SignalScore

LinkedIn's native analytics show impressions, reactions and comments. They never show a baseline and never suggest a next step. Operators and founder-creators post into a vacuum. They cannot tell what good looks like for their own account, and every post feels like starting from scratch.

• 01The operator exports per-post analytics from LinkedIn (Post, then View analytics, then Export) and uploads the XLSX files. No LinkedIn login and no API access.
• 02Each post is tagged with a format (carousel, text, video) and an optional topic. Five posts is enough to start, and more sharpens the signal.
• 03SignalScore builds a personal baseline across format, topic and cadence, so every new post is scored against your own history instead of a global average.
• 04The app surfaces what held a post back and returns one falsifiable experiment for the next week: a specific format, hook or hour to test.

• 01Browser-only data pipeline. Analytics files are parsed locally and never leave the device.
• 02Three-screen flow: Import, Analysis, Insights, with zoomable screenshots in the marketing site.
• 03Local persistence so weekly experiments stack into a real learning loop.
• 04Privacy by design. No LinkedIn login, no API connection, delete-all from Settings.

AI Gateway (GPT-4 class LLMs) · Client-side XLSX parsing · React + Vite · shadcn/ui

Sold to solo creators, founder-led brands and B2B marketing teams that own LinkedIn as a channel. It replaces a layer of agency reporting with a self-serve, privacy-safe learning loop the operator runs themselves.

Roughly one high-confidence content experiment shipped per week, instead of zero.

Illustrative assumptions

• 01Most operators run zero structured content experiments because building a personal baseline alone takes a half-day each time.
• 02SignalScore collapses baseline and recommendation into one session.
• 03Assumes the operator posts 2 to 4 times per week and acts on at least the next recommendation.

These are assumptions, not measured outcomes. They are here so the commercial logic is visible in a hiring conversation.