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Signal collection · used in Consumer Assessment

Define what you're studying. Get scraper-ready URLs.

Frame a research brief, discover the subreddits where the conversation lives, and emit paste-ready inputs for Apify's Reddit scraper. The friction this removes is the part that costs the most time and produces the most bad samples — the part where a strategist guesses at subreddits and reaches for top-of-year by default.

Step 01 / Frame the brief

What are you actually studying?

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Strategic frame plus priors-to-test. The hypotheses are deliberately framed as things to disconfirm, not confirm — the synthesis will be richer if the brief expects to be wrong about half of them.

The narrowest framing of what you're studying. Be specific.
One or two sentences. Will be used by the LLM helpers to ground their suggestions.
For category research, "past year" is usually right. Use "past month" for trend work, "all time" for evergreen / canonical posts.
Category terms, competitor names, varieties, synonyms. Strengthens query targeting.
Disambiguators. Critical for ambiguous category names.
Step 02 / Discover subreddits

Where does this conversation actually live?

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The highest-leverage decision in the brief. Strategist-quality subreddit selection determines corpus quality more than any other lever. Mark each one as Primary, Secondary, or Drop. Aim for 4–6 Primary subreddits.

Strategist-known subreddits go here. The LLM doesn't always surface niche communities.
Step 03 / Review & emit

Paste-ready inputs for Apify.

Pending

One Apify run per primary subreddit. Running them as separate calls avoids the global maxItems cap behavior that silently truncates multi-subreddit batches.

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