Instagram Business Performance Report
A Claude skill that connects to your Databox workspace via MCP and writes a structured Instagram Business profile performance report from live data.A Claude skill that connects to your Databox workspace via MCP and writes a structured Instagram Business profile performance report from live data. Covers reach, benchmarked engagement, follower growth, content mix by format, Reels and Stories sections, profile actions, audience demographics, and optional GA4 traffic from Instagram. Output: an 11-section HTML report in under 60 seconds.
- ~5 min setup
- Runs on demand
- Claude + Databox MCP
What it does
Most Instagram reviews stop at likes and follower count. This skill connects to your Databox workspace and writes a structured organic performance report from live Instagram Business data in a single run.
Connect your workspace, trigger the skill, and it reads live data from your Instagram Business profile and writes a report covering: an account snapshot with reach, impressions, profile visits, accounts engaged, interactions, new followers, and website clicks, each with a period-over-period delta; a six-month trend view across reach, engagement, and follower growth; engagement rate calculated by followers, with the composition of interactions broken out into likes, comments, saves, shares, and replies; follower growth with a monthly trend and growth rate; a content-mix breakdown showing how each post format is performing; a dedicated Reels section with plays, reach, average watch time, and saves; a dedicated Stories section with reach, replies, and navigation; a profile-actions section covering the taps that show the profile drove real action — website clicks, link taps, and contact taps; audience demographics by age, gender, country, and city; and optional website traffic from Instagram where GA4 is connected, with conversion rate compared to your site average.
The report separates saves and shares from likes, since those are the signals that earn distribution rather than just approval. Reels and Stories each get their own section rather than being folded into a single feed view — the way Instagram actually splits content.
On first run the skill confirms your Instagram data source, asks about your objective, follower size, industry, and reporting window, then saves the configuration permanently. Every subsequent run skips setup and goes straight to the data — output in under 60 seconds, replacing a manual Instagram Insights pull that typically takes 30–45 minutes per cycle.
Who it's for
What's in the package
Security scanned Reviewed by DataboxWhat you need to run this
Claude
Free to download. Required to install and run skills.
Databox account
The skill connects to your data in Databox. The free plan includes all integrations you need to use this skill.
MCP connection
Connector inside your Claude. Takes less than a minute to set up. Full instructions in the setup guide included in the download.
Free to start. Connect your first integration in minutes — no credit card required.
How to use it
Connect any AI tool to your Databox data with Databox MCP.
Databox MCP is the bridge between your live metrics and any AI — Claude, ChatGPT, Cursor, or any client that speaks MCP. One auth, every workspace, no scraping.
No AI hallucinations. Analysis built on a real context layer.
Ask a generic AI to analyse your business performance and it will give you a confident answer. It will also be working from assumptions.
Generic AI doesn't know how your business defines a qualified lead, what your MRR calculation includes, or how you attribute revenue. It fills those gaps with the most plausible interpretation it can find — which is different from the correct one.
The products here run on Databox's data layer — if you choose so. Your metric definitions, your reporting logic, and your live numbers are what the AI reads, pulled straight through Databox MCP instead of uploaded by hand. That's the difference between an output you can share with your team and one you have to verify before you trust it.
Example output
Common questions
Do I need a Databox account to use this skill?
Yes, ideally — and here's why it matters. Point a generic AI at a raw data export and it has to guess what your numbers mean: which conversions count, how you define an engaged session, what a "normal" week looks like. It fills those gaps with the most plausible interpretation it can find, which is often not the correct one. The skill avoids that by reading your data live from Databox through MCP, where your metrics are already standardized — one consistent definition for sessions, engagement, and conversions across your setup. The AI reads what's actually true for your business instead of inferring it, so the report is one you can trust rather than verify. You can technically run it against data you've pasted in by hand, but you lose that context layer and the output is only as reliable as the export. If you don't have an account or data source connected yet, the skill walks you through the setup.
Can I use this with the free Databox plan?
Yes — the free Databox plan includes the integration this skill needs, so you can run it at no cost. The skill itself is also free to download.
Does this use live data from my connected source?
Yes — every run reads your live data directly from Databox through the MCP connection. The report reflects your current data at the moment you run it, not a cached or uploaded snapshot.
Do I need to export data manually?
No — there are no CSV exports and no copy-paste. The skill pulls your data straight from Databox through MCP each time it runs, so the report is always built from your live source.
Can agencies run this for multiple clients?
Yes — run it against each client's data connected in Databox, one account at a time, and you get the same structured weekly brief for every client. It's built to give a consistent report you can take to each client review.
Can I customize the report?
Yes. Before it runs, the skill asks a few onboarding questions — what you want to measure, the time frame, and any context that matters for the analysis — so the report is shaped to your goals from the start. After a run, you can give it feedback to adjust focus, sections, or anomaly thresholds, and reinstall the updated version so your changes carry into future runs.
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