data limitations, work priorities, and three measurable tests for [Next Period].
Evidence-Based Content Plan
Using the Catchr MCP, study Instagram Public Data for [Client Profile] over [Lookback Period] and build a content plan for [Planning Period]. Rank unique posts using Media Likes, Comments, and the visible interaction rate proxy (Media Likes + Comments) / latest Profile Followers, then compare winners and underperformers by Post Type, posting day and hour from Post Created, Post Caption Length (without Hashtags), Post Hashtag Count, Post Caption, and Post Hashtags. Turn the repeatable patterns into [Number] content briefs, each with a topic, format, caption angle, hashtag direction, suggested publishing window, success metric, and a Link To Post example, while distinguishing correlation from proven cause.
Product Content Resonance Finder
Using the Catchr MCP, pull Instagram Public Data for [Brand Profile] over [Period]. Use Post Caption and Post Hashtags to group unique posts into [Product Categories, Collections, Campaigns, or Launch Themes], then compare Post Type, Media Likes, Comments, and the visible interaction rate proxy (Media Likes + Comments) / latest Profile Followers across those groups. Require at least [Minimum Posts] per group, surface the strongest and weakest product-content combinations with Link To Post, and recommend three specific creative, caption, or hashtag tests for the next merchandising cycle. Treat interactions as audience-interest signals only; do not infer clicks, orders, revenue, or ROAS.
Competitor Launch Watch
Using the Catchr MCP, monitor Instagram Public Data for [List of Competitor Profiles] over [Period]. From Post Created, Post Caption, Post Hashtags, Post Type, and Link To Post, identify likely product launches, restocks, promotions, collaborations, or seasonal pushes using [Keywords or Product Terms]. For each detected theme, summarize posting cadence, median Media Likes, median Comments, and visible interaction rate proxy using the latest Profile Followers, then compare competitors and rank the themes generating the strongest observable response. Deliver a launch watchlist plus differentiated content opportunities for [Brand], while marking launch classification as an inference from public post text.
Instagram Storefront Readiness Audit
Using the Catchr MCP, audit the public Instagram storefront of [Brand Profile] as of [Snapshot Date] and review its posts over [Period]. Check whether Biography clearly states the offer and value proposition, whether Website is present, and whether recent Post Captions contain recognizable product, benefit, urgency, or call-to-action language from [Brand Messaging Guidelines]. Compare those patterns by Post Type using Media Likes and Comments, and include representative Link To Post examples. Return a prioritized audit of positioning gaps, profile fixes, caption opportunities, and five concrete copy tests; do not claim that Website presence or calls to action produced traffic or sales because those outcomes are not available in this connector.
Public Dataset Integrity Audit
Using the Catchr MCP, audit Instagram Public Data for [Profile or All Connected Profiles] over [Period]. Validate completeness and consistency for Instagram ID, Username, Name, Post ID, Post Created, Extracted Date, Post Type, Post Media URL, Link To Post, Media Likes, Comments, Profile Followers, Profile Follows, and Profile Post Count. Flag duplicate Post IDs, conflicting profile identities, missing post identifiers or timestamps, negative counts, changing static post attributes across extracts, and records where Extracted Date precedes Post Created. Return an exception table with profile, Post ID, failed rule, observed values, severity, and recommended remediation or source check.
Profile Snapshot Trend Model
Using the Catchr MCP, pull Instagram Public Data for [List of Profiles] across [Snapshot Period]. Build one daily profile snapshot per Instagram ID and Extracted Date, avoiding sums across repeated post rows, and track the latest Profile Followers, Profile Follows, and Profile Post Count. Calculate day-over-day and week-over-week changes, reconcile Profile Post Count movements with unique Post IDs and Post Created when possible, and flag impossible reversals, duplicate snapshots, missing extraction days, or jumps above [Threshold]. Output a tidy trend table, a data-quality exception table, and a concise explanation of which movements appear real versus extraction artifacts.
Visible Interaction Outlier Monitor
Using the Catchr MCP, pull at least [Lookback Period, e.g., 90 days] of Instagram Public Data for [Profile or List of Profiles]. Deduplicate posts by Post ID and model Media Likes, Comments, and the visible interaction rate proxy (Media Likes + Comments) / latest Profile Followers by Post Type and publication cohort from Post Created. Compare each post with the rolling [Baseline Window] median and median absolute deviation for its profile and Post Type, flag outliers beyond [Threshold], and use Post Caption, Post Hashtags, Post Caption Length (without Hashtags), and Post Hashtag Count to describe possible content drivers. Classify every alert as likely genuine content performance, low-volume uncertainty, profile-size effect, or data-quality issue, and provide the evidence for that classification.
Replace [variables] Facts ≠ hypotheses Action + follow-up metric

Instagram Public Data to ChatGPT FAQs

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

What Instagram Public Data data can ChatGPT analyze through Catchr?

ChatGPT can query connected Instagram Public Data data for content, reach, engagement, audience, follower, traffic, and video reporting.

Representative measures include Profile Followers, Profile Follows, Profile Post Count, Media Likes, and Comments. Useful breakdowns include Username, Name, Post Type, Post Caption, and Post Hashtags. The exact field set depends on the selected dataset and compatible reporting reporting level.

How granular can Instagram Public Data analysis be in ChatGPT?

The available detail depends on the fields returned for the selected dataset. Useful breakdowns include Username, Name, Post Type, Post Caption, and Post Hashtags.

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 Instagram Public Data?

Yes. ChatGPT can rank posts, videos, or formats by the engagement and reach signals that matter to the channel. Relevant fields include Profile Followers, Profile Follows, Profile Post Count, Media Likes, and Comments.

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

Can ChatGPT analyze audience growth and publishing patterns in Instagram Public Data?

Yes. ChatGPT can compare audience, timing, format, discovery, or follower trends across a consistent period. Useful breakdowns include Username, Name, Post Type, Post Caption, and Post Hashtags.

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 Instagram Public Data analysis?

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

  • Monitor: “Multi-Client Public Profile Pulse”
  • Diagnose: “Public Dataset Integrity Audit”
  • Find opportunities: “Evidence-Based Content Plan”
  • Report: “Monthly Organic Client Report”

Can I combine Instagram Public Data 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 Instagram profiles 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 Instagram Public Data to ChatGPT with Catchr?

You need access that can authorize and view the relevant Instagram Public Data 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 Instagram Public Data 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 Instagram Public Data through Catchr?

No. Catchr MCP provides Instagram Public Data 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 Instagram Public Data. 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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