Competitor monitoring that ends in a written strategy, not a dashboard

The challenge

Marketing teams at direct-to-consumer brands know they should watch their competitors. In practice it means someone checking ads, landing pages and social accounts by hand, when they have time. The information is collected unevenly and rarely turned into decisions.

The requirement

• Continuous tracking of a defined set of competitors.
• Analysis that identifies gaps and opportunities, not only a feed of activity.
• A regular report with specific recommendations, written for the brand in question.
• Subscription plans based on how much a brand tracks.

The solution

A brand sets up its category, its competitors and its own positioning once. The platform then gathers competitor marketing activity on a schedule.

Each month, the collected material is passed through an AI pipeline that produces a strategy report: what competitors did, where the gaps are, and which actions the brand should consider, ordered by priority and weighed against the goals the brand has set in the product.

Architecture

The web application is built with Next.js on Supabase, which provides the database and authentication. Data collection and analysis run as Python jobs. The report step uses the OpenAI API with the brand’s stored context, so the output reflects that brand’s market and tone.

The pipeline is split into stages: collect, structure, analyse, write. Each stage can be inspected and improved separately, and a weak report can be traced to the stage that caused it.

Technology

Next.js, Supabase, Python, the OpenAI API and Tailwind CSS.

Outcome

A working SaaS product in which the AI output is a finished document a marketing lead can act on, produced without anyone compiling it by hand.