MARKET RESEARCH

Monthly Pain-Point Trend Digest by Email

Once a month, compares this month's mined forum complaints against last month's stored set to surface rising and fading themes.

CategoryMarket Research
Enginesim
Difficultyadvanced
Triggerschedule
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerMonthly schedule
  • ActionScrape trailing month of complaintsApify
  • ActionTally theme volume and intensityOpenAI
  • ActionRead prior month talliesPostgreSQLPostgres
  • LogicCompute deltas and persist current monthPostgreSQLPostgres
  • OutputEmail trend digest to leadershipGmailGmail

What it does

Turns ongoing pain-point mining into a month-over-month trend report. It pulls this month's complaints, scores theme volumes, compares them against the prior month held in storage, and emails a digest that highlights what's surging, what's cooling, and what's brand new — with representative quotes for each mover.

When to use it

Use it for a recurring leadership or investor update where the question isn't just "what are people unhappy about" but "what's changing." It frames market sentiment as a trend line instead of a snapshot.

How it works

  1. 1A monthly schedule triggers the digest.
  2. 2Apify scrapes the trailing month of complaints from your tracked subreddits and forums.
  3. 3OpenAI tallies each theme's volume and intensity for the period.
  4. 4The prior month's tallies are read from a Postgres store for comparison.
  5. 5A logic step computes deltas and classifies each theme as rising, fading, or new, then persists the current month back to Postgres.
  6. 6The formatted trend digest is emailed via Gmail.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect ApifyActors, scrapers, datasets.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect PostgresAny Postgres URL — query, write, migrate.
  4. 4
    Connect GmailRead, draft, send, label.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

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