Collecting Content Demand with an Audience Radar

Definition

A monitoring process that regularly collects the channels where target customers gather and the activity of competitors, then structures the recurring pains, questions, objections, and phrasings — plus competitors' gaps — and keeps them as input files for content production.

Perspectives

Ronin (2026-08-17, X)

A sources.md file defines 5-10 subreddits, the X accounts the target customers reply to, and the YouTube channels they comment on, and a Claude Code scheduled task pulls fresh posts and comments every night. Either a scraper or an API works for collection.

From the collected material, pain points, repeated questions, objections, and customers' exact phrasing are extracted, grouped by theme, and counted for frequency, and a separate competitor agent tracks 5-10 competitors' posts, performance, offers, and the areas they stay silent on. The results are written into context files like audience-pains.md, hot-questions.md, and competitor-gaps.md, which are read before writing any content.

Ronin has run this system for months and plugs it straight into the Content Engine described in Repurposing Across Platforms with an AI Content Skill Graph — the engine turns one idea into 10 platform-native posts, the radar supplies the ideas, so the human is removed from both ends of the pipeline. Hooks come from real complaints, offers from gaps competitors ignore, and articles answer questions people asked this week; creating from surveillance beats creating from imagination. A newer version extends the radar to all existing sources in the AI/tech space.

Okara (2026-07-17, X)

As an alternative to scrolling for threads yourself, drop your website URL into Okara and let it monitor Reddit 24/7 for keywords related to your product, surface the high-intent conversations, and draft replies you approve before they go out. The reply-writing rules and the rest of the Reddit route are in Getting Your First 100 Users on Reddit.

How to apply

• Fits a builder who already publishes regularly, or is about to with Repurposing Across Platforms with an AI Content Skill Graph, and needs a steady topic supply — the radar is the input end, not the writing end.
• Assumes the target customers talk in public, findable places on Reddit, X and YouTube; if they live in private Slack/Discord groups or enterprise buying committees, sources.md stays thin and the frequency counts mislead.
• Requires an agent that can run on a schedule (Claude Code in the source) plus scraper or API access, and a willingness to handle platform terms and rate limits yourself.
• Not a substitute for validating the idea — recurring pains can feed the problem-frequency signal in B2C App Idea Validation, but the radar starts after you know who the customer is.
• If the goal is replying in threads rather than writing your own content, start from Getting Your First 100 Users on Reddit instead; Okara's monitoring is that route's tooling.

Limits

• This is a description of a single system Ronin says has been running for months; its quality, revenue, and time-saving effects are not independently verified.

• The post's claim of "getting viral news every second" cannot be reproduced, since the collection scope, latency, and "viral" criteria are not stated.

• The source does not cover the scraper/API choice, deduplication, rate limits, failure recovery, or compliance with privacy and platform terms.

• Frequency is not the same as customer importance. Without separating channel bias and a few repeat voices, you can mistake a loud minority for the whole market.

• The Okara description is a single-vendor source that includes promotion of its own product; its monitoring scope, draft quality, and Reddit-policy compliance are not verified.

• Audience Radar original post

• Okara original post