50 ChatGPT Prompts for B2B Sales

What it does

organizes account context, fit, initiatives, triggers, stakeholders, risks and possible entry points into one brief.

Use it when

a named account warrants more than a quick summary.

Give ChatGPT

company, target personas, offer, approved source material, existing relationship and the decision the brief must support.

Expected output

structured account brief with evidence, implications, hypotheses and unknowns.

Improve and review

date the brief and trace material claims to sources. Remove generic industry pain that is not account-specific.

Next

run the Account Research to Personalized Outreach chain.

You are researching a target account for our sales team. 
Conduct a comprehensive account intelligence briefing on this company.

TARGET COMPANY: [COMPANY NAME]
WEBSITE: [URL]
PRIMARY CONTACT I'M TARG …

Open the canonical prompt: Build a Full Account Intelligence Briefing

What it does

briefs ChatGPT’s research capability to investigate a named account and return a documented report.

Use it when

the account is high value and source quality matters.

Give ChatGPT

sales decision, company, personas, time horizon, source hierarchy, exclusions, internal approved files and required evidence labels.

Expected output

research plan, sourced report, stakeholder and initiative evidence, hypotheses, unknowns and next questions.

Improve and review

edit the proposed research plan before it runs. Open sources behind every material conclusion.

Next

follow the full Deep Research for sales process.

Use your deep research capability to build a comprehensive account brief for [COMPANY NAME]. I'm a sales rep at [YOUR COMPANY] selling [SOLUTION].

Research and compile:
1. Company overview: Business …

Open the canonical prompt: Build a Comprehensive Account Brief with Deep Research

What it does

turns a filing or annual report into sales-relevant initiatives, risks, financial signals, language and questions.

Use it when

a public company’s primary documents can ground your account point of view.

Give ChatGPT

the report, filing period, target persona, offer and the sections or questions that matter.

Expected output

quoted or referenced evidence, strategic themes, risks, metrics, sales implications and validation questions.

Improve and review

preserve page/section references and fiscal periods. Do not treat risk-factor boilerplate as a confirmed active initiative.

Next

match approved proof to the evidence with prompt 13.

I've uploaded / pasted a company's annual report. Extract and summarize: (1) their top 3 strategic priorities, (2) key financial metrics and trends, (3) risks they highlighted, (4) technology or opera …

Open the canonical prompt: Annual Report Sales Intelligence Extractor

What it does

summarizes relevant public statements, remit, published material and communication themes.

Use it when

a senior stakeholder’s documented views can make preparation more relevant.

Give ChatGPT

name, title, company, verified profile/source URLs, time range, meeting or outreach objective and privacy boundaries.

Expected output

sourced themes, direct statements, dates, professional context and questions to test.

Improve and review

avoid personality diagnosis, private-life inference and fake familiarity. Verify identity where names are common.

Next

use the evidence to prepare, not to pretend you know the buyer.

Research the online presence of [EXECUTIVE NAME], [TITLE] at [COMPANY], and summarize:
1. Their stated professional focus areas (from LinkedIn About section, recent posts, interviews)
2. Topics they e …

Open the canonical prompt: Research an Executive's Online Presence Before Outreach

What it does

maps known stakeholders by role, influence, stance, evidence and missing coverage in a live opportunity.

Use it when

one contact is not enough to understand how the decision will be made.

Give ChatGPT

known stakeholders, titles, meeting evidence, decision context, product/category and explicit uncertainties.

Expected output

stakeholder table, influence and stance assessment, champion/blocker hypotheses, coverage gaps and next multithreading action.

Improve and review

mark unknown roles as hypotheses. Do not label someone a champion without evidence of access, influence and active support.

Next

see Stakeholder Mapping & Multi-Threading.

You are a B2B sales strategist mapping stakeholders for an active deal.

CONTEXT
- Account: [ACCOUNT]
- Industry: [INDUSTRY]
- Solution type: [PRODUCT OR SOLUTION CATEGORY]
- Current deal stage: [STAG …

Open the canonical prompt: Map Buying Committee Stakeholders for an Active Deal

What it does

organizes current competitor evidence into positioning, differences, risks, proof and questions.

Use it when

a named alternative or incumbent is affecting a live deal or segment.

Give ChatGPT

competitor, segment, use case, current sources, your approved claims, customer proof and known deal context.

Expected output

sourced comparison, likely buyer concerns, landmines, proof, trap questions and unknowns.

Improve and review

verify competitor claims and dates. Avoid invented weaknesses, confidential information and absolute claims.

Next

use Deep Research when the evidence needs a full current investigation.

Provide my sales team with insights into [COMPETITOR] to better position [YOUR PRODUCT/SERVICE]. You are an AI assistant with access to public information.

Research and summarize:
1. [COMPETITOR]'s c …

Open the canonical prompt: Build a Competitive Battlecard Against a Named Competitor

What it does

extracts approved customer evidence and maps it to the buyer and decision moment where it is relevant.

Use it when

sellers have plenty of proof but use it indiscriminately.

Give ChatGPT

case studies, quotes, metrics, product details, approval status, personas and buying stages.

Expected output

persona-stage matrix, source, proof type, permitted wording, relevance and limitations.

Improve and review

retain the original customer and metric context. Do not generalize one result into a universal promise.

Next

use the mapped proof in outreach, discovery, objection and proposal prompts.

You are a B2B sales enablement strategist who specializes in organizing proof points for maximum relevance by audience and buying stage.

CONTEXT:
Company: [COMPANY]
Product: [PRODUCT]
Industry: [INDU …

Open the canonical prompt: Extract and Map Proof Points by Persona and Buying Stage

What it does

converts an account brief and selected commercial angle into a concise first-touch email.

Use it when

research and the reason to contact are already clear.

Give ChatGPT

verified account evidence, buyer role, chosen angle, offer, approved proof, tone, length and CTA constraint.

Expected output

subject options, short email, evidence used and alternate CTA.

Improve and review

delete any unsupported personalization. Ask whether the message makes sense if the first sentence is removed.

Next

use the Cold Outreach Chain for the full sequence.

Using the research and recommended angle pasted below, write a personalized cold email to [PROSPECT NAME] at [COMPANY]. <prior_context> [PASTE: (1) the account research and trigger event/signal, (2) t …

Open the canonical prompt: Write a Personalized Cold Email from Research and Angle

What it does

structures a teach-tailor-take-control opening around a defensible commercial insight.

Use it when

you have credible evidence that can reframe how the buyer views a problem.

Give ChatGPT

buyer, current belief, evidence, cost/risk, your category’s relevance, approved proof and meeting objective.

Expected output

reframe, evidence, tailored implication, transition and question.

Improve and review

a provocative claim without evidence is not an insight. Verify every number and avoid manufacturing urgency.

Next

test the opening in roleplay before using it live.

Build a Challenger Sale commercial insight opening for a discovery call with [JOB TITLE] in [INDUSTRY]. The insight should:

1. TEACH: Lead with a counterintuitive insight about their industry that th …

Open the canonical prompt: Build a Challenger Sale Commercial Insight Opening

What it does

acknowledges a real point from a prospect’s public post and connects it to a relevant business conversation.

Use it when

the post is recent, professionally relevant and genuinely connected to your outreach.

Give ChatGPT

exact post text or URL, date, buyer role, your relevant point of view, proof and CTA.

Expected output

concise acknowledgement, connection, relevance and low-friction next step.

Improve and review

do not overpraise, summarize the post back to its author or imply a relationship that does not exist.

Next

choose another route if the post is unrelated to the business reason for contact.

Write a personalized cold email that references a prospect's recent LinkedIn post and ties it into a relevant offering. Structure it as:
1. Reference their specific post and acknowledge a key point th …

Open the canonical prompt: Write a Cold Email Referencing a Prospect's LinkedIn Post

What it does

opens a call with a relevant observation before introducing the solution.

Use it when

the insight is current, concise and credible for the buyer’s role.

Give ChatGPT

persona, industry, verified observation, source, likely implication, offer and permission-based transition.

Expected output

opener, relevance bridge, permission question and alternate version.

Improve and review

read it aloud. Remove jargon and any statistic you cannot explain under questioning.

Next

prepare likely objections with prompt 27.

Write a cold call opening for a [JOB TITLE] that opens with a surprising industry insight rather than a pitch. Structure:
1. State the insight in one sentence: '[X]% of [BUYER TYPE] are dealing with [ …

Open the canonical prompt: Write a Cold Call Opener with an Industry Insight

What it does

creates a brief voicemail with identity, relevance, value and a clear response path.

Use it when

a voicemail supports a coordinated outreach sequence.

Give ChatGPT

name, company, buyer role, relevant issue, credible benefit, callback detail and companion channel.

Expected output

speakable script under the required time plus a shorter fallback.

Improve and review

time it aloud. Remove complex clauses, inflated value claims and rushed contact details.

Next

align the voicemail with the email and call intent in prompt 19.

Write a professional voicemail script under 30 seconds: your name and company, one industry-relevant benefit, and your callback number said slowly. Needs your name, company, industry, number. …

Open the canonical prompt: Write a 30-Second Industry-Relevant Voicemail Script

What it does

coordinates email, LinkedIn and call touches with a distinct purpose for each step.

Use it when

a single message is unlikely to be enough and the channel cadence is permitted.

Give ChatGPT

persona, account evidence, offer, approved proof, available channels, cadence limits, prior touches and stop conditions.

Expected output

touch plan, channel, timing, purpose, message draft and stop rule.

Improve and review

every touch should add information or make a different ask. Check legal, platform and company outreach rules.

Next

use a canonical automated workflow only after the sequence works manually.

Create a multi-channel follow-up sequence for [PERSON]:

Touch 1: Email (Day 1)
Touch 2: LinkedIn connection (Day 2)
Touch 3: Email bump (Day 4)
Touch 4: LinkedIn message (Day 6)
Touch 5: Phone/voicem …

Open the canonical prompt: Build a Multi-Channel Follow-Up Sequence

What it does

produces one low-pressure sentence that references the last meaningful interaction and offers value.

Use it when

the prospect engaged before but no longer responds.

Give ChatGPT

last interaction, date, open commitment, likely reason for delay, new value and what you want to learn.

Expected output

one concise line and two tone variants.

Improve and review

curiosity is useful; guilt and false urgency are not. Ensure the “new value” is genuinely new.

Next

diagnose the deal with prompt 35 if silence follows active evaluation.

This prospect recently ghosted me after [DESCRIBE LAST INTERACTION]. Draft a single-sentence message I can send via email or LinkedIn to re-engage them. Make the message curious, not needy. It should …

Open the canonical prompt: Single-Sentence Re-Engage a Ghosted Prospect

What it does

closes an outreach loop respectfully and gives the prospect a simple way to correct the assumption.

Use it when

a reasonable sequence has produced no response and the team intends to stop.

Give ChatGPT

prior attempts, relevance, buyer role, archive decision, tone and whether a referral option is appropriate.

Expected output

brief final message, clear close and optional route to re-engage.

Improve and review

avoid manipulative scarcity, passive aggression and an artificial ultimatum.

Next

record the disposition in the CRM and respect the stop decision.

This is the final email before I archive [PROSPECT]'s record. They have not responded to [NUMBER] attempts over [TIMEFRAME]. The email should:
1. Be honest: 'I'm going to stop reaching out after this' …

Open the canonical prompt: Write a Final Breakup Email Before Archiving a Prospect

What it does

combines person, company, opportunity and meeting context into one preparation document.

Use it when

a scheduled meeting warrants structured preparation.

Give ChatGPT

participants, meeting type, account research, stage, prior notes, objective, time and known risks.

Expected output

context, hypotheses, objectives, agenda, questions, objections and next-step target.

Improve and review

separate verified information from inferred priorities. Keep the brief usable in the minutes before the call.

Next

retain the account history in a Project if meetings will continue.

Create a meeting prep brief for my call with [PERSON], [TITLE] at [COMPANY]:

My product: [WHAT YOU SELL]
Meeting purpose: [DISCOVERY / DEMO / NEGOTIATION / etc.]
Time allocated: [MINUTES]

Include: …

Open the canonical prompt: Create a Detailed Meeting Prep Brief

What it does

converts supplied account and buyer context into a company snapshot, persona view, testable pain hypotheses, discovery questions, call flow and risk checklist.

Use it when

the meeting is close and the seller needs a compact brief rather than a broad research report.

Give ChatGPT

company, attendee, role, meeting objective, known context, offer, relevant sources and time available.

Expected output

account snapshot, persona priorities, labeled hypotheses, SPIN-style questions, proposed call flow, likely objections and a final preparation checklist.

Improve and review

open the cited sources, remove unsupported pains and keep every hypothesis visibly testable.

Next

keep the evolving meeting context in a Project.

Good discovery requires preparation. Get a pre-call brief with research, questions, and strategy. Tell me about the prospect. I'll prepare your discovery brief. PROSPECT: ● Name: [NAME] ● Title: [ROLE …

Open the canonical prompt: Prepare a Pre-Discovery Brief for an Upcoming Call

What it does

builds situation, problem, implication and need-payoff questions around a specific buyer role.

Use it when

a seller needs a structured question bank and understands that it is not a script to interrogate the buyer with.

Give ChatGPT

persona, account context, known situation, offer, meeting objective and topics already answered.

Expected output

prioritized questions by SPIN stage with intent and follow-up paths.

Improve and review

remove questions that can be answered by research. Rephrase for natural conversation and buyer relevance.

Next

compare with Discovery Call to MEDDIC-Scored Deal Summary.

Generate discovery questions that uncover real pain, not surface-level answers. Questions grouped by SPIN methodology and customized for your persona. Tell me who you're talking to and what you sell. …

Open the canonical prompt: Generate SPIN Discovery Questions by Persona

What it does

creates an executive-level brief with stated priorities, hypotheses, meeting objective and concise questions.

Use it when

a senior executive meeting requires business context rather than a product tour.

Give ChatGPT

executive, company, public statements, account context, meeting sponsor, objective, time and approved proof.

Expected output

executive context, business hypotheses, three questions, value relevance, risks and close.

Improve and review

remove biography filler. Confirm every quote, title and date; keep the conversation at the level of the executive’s remit.

Next

use Deep Research when evidence is thin or the account is strategic.

I'm meeting with the [FILL IN title, e.g., CEO or CFO] of [FILL IN company name] for the first time. Prepare me with: (1) executive-level insights on their company's strategic priorities, (2) what C-s …

Open the canonical prompt: C-Suite First Meeting Executive Prep Brief

What it does

forces clarity on the meeting’s objective, agenda, desired commitment, likely blockers and fallback outcome.

Use it when

the team has prepared content but has not agreed what the meeting must accomplish.

Give ChatGPT

stage, participants, known needs, unresolved questions, available time, target outcome and constraints.

Expected output

primary and minimum viable outcome, agenda, roles, decision questions and close language.

Improve and review

the desired outcome must be valuable to the buyer as well as the seller.

Next

share internal roles before the meeting and record the result afterward.

You are helping an enterprise seller prepare for a live customer meeting. Task: Create a meeting outcome planner. Inputs: - Account: [COMPANY] - Persona(s): [TITLE / STAKEHOLDERS] - Opportunity stage: …

Open the canonical prompt: Meeting Outcome Planner Enterprise

What it does

predicts plausible objections for the persona and situation, then prepares clarifying questions and grounded responses.

Use it when

evidence or prior interactions suggest likely resistance.

Give ChatGPT

buyer role, account context, solution, stage, known concerns, competitor/status quo and approved proof.

Expected output

ranked objections, why they may arise, clarifying questions, response and proof needed.

Improve and review

do not treat predicted objections as facts. Prepare to diagnose before responding.

Next

practice the most consequential one with prompt 38.

I have a call coming up with [name / position / industry]. Based on common challenges in [industry or persona type], list 3-5 objections I'm likely to hear during a sales conversation about [product o …

Open the canonical prompt: Anticipate Likely Objections Before a Call

What it does

turns discovery evidence into a prioritized show list, skip list, narrative arc and transitions.

Use it when

a demo should prove outcomes instead of touring features.

Give ChatGPT

discovery notes, buyer roles, desired outcomes, current workflow, proof, available time and product constraints.

Expected output

show/skip table, three-act story, role-specific value, questions and close.

Improve and review

verify that every demo segment traces to discovered evidence. Do not overpromise product behavior.

Next

capture buyer reactions and decisions for post-call analysis.

ACCOUNT EXECUTIVE — DEMO STRATEGIST

CONTEXT
- Account: [ACCOUNT]
- Prospect role(s) in the room: [ROLE], [STAKEHOLDER]
- Industry: [INDUSTRY]
- Discovery notes: [PASTE DISCOVERY NOTES OR CALL SUMMARY …

Open the canonical prompt: Plan a Discovery-Led Demo with Show, Skip, and Story Arc

What it does

turns a supplied transcript into a concise meeting summary, participant list, key points and action items.

Use it when

the team needs an accurate working summary soon after a call.

Give ChatGPT

the transcript and, if needed, confirmed participant names or a required summary format.

Expected output

summary, participants, key points and action items requested by the canonical prompt.

Improve and review

check names and actions against the transcript. Do not imply decisions, CRM fields, owners, dates or commitments unless the transcript and requested format support them.

Next

use prompt 30 for the CRM and prompt 32 for the buyer follow-up.

From the provided meeting transcript, summarise the key details in the following format:

1. Meeting Participants: List the names and titles of all participants in the meeting.
2. Action Items: Identi …

Open the canonical prompt: Summarize a Meeting Transcript with Action Items

What it does

converts supplied notes or a transcript into structured CRM-ready fields without claiming to write to the CRM.

Use it when

a seller needs a consistent summary after a call, email exchange or meeting.

Give ChatGPT

interaction type, account/contact, date, raw notes or transcript, CRM field definitions and explicit next steps.

Expected output

concise summary, key points, stakeholders, objections, agreed next steps and follow-up items.

Improve and review

keep missing fields blank or unknown, preserve the buyer’s wording and confirm every owner and date before saving manually or through an approved app.

Next

use the Deal Intelligence Chain when qualification evidence is also required.

Write CRM notes for this interaction.

Interaction details:
- Type: [CALL / EMAIL / MEETING / DEMO]
- Prospect: [NAME, TITLE]
- Date: [WHEN]
- Duration: [HOW LONG]
- What happened: [RAW NOTES OR MEMOR …

Open the canonical prompt: Write CRM Notes for Any Interaction Type

What it does

classifies buyer evidence against MEDDPICC and identifies what remains missing.

Use it when

a discovery or deal call contains information relevant to qualification and strategy.

Give ChatGPT

transcript, MEDDPICC definitions, current stage, prior confirmed evidence and the organization’s scoring standard.

Expected output

evidence by element, direct support, gaps, contradictions, confidence and recommended questions.

Improve and review

missing is not zero and inference is not evidence. Require transcript support for every populated field.

Next

run Deal Intelligence Chain: Transcript → MEDDPICC → Next Action.

Act as my sales intelligence analyst. I just finished a call with [COMPANY]. Here's the transcript: [PASTE TRANSCRIPT]. Produce:
1. Full call summary
2. Stakeholder map with risk flags
3. Key intel ex …

Open the canonical prompt: Extract MEDDPICC Deal Intelligence from a Call Transcript

What it does

turns meeting evidence into a concise customer-facing recap and next-step confirmation.

Use it when

the seller needs to send an accurate summary soon after the meeting.

Give ChatGPT

notes or verified summary, participants, agreed outcomes, commitments, owners, dates, tone and attachments.

Expected output

subject, short recap, agreed next steps and clear confirmation ask.

Improve and review

check every commitment and date. Do not add a new sales claim or next step that was not discussed.

Next

update the CRM only after the external and internal records agree.

Write a follow-up email summarizing my meeting with [PERSON/TEAM]:

Meeting notes:
[PASTE YOUR NOTES]

Include:
1. Thanks (brief)
2. Key points discussed
3. Agreed next steps (with owners and dates)
4 …

Open the canonical prompt: Write a Post-Meeting Follow-Up Email from Notes

What it does

identifies explicit next steps, owners, dates and dependencies, then structures them for joint review.

Use it when

a complex evaluation contains enough mutual commitments to benefit from a shared plan.

Give ChatGPT

transcript, target decision date, known stakeholders, decision milestones, existing commitments and plan format.

Expected output

milestone, owner, date, dependency, evidence, status and open confirmation.

Improve and review

do not assign the buyer work they did not accept. Share the draft for mutual correction.

Next

use prompt 43 when the deal needs a complete mutual action plan.

Review this call transcript or summary and extract clear, actionable next steps. For each action item, assign ownership (sales rep vs. prospect) and a timeline. Format as a structured mutual action pl …

Open the canonical prompt: Extract Next Steps and Ownership into a Mutual Action Plan

What it does

scores each element from supplied evidence, ranks threats and proposes actions to close the most consequential gaps.

Use it when

a live deal needs an evidence-based qualification review before forecast or resource decisions.

Give ChatGPT

CRM notes, call summaries, emails, stage, forecast, stakeholders, target date and scoring definitions.

Expected output

element scores, evidence, gaps, risk rank, next action, owner and confidence.

Improve and review

challenge happy ears. Compare the output with Diagnose MEDDPICC gaps and the manager’s source review.

Next

put repeated deal reviews in a Project, not a general chat.

Analyze this deal against the MEDDPICC framework. Be brutally honest. DEAL: [COMPANY NAME — DEAL NAME] DEAL VALUE: [AMOUNT] CLOSE DATE: [DATE] Everything I know about this deal: [PASTE ALL CRM NOTES, …

Open the canonical prompt: MEDDPICC Deal Analysis: Score, Gaps and Actions

What it does

identifies plausible stall causes and ranks re-engagement, reframing, multithreading or qualification-out actions.

Use it when

an active opportunity has stopped moving and the current next step is weak or absent.

Give ChatGPT

stage, days in stage, timeline, stakeholders, last interaction, commitments, objections, competitor/status quo and attempts already made.

Expected output

stall diagnosis, evidence, ranked recovery paths, exit criteria and 14-day plan.

Improve and review

require alternative explanations and a qualification-out option. Do not create false urgency.

Next

update the opportunity only after the seller validates the diagnosis.

You are a senior enterprise sales coach. A deal of mine has stalled and I need a straight diagnosis and a recovery plan. <deal_notes> [paste deal notes: stage, value, last activity, champion, economic …

Open the canonical prompt: Diagnose a Stalled Deal and Build a Recovery Plan

What it does

analyzes observable language and participation to identify support, neutrality, skepticism or blocking behavior.

Use it when

several stakeholders joined a conversation and the seller needs a careful relationship hypothesis.

Give ChatGPT

transcript, participant names/roles, prior evidence, decision context and definitions for champion, skeptic and blocker.

Expected output

stakeholder, observable evidence, provisional classification, confidence, risk and validation action.

Improve and review

tone is not intent. Keep classifications provisional and avoid inferring private motivations.

Next

update the stakeholder map with evidence and unknowns.

Analyze the following discovery call transcript and assess stakeholder sentiment for each participant. For each person who spoke: 1. Name/title (or best guess) 2. Overall sentiment: Champion / Neutral …

Open the canonical prompt: Call Transcript Stakeholder Sentiment Analysis

What it does

creates a structured internal bank of objections, diagnostic questions, responses, proof and escalation points.

Use it when

a team needs consistent preparation across a product or use case.

Give ChatGPT

observed objections, call evidence, product limits, approved claims, proof, competitors, commercial boundaries and response framework.

Expected output

objection, diagnosis, response, proof, question, do-not-say and escalation.

Improve and review

build from real calls, not stereotypes. Product, legal and enablement owners approve the final playbook.

Next

practice difficult cases with prompt 38.

As a Sales Enablement Lead, create objection handling playbooks for the top concerns about [PRODUCT OR FEATURE]: [OBJECTIONS]. Provide root cause, talk tracks, proof points, and discovery follow-ups. …

Open the canonical prompt: Build Objection-Handling Playbook by Product

What it does

simulates a defined buyer and provides feedback after the practice round.

Use it when

a seller wants to rehearse questioning, listening, response and next-step control.

Give ChatGPT

buyer role, company situation, known priorities, personality boundaries, likely objections, difficulty, success criteria and feedback rubric.

Expected output

in-character exchange followed by scored feedback, missed questions and a retry target.

Improve and review

keep the simulation grounded in the brief and ask it to resist realistically. Separate buyer roleplay from coaching feedback.

Next

repeat the weakest moment rather than rerunning the entire conversation.

I want to practice a [DISCOVERY CALL / DEMO / OBJECTION HANDLING CONVERSATION] with a simulated prospect. Play the role of [JOB TITLE] at [COMPANY TYPE] in [INDUSTRY].

Persona details:
- Name: [FICTI …

Open the canonical prompt: Run a Prospect Roleplay for Discovery or Objection Prep

What it does

ranks possible concessions by cost and defines the give/get required for each.

Use it when

an approved commercial discussion is approaching and the seller needs discipline.

Give ChatGPT

deal value, requested concessions, approved levers, costs, alternatives, target, floor, authority and buyer priorities.

Expected output

ordered ladder, cost, give/get, condition, approval and walk-away boundary.

Improve and review

commercial leadership must validate every option. Never let the model create new pricing authority.

Next

rehearse the order and conditional language before the call.

Before my negotiation with [PROSPECT], help me build a concession ladder — a planned sequence of concessions I'm willing to make, ordered from cheapest to most expensive for us.

For each concession, …

Open the canonical prompt: Build a Concession Ladder for Negotiation Prep

What it does

prepares for procurement tactics, contract redlines, stakeholder routing and escalation.

Use it when

a deal is entering procurement or legal review with approved internal support.

Give ChatGPT

process, stakeholders, timeline, known requests, approved positions, negotiable/non-negotiable terms and escalation owners.

Expected output

issue map, response options, owner, escalation, sequence and timeline risk.

Improve and review

legal and commercial owners approve all substantive language. Treat the output as preparation, not legal advice.

Next

add agreed milestones to the mutual action plan.

Help me navigate procurement/legal review on this deal.
Context:
● Company: [PROSPECT]
● Deal size: [VALUE]
● Their procurement process: [WHAT YOU KNOW]
● Contract redlines: [ISSUES THEY RAISED]
● Tim …

Open the canonical prompt: Build a Procurement Navigation Plan with Redline Responses

What it does

uses the buyer’s language to frame the current state, desired outcome, approach and decision.

Use it when

discovery is complete enough to support a customer-specific proposal opening.

Give ChatGPT

discovery notes, buyer language, stakeholders, agreed outcomes, solution scope, proof, risks and proposal constraints.

Expected output

concise executive summary, customer priorities, proposed outcome, evidence and next decision.

Improve and review

trace claims to discovery. Remove generic company praise and product boilerplate.

Next

use Work for the complete proposal package.

You are a senior consultant specializing in [INDUSTRY] with 15+ years of experience. Write a compelling executive summary for a sales proposal to [CLIENT COMPANY]. The summary should:
- Open with the …

Open the canonical prompt: Write Proposal Executive Summary from Discovery Notes

What it does

structures costs, benefits, assumptions, scenarios, payback and sensitivity for a deal.

Use it when

buyer-validated inputs exist and financial justification is part of the decision.

Give ChatGPT

current costs, volumes, time, adoption assumptions, price, implementation cost, benefit logic, period and buyer-approved rates.

Expected output

transparent model, formula table, scenarios, payback, sensitivity and missing inputs.

Improve and review

recalculate every formula. Keep assumptions editable and never invent customer metrics.

Next

validate the model with the buyer and financial owner.

Create the ROI/business case section for a SaaS proposal.

Deal context:
- Prospect: [COMPANY]
- Annual deal value: [ACV]
- Contract length: [MONTHS/YEARS]
- Implementation cost: [IF ANY]

Value drive …

Open the canonical prompt: Build an ROI and TCO Business Case for SaaS

What it does

creates a joint path from current state to decision and implementation with owners and dependencies.

Use it when

the evaluation has multiple stakeholders, milestones and a meaningful target date.

Give ChatGPT

decision outcome, target date, stakeholders, evaluation steps, technical/legal/procurement needs, dependencies and explicit commitments.

Expected output

milestone plan, mutual owners, dates, dependencies, success criteria, status and open decisions.

Improve and review

co-create it with the buyer. A seller-only close plan is not a mutual action plan.

Next

review the plan at every deal meeting and update the CRM milestones.

Complex deals need shared roadmaps. Get a mutual action plan template to align with your buyer. Tell me about the deal timeline and stakeholders. I'll draft the plan. TARGET CLOSE DATE: [DATE] KEY STA …

Open the canonical prompt: Build a Mutual Action Plan for a Complex Deal

What it does

works backward from the renewal date and notice period to schedule value, risk, stakeholder and commercial work.

Use it when

an AM or CSM needs to avoid late renewal preparation.

Give ChatGPT

renewal/notice dates, contract, stakeholders, adoption and value evidence, risks, account plan, commercial process and internal owners.

Expected output

dated milestones, evidence needed, owners, customer actions, risks and escalation.

Improve and review

verify contractual dates and owners. Keep the plan tied to customer value, not only procurement timing.

Next

see QBR Agenda & Renewal Strategy.

I keep getting caught flat-footed on renewals — starting too late, missing a notice deadline, scrambling at the end. Build me a renewal runbook that works backward from the renewal date so I'm always …

Open the canonical prompt: Build a Backward-Planned Renewal Runbook

What it does

analyzes usage and account context to rank growth hypotheses.

Use it when

approved customer data shows adoption, gaps or adjacent needs worth investigating.

Give ChatGPT

approved usage data, contracted products, business goals, stakeholder feedback, renewal state, product eligibility and known constraints.

Expected output

ranked opportunity, evidence, customer outcome, stakeholder, risk, question and next action.

Improve and review

do not confuse low adoption with upsell readiness. Validate value and fit before pitching expansion.

Next

keep the renewal and expansion context in a customer Project.

Analyze the following customer usage data and identify the top cross-sell or upsell opportunities for [CUSTOMER COMPANY]. For each opportunity:
1. Which product feature or tier are they not using that …

Open the canonical prompt: Identify Cross-Sell and Upsell Opportunities from Customer Data