Using Claude for Chrome, research these
competitors: [Rival A url], [Rival B url],
[Rival C url].

For EACH, visit the homepage, pricing &
about pages and extract:
- One-line positioning & target ICP
- Core offer & top 3 features
- Pricing tiers (price, what's included)
- Proof: logos, case studies, reviews
- Tone & key messaging hooks

Output a clean comparison table, one row
per competitor. Cite the URL for each fact.
Flag anything you couldn't verify.

Here is our product: [1-paragraph
description + pricing].

Using the competitor table you just built:
1. Plot a positioning matrix on two axes
   I care about: [axis 1] vs [axis 2].
2. Identify 3 "white space" gaps no rival
   owns (segment, price point, or message).
3. For each gap, rate how defensible it is
   for us (High/Med/Low) and why.
4. Recommend ONE positioning angle we
   should test next quarter.

Build this as an interactive artifact I can
share with the team.

Create a sales battlecard for beating
[Rival A] specifically.

Include:
- Their strengths (be honest) & weaknesses
- 5 common objections a prospect raises
  comparing us to them
- For each: a crisp "when they say X,
  we say Y" rebuttal grounded in fact
- 3 discovery questions that expose where
  we win
- A one-line "trap" question to ask the
  prospect

Keep it to one page, scannable, no fluff.
Tag any claim that needs proof from our team.

Open the Meta Ad Library for our market:
facebook.com/ads/library → search "[keyword]",
Country = Malaysia, Status = Active.

Using Claude for Chrome, for the top
advertiser [competitor] capture each active ad:
- Hook (first line / thumbnail text)
- Format (image / video / carousel)
- Core offer & CTA button
- Landing page it sends to
- How long it's run (start date)

Output one row per ad, tagged by advertiser.
Scroll to capture them all; give me the count.

From the ads you collected, find the patterns:
1. Group ads by ANGLE (pain, proof, price,
   speed, authority, FOMO…).
2. Flag the likely WINNERS — ads running the
   longest or duplicated many times.
3. Which hook styles & offers repeat across
   competitors?
4. What's the common landing-page promise?

Summarise the 5 angles working in our market
right now, ranked, with one example each.

Turn this into action:
1. Build a swipe file of the 10 best ad ideas
   (hook + why it works).
2. Spot the GAP — an angle nobody is running.
3. Draft 3 differentiated ad concepts for us:
   hook, primary text, CTA, visual direction.
4. Give me a test plan: which to run first,
   budget split, and the metric to watch.

Keep our brand voice. Flag any claim we must
substantiate before publishing.

Using Claude for Chrome, audit this page:
[URL]. Target keyword: [keyword].

Check and score (0-5) each of:
- Title tag & meta description
- H1 / heading structure & keyword use
- Content depth vs search intent
- Internal & external linking
- Image alt text & file names
- Schema / structured data present?
- Obvious speed & mobile red flags

Output a table: Issue | Severity | Fix |
Effort. Sort by impact. End with the top 5
fixes to do first and why.

Seed topic: [topic]. Market: [country].
Audience: [who].

Generate a keyword map:
1. 40-60 keyword ideas (head + long-tail).
2. Group into 6-10 clusters by theme.
3. Tag each cluster's dominant intent:
   informational / commercial / transactional.
4. Estimate relative difficulty & priority
   (High/Med/Low) with one-line reasoning.
5. Suggest ONE pillar page + supporting
   posts per high-priority cluster.

Present as a table grouped by cluster.

Compare our site [our URL] to competitor
[competitor URL] for the topic [topic].

1. List content they rank for that we don't
   cover (the gaps).
2. Pick the 3 highest-value gaps for us.
3. For each, write a content brief:
   - Working title & target keyword
   - Search intent & angle
   - Suggested H2/H3 outline
   - 5 "People also ask" FAQs
   - Internal links to add
   - Target word count & meta description

Make it ready to hand to a writer.

We sell [product] to [market]. Here are
our 10 best customers and why we love them:
[paste list / notes].

1. Infer our Ideal Customer Profile:
   firmographics, role, behaviour & intent
   signals that predict a good fit.
2. Design a transparent 0-100 scoring model:
   list each factor, its weight, and how to
   score it. Keep it explainable.
3. Define tier cut-offs (A/B/C) and what
   each tier should trigger.

Show the model as a table I can reuse.

Here is my lead list (CSV attached / pasted
below): [data].

Using the scoring model we built:
1. Score every lead 0-100 and assign a tier.
2. Add a column explaining the top 2 reasons
   for each score.
3. Sort highest to lowest.
4. Flag any lead missing data that would
   change the score if filled in.
5. Give me the headline: how many A / B / C,
   and total A-tier pipeline value.

Output as a clean table I can paste to Sheets.

For my A and B tier leads, recommend a
next-best-action for each.

For every lead give me:
- The action (call / demo / nurture / wait /
  disqualify) and timing
- A one-line reason tied to its score
- A 2-sentence personalised opening message
  referencing their likely pain point

Then build it all as an interactive artifact:
a sortable board with tier, score, action
and the draft message per lead.

Size the market for [product] in [country/
region]. Buyer: [who]. Price point: [price].

1. Use the web to find relevant figures
   (population, businesses, spend) — cite
   each source.
2. Estimate TAM, SAM and SOM both top-down
   AND bottom-up.
3. State every assumption explicitly and
   show the math.
4. Give a realistic 3-year SOM scenario
   (low / base / high).

Flag where the two methods disagree and
which number you'd trust for a board deck.

Here is raw customer feedback (reviews /
survey answers / call notes): [paste data].

1. Cluster it into the main themes.
2. For each theme: % of mentions, intensity
   (mild/strong), and a representative quote.
3. Rank pains by frequency x intensity.
4. Separate "table stakes" from "delighters".
5. Recommend the top 3 things to fix or
   build next, with the evidence behind each.

Be honest about small sample sizes.

Turn the market sizing + voice-of-customer
findings into an interactive dashboard
artifact.

Include:
- KPI strip: TAM/SAM/SOM & top pain
- A bar chart of themes by frequency
- A TAM/SAM/SOM funnel visual
- A filter to switch low/base/high scenario
- A short "so what" insight box

Use a clean, modern style. Brand accent
#D97757 on a cream background. Make it
shareable and self-explanatory.

Cowork brief — run my weekly growth digest.

Every Monday 8am, autonomously:
1. Competitor watch: re-check [Rival A/B/C]
   sites & pricing; flag changes vs last week.
2. SEO drift: audit my top 10 pages; list new
   issues + 1 content brief.
3. Lead scoring: score new leads in [sheet/CRM]
   with our model; surface the A-tier.
4. Market pulse: this week's signals for
   [market], 3 bullets.

Compile a one-page digest with a "do this
first" section. Draft — don't send — a
Slack summary for #growth. Tell me what you
couldn't access.

Cowork brief — full competitor sweep.

For EACH competitor — [Rival A], [Rival B],
[Rival C], [Rival D] — run a separate research
pass and capture:
- Teardown (offer, pricing, ICP, proof)
- Changes in the last 90 days
- Their strongest & weakest message

Then merge everything into:
1. One comparison matrix
2. A battlecard per competitor
3. A single "where our white space is" view

Work through them in parallel and hand me the
finished pack as an artifact. Cite every source.

Cowork brief — entry pack for [segment /
country].

Autonomously produce a go-to-market starter:
1. Market sizing: TAM/SAM/SOM with sources
   & assumptions.
2. Competitor map: who's there + the gaps.
3. ICP + a lead-scoring model for this segment.
4. Keyword + content plan for the first 90 days.
5. A 1-page interactive dashboard tying it
   together.

Save each as a file in this project. Flag the
3 biggest risks and what to validate before
we invest.