MARKET RESEARCH

Weekly Emerging-Terminology Scan with Brave Search

Every week, runs Brave searches across your category and flags terms that newly appear or spike in frequency, then writes a ranked 'new jargon' digest to Notion.

CategoryMarket Research
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule fires
  • ActionBrave Search sweeps category seed phrasesBraveBrave Search
  • ActionExtract and normalize candidate termsOpenAI
  • LogicDiff against prior-week baseline for net-new terms
  • ActionRank by novelty and momentum, write glossOpenAI
  • OutputPublish ranked digest to NotionNotionNotion

What it does

Runs a recurring sweep of your market category through Brave Search, compares the vocabulary it finds against last week's baseline, and surfaces words and phrases that are brand-new or rising fast. The output is a ranked digest of emerging terminology delivered to Notion so the team sees language shifts before competitors name them.

When to use it

Use it when your category moves fast and naming matters — early-stage markets, AI tooling, dev infra, fintech — and you want a standing signal on the words analysts, buyers, and rivals are starting to use.

How it works

  1. 1A weekly schedule fires the run.
  2. 2Brave Search queries a fixed set of category seed phrases and pulls fresh result titles and snippets.
  3. 3OpenAI extracts candidate terms and normalizes variants (plurals, hyphenation, acronyms).
  4. 4A logic step diffs the extracted terms against the stored prior-week baseline to isolate net-new and spiking terms.
  5. 5OpenAI ranks each by novelty and momentum and drafts a one-line gloss.
  6. 6The ranked digest is written to a Notion database as the new baseline and weekly brief.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect Brave SearchWeb, news, image, video search.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect NotionPages, databases, comments.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    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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