30 AI Prompts for Sales Teams
Copy-ready prompts that assume you will attach the call notes, the CRM record or the prospect's site — built on sales frameworks (BANT, MEDDIC, SPIN) so you spend time selling, not typing.
Each prompt gives the AI a sales persona, references what you will attach, applies a qualification or messaging framework, and defines the deliverable. These prompts are tool-agnostic and optimised to work across all major AI assistants — Claude, Microsoft Copilot and ChatGPT (and Google Gemini). Replace the [bracketed placeholders] with your own details, and always review AI output before you act on it.
Prospecting and outreach
Problem-First Cold Email
Sending a cold email after researching a specific prospect
prospect and company research notes
- Open with a specific observation about their business
- State the pain point we solve, then add one proof point
- End with a low-friction ask
- Keep it under 90 words with one idea and one CTA only
The email plus a subject line and the single insight it led with.
See example AI output
Subject: Saw Kedai Emas Aiman's 3rd branch opening Hi Amirul, Noticed Kedai Emas Aiman just opened a third outlet in Puchong - fast expansion like that usually means reconciling stock across branches eats up your evenings. We helped Selangor Jewellers Co. cut month-end reconciliation from 3 days to 4 hours. Worth 15 minutes next Tuesday? Best, Farah Insight led with: multi-branch expansion creating reconciliation pain.
Three-Angle Cold Email Variations
Testing which outreach angle resonates before a wider campaign
no file - fill in offer, target role, company type
- Write three cold emails on distinct angles: pain, curiosity, social proof
- Make each angle genuinely different, human, non-templated, under 90 words
- Draft a two-step follow-up cadence for non-responders
Three labelled cold emails plus a two-step follow-up cadence.
See example AI output
Email 1 (Pain): 'Stockouts costing weekend overtime, Encik Farid? We fix that in 6 weeks.' Email 2 (Curiosity): 'What do Klang Valley's fastest-growing manufacturers know about demand that most don't?' Email 3 (Social proof): 'Kluang Steel cut excess inventory 22% in 8 weeks.' Follow-up 1 (Day 4): short nudge with a one-line case study link. Follow-up 2 (Day 9): graceful breakup.
LinkedIn Connection and Follow-Up
Starting social-selling outreach to a new LinkedIn prospect
the prospect's LinkedIn profile and context
- Write a LinkedIn connection request with no pitch in it
- Write a value-first follow-up that gives before it asks
- Keep each message under 300 characters
The two messages plus the reasoning behind the angle.
See example AI output
Connection request: 'Hi Siti, enjoyed your post on flexible-benefits adoption in Klang Valley firms - would love to connect.' (109 characters) Follow-up: 'Thanks for connecting! Saw your team is rolling out hybrid work - here's a short guide our clients used to keep benefits fair, no strings attached.' (198 characters)
30-Second Cold Call Opener
Scripting a cold call before dialing a new prospect
no file - fill in the product and role placeholders
- Write a permission-based intro with a relevant reason for the call
- Ask a question that gets them talking, conversational not a monologue
- Include branches for 'I'm busy' and 'we already use someone'
The 30-second call script with the two objection branches.
See example AI output
Opener: 'Hi Encik Rizal, this is Dev from PayStream - 20 seconds, is that okay? We help Finance Managers cut payroll processing from 3 days to 3 hours. Quick one: how are you currently handling multi-site payroll?' Branch - 'I'm busy': 'Totally understand - can I send a 90-second video instead?' Branch - 'we already use someone': 'Good to hear - mind if I ask what's still manual in it?'
Pre-Call Prospect Account Brief
Researching a company before a first call or meeting
the prospect's website and any notes
- Summarise what the company does and its likely priorities
- List three probable pain points we address
- Name two people to engage plus three tailored talking points
- Base it only on the source material and mark inferences as assumptions
A one-page account brief.
See example AI output
Account: Cergas Retail Sdn Bhd What they do: 40-outlet grocery chain expanding into Johor. Likely priorities: inventory accuracy during expansion, staff scheduling across new sites. People to engage: Ops Director (budget), IT Manager (implementation). Assumption: priorities inferred from expansion news, not confirmed internally.
Discovery and qualification
SPIN Discovery Question Bank
Preparing questions ahead of a discovery call
no file - fill in the role and solution placeholders
- Write 4 situation, 4 problem, 4 implication and 4 need-payoff questions
- Sequence them so each stage logically builds the case
- Use open questions only, never leading
The SPIN question bank grouped by type.
See example AI output
Situation: 'How do you currently back up your servers?' Problem: 'Have you had a restore that failed or took too long?' Implication: 'What would 48 hours of data loss cost the business?' Need-payoff: 'If backups ran themselves, what would that free your team to do?'
MEDDIC Discovery Notes Summary
Turning raw discovery-call notes into a qualification record
raw discovery-call notes
- Structure notes into Metrics, Economic buyer, Decision criteria, Decision process, Identified pain, Champion
- Flag every field with a gap and mark unknowns clearly
- Only use what the notes actually support
A MEDDIC table plus the top three gaps to close next call.
See example AI output
Metrics: wants to cut onboarding time from 6 weeks to 2. Economic buyer: likely CFO Puan Zalina - unconfirmed. Champion: HR Manager Aiman, no budget authority - GAP. Top 3 gaps: confirm economic buyer, map decision process, find a second champion.
BANT Deal Qualification Scorecard
Deciding whether to keep chasing an open opportunity
notes on the opportunity
- Score Budget, Authority, Need and Timeline 1-5 each with evidence
- Give an overall qualify, disqualify or nurture call
- Score on evidence only, no optimism bias
The BANT scorecard and recommendation with reasoning.
See example AI output
Budget: 3/5 - mentioned a range but not confirmed. Authority: 2/5 - contact is an influencer, not the signer. Need: 5/5 - described the pain unprompted, twice. Timeline: 4/5 - tied to a Q1 deadline. Overall: Nurture - get the economic buyer on the next call.
Buying Committee Stakeholder Map
Mapping who influences a complex, multi-stakeholder deal
attached account information
- Map the buying committee roles: economic buyer, champion, blocker
- Note each person's probable motivation
- Suggest the engagement move for each, and mark assumptions with how to confirm them
A stakeholder map table.
See example AI output
Economic buyer (likely): COO Encik Hafiz. Champion: Sales Ops Lead Mei Ling. Blocker (probable): IT Security. Engagement moves: send Hafiz an ROI one-pager, give Mei Ling early demo access, invite IT Security to a technical call before it becomes a blocker.
Discovery Call Recap and Follow-Up
Closing out a discovery call with a written record
a discovery-call transcript
- Extract the top three business problems in the prospect's own words
- Note quantified impact if it was mentioned
- Capture the agreed next step without embellishing
A structured recap plus a follow-up email that reflects it back.
See example AI output
Top 3 problems: 'Our reports take a week to compile', 'We keep losing customers to double-entry errors', 'Nobody trusts the numbers'. Quantified impact: reporting delay estimated at RM15,000/month. Follow-up email: 'Great speaking today - to recap, sending the proposal by Friday as agreed.'
Proposals and quotes
One-Page Outcome-Led Proposal
Turning discovery findings into a proposal draft
the prospect's stated pains, plus a solution description
- Open with their situation and desired outcome, not our features
- Describe our approach, then add proof and the investment
- State the next step, plain language, one clear price
A one-page proposal.
See example AI output
Their situation: manual invoicing across 3 branches causing month-end delays. Desired outcome: close the books in 2 days, not 8. Proof: Ecoworld Distribution cut close time from 9 to 2 days. Investment: RM4,200/month. Next step: 20-minute technical walkthrough Thursday.
Ready-to-Send Quotation Email
Sending pricing once the scope of work is agreed
the scope of work
- Present the deliverables and state pricing with what is and isn't included
- Give the timeline and assumptions to avoid scope disputes
- State the next step to proceed
The ready-to-send quote email.
See example AI output
Deliverables: supply and install of 40 pallet racks, safety certification included. Pricing: RM38,500, includes delivery; excludes forklift rental. Timeline: 10 working days from PO. Reply to confirm and we'll issue the PO for signature.
CFO-Ready Executive Summary Page
Opening a proposal aimed at a finance decision-maker
no file - fill in the company placeholder
- State the problem in their own words
- Quantify the cost of inaction with credible numbers only
- State the result we deliver, no product features, one page
The opening executive-summary page of a proposal.
See example AI output
Puncak Manufacturing loses an estimated RM280,000 a year to unplanned line stoppages. Our predictive-maintenance platform flags failures an average of 11 days before they occur. Clients in similar plants have cut unplanned downtime by 35% within two quarters.
Conservative ROI Business Case
Giving a champion a defensible number to take to finance
no file - fill in the solution placeholder
- State the current cost or lost value
- Project the improvement using a conservative assumption, showing the maths
- Calculate the payback period and write the one-line business case
An ROI one-pager a champion can take to finance.
See example AI output
Current cost: manual data entry consumes 24 staff-hours/week at RM35/hour = RM43,680/year. Expected improvement: automation removes 70% of that time, saving RM30,576/year. Payback period: roughly 8 months. Business case: 'This pays for itself before year-end.'
Post-Proposal Follow-Up Email
Following up after a proposal has gone quiet
no file - fill in the prospect placeholder
- Reinforce the top outcome discussed
- Address the objection you sensed and restate the next step
- Create one gentle, honest reason to decide, no needy language
A single follow-up email.
See example AI output
Hi Puan Aina, Great presenting the proposal on Tuesday - the part that mattered most was cutting your reconciliation time to same-day. I sensed budget timing might be the sticking point, so I've split the rollout into two phases. Happy to walk your finance team through it this week.
Objection handling
Feel-Felt-Found Price Objection Scripts
Responding live to a price objection on a call
no file - describe the price objection raised
- Ask a diagnostic question before responding
- Write three responses using feel-felt-found and value-reframing
- Acknowledge the concern first each time, never discount reflexively
The diagnostic question plus three response scripts.
See example AI output
Diagnostic question: 'When you say the price is too high, is that versus budget, or versus what you're comparing it to?' 1 (Feel-felt-found): 'I get that - other clients felt the same until they saw the hours it saved.' 2 (Value-reframe): 'At RM2/day per user, it's less than your team's coffee budget.'
Competitor Comparison Talking Points
Prospect is actively evaluating us against a named competitor
no file - fill in the competitor placeholder
- Acknowledge the competitor's genuine strength first
- Differentiate on the axes that matter to this prospect, honest claims only
- End with one reframing question, no trash-talk
Talking points plus one reframing question.
See example AI output
Talking points: [Competitor] has a strong native mobile app, we'll acknowledge that upfront. Where we differ: same-day local support, no lock-in contract, direct integration with SQL Accounting. Reframing question: 'Beyond features, how much does response time when something breaks actually matter to your team?'
Quiet-Deal Re-Engagement Message
A deal has gone silent and needs a nudge
no file - fill in the stage placeholder
- Write a short pattern-interrupt opener with a value nugget
- Include an easy yes-or-no ask that surfaces real status
- Provide a fallback message for no reply, no guilt, no 'just checking in'
The re-engagement message plus a fallback message.
See example AI output
Message: 'Hi Encik Dinie - random thought: saw your competitor just launched in Penang. Wondering if that changes the timeline we discussed? No pressure, just let me know yes or no.' Fallback if no reply: a short note two weeks later - 'Totally understand if priorities shifted. Door's open whenever it's useful again.'
Surface the Real Hesitation
Prospect says 'let me think about it'
no file - the prospect's 'let me think about it' response
- Name the likely underlying concern
- Ask a genuine, non-manipulative permission-based question
- Branch the response for a price concern versus a risk concern
A single response with two branches, price versus risk.
See example AI output
Response: 'Totally fair - when people say that, it's usually either the price or whether this actually solves the problem. Which one is closer for you?' Branch - price concern: offer a phased start. Branch - risk concern: offer a pilot with a defined success metric.
Objection-Handling Cheat Sheet
Building a reusable objection reference for the whole team
no file - fill in the product placeholder
- List the five most common objections and the real concern behind each
- Write a one-line reframe for each
- Give the proof point to deploy, keep it field-usable
A cheat-sheet table: Objection, Real concern, Reframe, Proof.
See example AI output
Too expensive | Unclear ROI | 'Cost of inaction is higher' | RM43k/year case study No time to implement | Fear of disruption | 'Live in 2 weeks' | Onboarding timeline Already have a tool | Switching risk | 'We migrate your data free' | Migration checklist
Follow-up and nurture
Three-Touch Follow-Up Sequence
Planning a structured cadence after no response
no file - fill in the stage placeholder
- Touch one adds value, touch two shares proof
- Touch three sends a graceful break-up message
- Keep each under 80 words, one CTA each, no repetition
Three messages with send timing over two weeks.
See example AI output
Touch 1 (Day 1, adds value): 'Sharing this benchmark on industry efficiency.' Touch 2 (Day 6, proof): 'Kedai ABC saw a 30% drop in processing time after 6 weeks.' Touch 3 (Day 13, graceful break-up): 'I'll stop following up here - if timing changes, the door's open.'
Value-First Nurture Check-In
Staying warm with a prospect who isn't ready to buy
no file - fill in the prospect placeholder
- Share something genuinely useful instead of chasing
- Give before you ask, no pitch
The message plus three ideas for what value to attach.
See example AI output
Message: 'Hi Puan Farah, saw HRD Corp just updated the SBL-KHAS claim process - thought it might save your team some admin time, no strings attached.' Three value ideas: (1) a relevant regulatory update, (2) an introduction to a useful contact, (3) a short resource unrelated to our pitch.
Email Thread Recap and Next Move
Picking a stalled deal back up from a long email thread
the full email thread with the prospect
- Summarise where the deal stands and identify the open question
- Reflect their last point back to them
- Draft the single best next message that advances the deal, not stalls it
The recap plus a ready-to-send message.
See example AI output
Deal status: proposal sent 2 weeks ago, prospect confirmed budget but no start date. Open question: does procurement need a second approval? Best next message: 'Hi Encik Amir, following up on where procurement stands - happy to join a short call with them directly if that speeds things up.'
Dormant Lead Reconnect Email
Reviving a lead that has gone cold for months
no file - fill in the months-dormant placeholder
- Acknowledge the time gap honestly
- Give a relevant reason to talk now, something that actually changed
- Make the ask small
A warm reconnect email.
See example AI output
Hi Puan Nurul, It's been about 6 months since we last spoke about streamlining your billing process - no hard feelings if priorities shifted. Reaching out because we just launched multi-currency invoicing, which I remember was your original blocker. Worth a quick 10-minute catch-up?
Post-Meeting Thank-You Email
Sending a same-hour recap after a good meeting
no file - fill in the prospect placeholder
- Recap the agreed value from the meeting
- Confirm the next step with a specific date
- Attach the one thing that keeps momentum
The thank-you and next-steps email.
See example AI output
Hi Encik Faiz, Great meeting today - really glad the automated approval flow resonated. As agreed, I'll send the pilot scope by Friday, and we'll reconvene on the 14th to confirm rollout. Attaching the case study from Sunway Distribution we discussed.
Pipeline and productivity
Weekly Pipeline Priority List
Planning the week's deal-by-deal priorities
current pipeline export
- Rank deals by value, stage and momentum
- Flag the two most at-risk deals and why, be honest about weak deals
- Give the single next action for the top five deals
A prioritised action list.
See example AI output
Deal A (RM120k, Proposal) - highest value, momentum stalling, needs economic buyer confirmed. Deal B (RM45k, Negotiation) - closing signal strong, send contract today. At risk: Deal C gone quiet 9 days post-demo.
Commit and Best-Case Forecast
Building the quarterly forecast for leadership
the attached deal data
- Produce a commit, best-case and pipeline forecast for the quarter
- State the assumptions and name the two deals that most move the number
- Flag the risk to the commit, no sandbagging or happy ears
A forecast summary with the swing deals highlighted.
See example AI output
Commit: RM310,000. Best-case: RM480,000. Pipeline: RM920,000. Swing deals: Kedai Aiman (RM90k, needs legal sign-off) and Puncak Manufacturing (RM65k, awaiting budget approval). Risk: Kedai Aiman's legal review has no confirmed date.
Weekly Manager Update Bullets
Sending a weekly status update to your sales manager
deal notes for the week
- Summarise wins and list at-risk deals with the help needed
- Note the forecast movement
- Be specific about asks, signal not noise
The update as five concise bullets.
See example AI output
- Won: Sunway Distribution, RM75k, closed 2 days early. - At risk: Puncak Manufacturing stalled at legal - need help escalating to their GM. - Ask: need pricing exception approval for Kedai Aiman by Friday.
One-Page Call Prep Brief
Prepping for a call using CRM history
the CRM record and history
- Summarise where things stand and state the goal of this call
- List likely questions and objections
- Define one clear outcome to drive, based only on the record
A one-page prep brief.
See example AI output
Account: Cergas Retail. Where we stand: demo completed, technical questions pending. Goal: get IT's sign-off on data security. Likely objection: migrating 3 years of historical data. Outcome: agreed date for the security review call.
Win-Loss Pattern Analysis
Reviewing closed deals to improve win rate
recent closed deals with notes
- Identify recurring patterns in wins and losses, pattern over anecdote
- Find the stage where losses cluster
- Recommend two actionable process changes to lift win rate
The analysis plus two process changes.
See example AI output
Pattern: deals lost mostly at negotiation stage, usually after a 3+ week gap post-proposal. Wins share a common trait: economic buyer was on the first call. Process change 1: cap the proposal-to-follow-up gap at 5 days. Process change 2: make 'economic buyer identified' a required Proposal-stage field.
More prompt packs by function
Frequently Asked Questions
Each one gives the AI a sales role, tells it what you will attach (call notes, CRM record, the prospect's site), and applies a real framework — SPIN for discovery, MEDDIC and BANT for qualification, feel-felt-found for objections. That produces field-usable output, not a generic email.
Yes — the prompts assume you will paste or attach discovery notes, transcripts, email threads and CRM records. For confidential customer data, use your company's approved enterprise AI so it stays in your control, and anonymise where you can under PDPA.
Copilot shines inside Outlook and Teams for reps in Microsoft 365; Claude and ChatGPT are excellent for research, call summaries and objection handling. Many teams also connect AI to their CRM. These prompts work across all of them.
No — it removes the admin (research, note-taking, drafting) so reps spend more time in the conversations where trust and deals are made. The best reps will be AI-fluent.
Yes. AITraining2U's courses are HRD Corp SBL-KHAS claimable for eligible Malaysian employers.
Never send the first draft. Feed the AI real, specific detail - a news item about the prospect, an exact number from their industry, a phrase they actually used on a call - instead of generic placeholders. Ask it for a first-person, conversational tone and ban stock phrases like 'I hope this finds you well'. Then do one human editing pass to cut anything that sounds like it could apply to any prospect. The AI is fastest at structure and drafting; you are still responsible for the one specific detail that makes it feel personally written.
Yes - just add a line to the prompt specifying the language and register you want. Claude, Copilot and ChatGPT all handle Bahasa Malaysia and Manglish well, though it helps to give a short example of your own past message so the AI matches your natural phrasing rather than textbook Malay. Always read the output aloud before sending - machine-translated tone is the easiest way to sound impersonal.
Track the same metrics you tracked before AI: cold-email reply rate, meetings booked per 100 outreach attempts, proposal-to-close ratio, and average sales-cycle length. Run a two-to-four-week baseline, then compare after adopting these prompts. Time saved is real but is a leading indicator, not proof - the confirming signal is more meetings booked or a shorter cycle, not just faster drafting.
Adoption fails when prompts live in a document nobody reopens. Build a shared, searchable prompt library organised by the moment in the sales cycle, not by tool. Have your best rep share one real before-and-after example in a team meeting - social proof beats a mandate. Ask managers to reference the library during 1:1 deal reviews so it becomes part of the existing workflow rather than an extra step.
You can start today - every prompt here is copy-paste ready, you just fill in the bracketed placeholders and attach your notes or CRM data. Prompt-writing skill matters more for editing the output well: knowing what to cut, what to add back, and when the AI's assumption is wrong. Start by using a prompt exactly as written, compare the result to what you'd have written yourself, then adjust the constraints to match your own voice.
Go beyond prompts — train your team
Prompts are the start. AITraining2U runs hands-on, HRD Corp SBL-KHAS claimable AI training for Malaysian teams — from everyday AI productivity to building agents that run sales workflows end-to-end.