Research

Competitive Research Digest

A weekly briefing on what your competitors actually shipped

Verified Intermediate AI Agent Mostly automated Paid
Use this workflow
Est. time
~30 min
Est. cost
$1.1
Steps
7
Automation
Mostly automated
Trigger
Schedule

Overview

Competitive monitoring degrades into a folder of unread alerts. This agent checks a defined set of sources weekly, compares against last week's snapshot, and reports only what actually changed — with a link to the evidence for each item.

The filtering is the product: an alert stream nobody reads is worse than no monitoring.

Business value

Replaces scattered manual checking with one briefing that names what changed and why it matters.

Expected outcome

A weekly digest of genuine changes across the tracked set, each with a source link and a materiality note.

Problems it solves

  • Alerts fire on noise and get muted
  • Manual competitor checks slip when everyone is busy
  • Pricing and positioning changes are noticed late
  • No record of how a competitor evolved over time

Who it is for

  • Product marketing teams
  • Founders tracking a competitive set
  • Strategy and corporate development teams

Benefits

  • Reports changes, not activity
  • Every item carries a source link to verify
  • Week-over-week snapshots build a change history
  • One briefing replaces many alert streams

Limitations

  • Only sees public information
  • JavaScript-heavy sites need a rendering fetch to read correctly
  • Cannot judge strategic intent — it reports what changed, not why
  • Materiality assessment needs your context to be useful

Success metrics

  • Material changes surfaced per month
  • False-positive rate in the digest
  • Time from competitor change to internal awareness
  • Digest read rate

Flow diagram

Every step in order, colour-coded by how much of it runs without a human.

Scroll to pan · use the controls to zoom, expand or export.

Steps

7 steps from trigger to result.

1

Weekly trigger

1 min Automated
Scheduled run kicks off against the tracked source list.
InputSchedule
OutputRun job
2

Fetch the tracked sources

6 min Automated
Retrieve each page with rendering, normalise the content and store this week's snapshot.
InputSource list
OutputSnapshots
  • Respect robots.txt and rate limits — aggressive scraping gets your IP blocked and can breach terms of service
3

Diff against last week

4 min Automated
Compare snapshots and discard cosmetic differences — timestamps, rotating testimonials, session tokens.
InputThis week + last week
OutputRaw change set
  • Most of the engineering effort here is discarding noise, not detecting change
4

Assess materiality

Claude Sonnet 8 min Automated
Judge each change against your positioning and drop the immaterial ones.
InputChange set + our positioning
OutputMaterial changes
Prompt
Assess these competitor changes for materiality to us.

Our positioning: {{our_positioning}}
Our target segments: {{segments}}

Changes detected:
{{change_set}}

For each change:
- what changed, in one line
- source URL
- materiality: high|medium|low|noise
- why it matters to us specifically, or why it does not

Be ruthless with "noise". A reworded headline is noise. A new pricing tier is not. If everything this week is noise, say so — an empty digest is a valid and useful result.
5

Write the digest

GPT-4o 6 min Automated
Compose the briefing: headline changes first, then detail, each with its source.
InputMaterial changes
OutputWeekly digest
6

Distribute and archive

Slack 3 min Semi-automated
Post to the team channel and file in the competitive intelligence archive.
InputDigest
OutputDistributed briefing
Expected result: One briefing per week with a permanent, searchable archive.
7

Team review

2 min Manual Human review
The team marks items as actioned or irrelevant, tuning next week's materiality judgement.
InputDigest
OutputFeedback signal

AI tools

Each tool records the role it plays and whether it is required.

Integrations

Services this workflow connects to, and how each authenticates.

Prompt library

Every prompt in the workflow, in chain order. Swap the highlighted placeholders for your own values.

4. Assess materiality · User prompt · Claude Sonnet
Assess these competitor changes for materiality to us.

Our positioning: {{our_positioning}}
Our target segments: {{segments}}

Changes detected:
{{change_set}}

For each change:
- what changed, in one line
- source URL
- materiality: high|medium|low|noise
- why it matters to us specifically, or why it does not

Be ruthless with "noise". A reworded headline is noise. A new pricing tier is not. If everything this week is noise, say so — an empty digest is a valid and useful result.
our_positioning segments change_set

Prerequisites

Have these ready before you start.

LLM API key
For diffing and synthesis.
Web fetching service
One that renders JavaScript — many marketing sites are client-rendered.
Tracked source list
The competitor URLs, changelogs and channels to monitor.
Storage for snapshots
To hold last week's state for comparison.

Use cases

Product marketing intelligence

Track competitor positioning and messaging shifts weekly.

Positioning stays current

Pricing monitoring

Detect pricing and packaging changes the week they happen.

Faster pricing response

Market landscape tracking

Maintain an evidence-backed record of how a market is moving.

Documented market history

Metrics

Author estimates — treat them as a starting point and measure your own runs.

Execution time
~30 min
Estimated AI cost
$1.1
Token usage
35K
Success rate
86%
Automated
82%
Human review
18%

Accepts

Website URLTextAPI

Produces

ReportSummaryEmail

FAQ

Is monitoring competitor websites legal?
Reading public pages generally is, but terms of service and rate limits still apply, and some jurisdictions treat aggressive automated access differently. Respect robots.txt and keep request rates modest.
Was this helpful?
How do we stop the digest becoming noise?
The materiality step exists for exactly this. Give it your real positioning, be strict about the "noise" category, and feed the team's actioned/irrelevant marks back in.
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Can it tell us why a competitor made a change?
No, and any workflow claiming to is guessing. It reports what changed and links the evidence — the interpretation is yours.
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