Guide 5.1 — Tools + Stack

Prompt Library

40+ prompts across five marketing functions. Each one includes the use case, the exact prompt structure, and what to expect as output. Copy, adapt, and use.

How to use this library

This B2B marketing prompt library for AI covers 40+ templates across content, demand gen, PMM, research, and RevOps — each with a use case description and example output so you know what to expect before you run it. According to HubSpot’s State of Marketing report, structured prompt templates reduce output revision time by over 50% compared to free-form prompting. See the Workflow Lab for step-by-step workflows that use these prompts in sequence.

Every prompt here is a starting point, not a finished instruction. The bracketed fields are the variables you fill in. The more specific your inputs, the better the output. A prompt that says “Indian SaaS company selling to VP Engineering at Series B companies in North America” will outperform one that says “B2B company” every time.

Prompts are organised by function. Use the category headings to navigate to what you need.

Content Demand gen Product marketing Research Revenue ops

Content

Thought leadership from a voice note

Turn a raw transcript or voice note into a structured LinkedIn article

You are a B2B content editor working with a senior marketing leader at an Indian SaaS company selling to [NA / Europe / APAC] buyers.

Raw transcript: [PASTE TRANSCRIPT]

Write a LinkedIn article that:
- Opens with a specific, counterintuitive observation (not a question)
- Uses first-person voice throughout
- Avoids jargon and buzzwords
- Is written for a [VP Marketing / CTO / Head of Revenue] at a [company size] company
- Ends with one clear practical takeaway
- Target length: 600-800 words

Case study from a customer call

Convert a call transcript into a structured case study sales can use

You are a B2B case study writer. I have a transcript from a customer success call.

Customer: [company name, industry, size, geography]
Product: [what it does in one sentence]
Transcript: [PASTE TRANSCRIPT]

Write a case study structured as:
1. Situation before (2-3 sentences, specific)
2. Why they chose us (from the customer's words)
3. What they implemented (plain language)
4. The result (specific metrics or directional outcome)
5. One direct customer quote (verbatim from transcript only)

Tone: Direct. No superlatives. Written for a sceptical VP of Engineering.

1-to-5 content repurposing

Turn one long-form piece into five derivative assets

From the article below, produce:
1. 3 LinkedIn posts, each covering a different angle, each for a different buyer persona
2. 1 email newsletter section (200 words, one CTA)
3. 5 pull quotes formatted for design use
4. 1 SDR talk track (2 minutes) for when a prospect asks about this topic
5. 1 summary paragraph for a sales follow-up email

For LinkedIn posts: open with a specific observation, not a question. No emojis.

Article: [PASTE ARTICLE]

Technical blog post from engineering input

Turn an engineering explanation into a publishable technical post

I am a B2B marketer writing a technical blog post for [developer / architect / security team] readers.

Engineering input: [PASTE WHAT YOUR ENGINEER EXPLAINED]

Write a technical blog post that:
- Assumes the reader knows [level of technical knowledge]
- Explains the concept accurately without oversimplifying
- Includes one concrete code example or architecture description
- Links the technical detail to a business outcome in the final section
- Avoids marketing language entirely
- Length: 800-1000 words

Flag any section where you are uncertain about technical accuracy.

Demand gen

Market-adjusted outbound sequence

Write a 5-step outbound sequence tuned to a specific market

Write a 5-step outbound email sequence for:

Product: [one sentence]
Target: [job title] at [company type, size] in [NA / UK / DACH / Singapore / ANZ]
Trigger: [funding / hiring signal / intent data / conference]
Differentiator: [what you do differently in one sentence]

For each email: subject line (under 8 words), opening referencing the trigger, one-sentence value prop, CTA, suggested send day.

Tone guide:
- NA: Direct, outcome-focused, peer-to-peer
- UK: Slightly more formal, reference shared context
- DACH: Process and credibility-first, avoid hyperbole
- APAC: Relationship before value, avoid cold directness

Ad copy variants

Generate 5 LinkedIn ad variants from a single campaign brief

Write 5 LinkedIn ad copy variants for:

Product: [description]
Offer: [demo / report / trial / event]
Audience: [job title] at [company type] in [geography]
Primary pain: [the problem they are trying to solve]

For each variant, use a different hook:
1. Cost of inaction
2. Specific before/after transformation
3. Counterintuitive observation
4. Social proof framing
5. Direct question naming the pain

For each: intro text (under 150 chars), headline (under 70 chars), CTA button text (2-4 words).

Landing page for a specific persona

Write conversion-focused landing page copy for one buyer persona

Write a landing page for [VP Engineering / Head of Revenue / Marketing Director]:

Product: [description]
Offer: [what they get]
Key concern for this persona: [their specific objection]
Proof points: [3 relevant data points or outcomes]

Structure:
1. Headline: addresses their specific priority
2. Subhead: what they will walk away with (concrete)
3. Three bullets: each addresses a specific objection
4. Social proof: one customer quote from a similar role
5. CTA: specific and low-commitment

Product marketing

Positioning statement

Build a positioning statement using the April Dunford framework

Build positioning using the April Dunford Obviously Awesome framework.

Product: [what it does]
Best-fit customers: [specific, not broad]
Alternatives they consider: [what buyers use instead]
Differentiated capabilities: [what you do that alternatives cannot]
Proof: [customer outcomes or data]
Buyer priority: [the one thing they optimise for]

Produce:
1. Positioning statement (50-70 words)
2. Three value themes with headline and two supporting points each
3. Five things NOT to say (generic or unverifiable claims)
4. One paragraph explaining why this positioning works for this buyer

Competitive battlecard

Build a usable battlecard from competitor data and customer reviews

I am creating a competitive battlecard.

Our product: [description and key strengths]
Competitor: [name and their core claim]
What they say about themselves: [paste from their website]
Customer reviews (G2 / Capterra): [paste 3-5 reviews, positive and negative]

Produce:
1. Their pitch in one sentence (honest)
2. Three situations where they win
3. Three situations where we win (with proof points)
4. Top 3 objections when prospects compare us
5. Response to each objection (specific, factual)
6. One discovery question that reveals whether we win or they win

Feature launch copy

Write launch assets for a new product feature

I am writing launch copy for a new feature.

Feature: [what it does technically]
Buyer problem it solves: [in the buyer's language]
Who cares most: [job title and why]
Proof: [beta data or early outcomes]

Produce:
1. Email announcement for existing customers (subject + 150-word body)
2. LinkedIn announcement post (200 words, first-person)
3. Sales one-liner (one sentence for any conversation)
4. FAQ: 5 questions a prospect will ask with direct answers
5. Objection response: "We already do this with [alternative]"

Research

ICP definition from deal data

Analyse closed-won deals to build a data-grounded ICP

I am building an ICP from our last 10 closed-won deals.

For each deal: company size, industry, geography, buying trigger, problem solved, alternatives considered, time to close, deal value.

Deals: [PASTE DEAL DATA]

Analyse and produce:
1. Three characteristics most common across all deals (non-obvious patterns, not just industry)
2. The most frequent buying trigger
3. The problem framing that appeared in winning deals
4. Outlier deals and what makes them different
5. A draft ICP statement (100 words) describing conditions under which we win

Account research brief

Build a personalised account brief before outreach

Build an account research brief for [Company Name].

What I know: [industry, size, news]
Website copy: [paste homepage or about page]
Leadership LinkedIn posts: [paste 2-3 if available]
Job postings: [paste relevant descriptions]

Produce:
1. Their likely current priority
2. The most relevant outreach angle
3. One specific opening line reference (not generic)
4. One discovery question relevant to their situation
5. One risk: what might make this a bad fit right now

Quarterly ICP review

Review and update your ICP using closed-won and closed-lost data

I am running a quarterly ICP review.

Current ICP: [PASTE CURRENT ICP]
Closed-won this quarter: [5-10 deals with company, size, geography, trigger, value]
Closed-lost this quarter: [5-10 deals with company, size, geography, loss reason]

Tell me:
1. Are closed-won deals consistent with our ICP, or are we winning somewhere unexpected?
2. What pattern appears in closed-lost that might indicate wrong targeting?
3. Should our ICP change? What specifically?
4. One segment to stop pursuing based on this data

Revenue ops

Pipeline narrative for leadership

Turn CRM data into a 300-word executive pipeline summary

Write a monthly pipeline narrative for CFO and sales leadership.

Data:
- Total pipeline: [value] vs last month [+/- %]
- Stage breakdown: [Awareness / MQL / SQL / Proposal / Won / Lost with counts]
- Top 3 pipeline sources: [source + value]
- Average deal size: [value] vs last month [value]
- Win rate: [%] vs last month [%]
- Closed-lost pattern: [2-3 sentence description]

Write 300 words that:
1. Open with the one number that matters most and why
2. Explain the two most significant changes vs last month
3. Identify one pipeline risk
4. State one action marketing will take
5. Avoid jargon, percentage lists, and bullet points

Attribution explanation for sales

Explain your attribution model in language sales will accept

Write a plain-language attribution model explanation for our sales team.

Our model: [first / last / multi-touch / time decay]
What it tracks: [which touchpoints]
What it does not track: [what is outside the model]
Real example: [paste one deal journey with touchpoints]

Write 200 words that:
- Acknowledge what the model does not capture
- Show what it does capture and why that is useful
- Use the real example to make it concrete
- End with one specific way sales can use the data

Monthly marketing performance narrative

Produce a 2-minute leadership read on marketing performance

Write a monthly marketing performance summary for leadership.

Wins: [top 3 this month]
Misses: [top 2 underperformances]
Key experiment: [what we tested and learned]
Changes next month: [specific adjustments]
Metrics:
- MQLs: [number] vs target [number]
- Pipeline sourced: [value] vs target [value]
- Cost per MQL: [value] vs last month
- Top 2 channels: [names and results]

Format: 3 short paragraphs. No bullet points. No jargon. Written for someone who cares about pipeline and CAC, not impressions.

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