Turn your ICP into messaging pillars for every campaign
Converts your ICP into 3-4 messaging pillars — core arguments mapped to specific ICP pains, each with proof, an emotional undertone, and ready translations for email, phone, and LinkedIn. The pillar test kills generic claims any vendor could make, and the usage map tells campaigns which argument leads where.
You are a B2B messaging strategist who bridges the most expensive gap in go-to-market: the one between a well-defined ICP and the actual words in campaigns. You've seen it a hundred times — a company does the hard work of defining exactly who they serve, then writes cold emails and landing pages that could belong to any vendor in the category. Your fix is messaging pillars: 3-4 core arguments derived directly from the ICP's pains and buying triggers, which every email, call opener, and LinkedIn post then draws from. Pillars create consistency without repetition — same argument, many surfaces. Build my messaging pillars. Produce: 1. THE PILLARS: 3-4 core arguments, each with — a name, the ICP pain or trigger it maps to (cite which part of my ICP), the claim stated in one plain sentence, the reason-to-believe (proof, mechanism, or customer evidence), and the emotional undertone (fear of falling behind, relief, control). 2. THE PILLAR TEST: for each, confirm it passes three filters — specific to my ICP (a generic vendor couldn't claim it as written), provable with what I have today, and connected to a pain the ICP would rank top-three. Kill or flag any pillar that fails. 3. SURFACE TRANSLATIONS: each pillar expressed as — a cold email opening line, a one-liner for a call, and a LinkedIn post angle. Same argument, native to each surface. 4. THE ANTI-MESSAGE: for each pillar, what we deliberately do NOT say — the adjacent claim that would blur our position or overpromise. 5. USAGE MAP: which pillar leads for each persona and funnel stage, so campaigns rotate pillars deliberately instead of mushing them into one crowded email. Before you write anything, interview me. Ask me these questions ONE AT A TIME, waiting for my answer each time: 1. Paste or describe your ICP, including pains and buying triggers. 2. What does your product actually do, and what's the strongest proof you have (numbers, case studies, mechanisms)? 3. What do competitors in your space all say? Paste a phrase or two from their sites if you can. 4. What do customers say you do better — in their words, if possible? Once you have my answers, produce the pillars. If one of my proposed strengths is something every competitor also claims, say so and dig for the sharper angle underneath it.
How to use it
- 1
Copy the prompt into Claude, ChatGPT, or any LLM.
- 2
Bring your written ICP and your best proof points — pillars without evidence are slogans.
- 3
Paste real competitor phrasing for question 3; the pillar test needs to know what 'generic in your category' sounds like.
- 4
Adopt the pillars as your campaign spine: each sequence leads with one pillar, not all of them at once.
- 5
Revisit the pillars whenever the ICP is revised — messaging inherits every targeting change.
Best practices
One pillar per email — cramming three arguments into 90 words is how differentiated messaging turns back into mush.
Take the anti-message section seriously; knowing what you don't claim keeps positioning sharp under pressure to overpromise.
Steal the reason-to-believe from customer verbatims where possible — 'their words' beats 'our claim' on every surface.
A/B test pillars against each other across campaigns and let reply data promote the strongest one to your lead argument.
Example: what this looks like in practice
A founder of a staffing-compliance platform has a crisp ICP — healthcare staffing firms of 50-300 employees facing multi-state credentialing rules — but her cold emails read like everyone's: 'streamline compliance and reduce risk'. She runs the interview, pasting two competitor homepages and a customer quote about credential-audit panic. The model returns three pillars: 'Audit-Ready Always' (mapped to the audit trigger, proof: a customer's clean 3-day audit), 'Fifty States, One Screen' (multi-state pain, mechanism-based proof), and 'Credential Lapses Caught Early' (undertone: relief from constant vigilance). A proposed fourth pillar about ease of use fails the generic test and dies. The usage map leads audit-pillar campaigns before survey season. Her next sequence, built on the audit pillar alone, doubles positive replies.
Best fit
This prompt is one gear in a bigger machine. We orchestrate 20+ tools into outbound systems our clients own — and guarantee the results.
Apply for a Pilot Spot → →Frequently asked questions
Messaging pillars are the 3-4 core arguments all your outreach and content draw from — each mapped to a specific pain or trigger in your ICP and backed by proof. Without them, every campaign reinvents its angle from scratch and your market hears a different, blurrier story each time. With them, you get consistency across reps and channels without word-for-word repetition.
More icp, targeting & lead scoring prompts
Define your ICP from your 10 best customers
Reverse-engineers a tight, one-page ICP from your actual closed-won history instead of aspirational guesswork. It forces narrow ranges, separates signal from coincidence, and flags when your customer base actually contains two different ICPs — the insight most founders miss until their outbound numbers tell them the hard way.
Design a lead scoring model with firmographic and behavioral points
Produces a complete, implementable lead scoring model: firmographic fit points, behavioral intent points with decay and negative scoring, threshold bands tied to actions, and a monthly validation loop. It caps complexity at 12 criteria and adapts to what you can actually track, so the model ships instead of dying in a spreadsheet.
Build a negative ICP: who to actively avoid and why
Turns your worst-customer war stories into a formal negative ICP: hard disqualifiers, stacking yellow flags, and the false-positive profile that keeps fooling your team. Includes list-building exclusion filters and a polite decline template, so avoiding bad fits becomes operational instead of a lesson everyone relearns quarterly.