It's scattered
TV, radio, streaming, podcasts, social and the website each report in a separate portal and format.
AI analytics firm for broadcasters
Infalytics takes your audience data from streaming, social, web and podcasts, and sends back the reports, charts and findings. Nobody on your team builds a dashboard.
Working with Mississippi Public Broadcasting through the Mississippi ITS AI Innovation Hub.
Livestream hours rose for the third straight week, led by the 6 to 9 a.m. block. Worth pitching to the morning sponsor.
Illustrative data. Every real report names its source and date range.
The problem
TV, radio, streaming, podcasts, social and the website each report in a separate portal and format.
Someone exports spreadsheets and rebuilds the same report every month. Leadership sees last quarter, not this week.
Most stations can't fund a data team, and chatbot tools want your audience data sent to someone else's model.
How it works
16 connectors, including Meta, YouTube, Google Analytics and HubSpot, plus file uploads for everything else.
Quality checks on every source, with each fix shown to you before it's applied.
63 tested analysis tools. The AI picks which to run; audited code does the math.
Dashboards, charts and a written summary of what changed and what to do about it.
Why stations trust it
Every calculation goes through tested code with limits on rows, output and run time. Ask twice and you get the same answer, which is what you need before it goes in front of a sponsor or a board.
By default the AI model only sees column names, never your values.
What the model sees. Stations that want more control can run a local model instead.
Each with limits on rows, output and run time.
Plus file uploads for anything without one.
Built around the numbers stations actually report.
Use cases
Leadership and development teams rebuild the same quarterly audience report by hand. Infalytics fills a board update or a CPB-style grant report from live data and sends it as a PDF on a schedule.
With federal funding gone, foundations and legislatures want evidence. One cross-channel view of reach, with the working behind every number, holds up when a funder asks how it was counted.
See activations, members in their grace period and renewals coming due, in aggregate and next to streaming use, so retention starts before a membership lapses. No member’s personal details are copied.
Ask which shows are growing and get a chart. Expected-range bands separate a real change from a normal week, and each show is scored against your own history, not a national average.
Run every call sign from one workspace. Station managers see only their own station; network leadership sees all of them, in dashboards, exports and scheduled reports alike.
A group with thirty stations gets one view across them. When a market’s streaming or digital audience drops, an alert opens an incident for someone to own, days after it starts instead of at quarter end.
Ad sales needs fresh audience proof for every pitch. A monthly PDF per market, with the methods written in, replaces an analyst pulling ratings and streaming exports by hand.
Compare a morning show’s broadcast audience with its YouTube clips, podcast downloads and social reach. Platform fields map to one shared set of metrics, previewed before anything is applied.
Acast, Simplecast, Spotify, Apple, Triton and StreamGuys each report differently and on their own delay. Infalytics puts them on one scale and shows how fresh each source’s numbers are.
A full-screen board for the newsroom wall ranks top episodes and segments from each connected source as it syncs, and says plainly how old each number is.
A digital manager asks a question in plain English and gets a computed answer instead of learning a BI tool. Questions you rely on are saved as verified, so they return the same number every time.
If your organisation blocks chatbot tools, this still fits. The AI sees column names, never your rows; you can run a local model; and the whole platform can run inside your own cloud account.
Duplicate rows and three spellings of one show name skew every report. Cleaning finds them, previews each fix before and after, and reapplies your saved fixes to every new upload.
When a connection stops syncing, a staleness alert fires before anyone presents last week’s numbers as this week’s. Each connection shows its health and run history.
Also a fit for
* New connectors, built and in testing. Each is checked against a station’s own account before it goes live there.
Your options today
| Option | Who does the work | Where the data goes | Same answer twice? |
|---|---|---|---|
| Power BI, Tableau | Your staff | Stays in-house | Yes |
| Agencies, consultants | Them, slowly | Shared with the agency | Yes |
| ChatGPT-style tools | Your staff, prompting | The model provider | Not reliably |
| We do | Stays put by default | Yes |
Working with a statewide broadcaster
Since the summer of 2026, Infalytics has been working with MPB staff through the Mississippi ITS AI Innovation Hub. Their audience data sat across five or six systems with nobody holding a single view. Infalytics built that view, including a podcast dashboard nobody on staff had to make, and we're in talks to take it into production.
A 20-minute walkthrough of a real station report, and what Infalytics would build from your sources.