Tailored Demo Script & Objection-Handling Playbook — Tech Sales (SDR/BDR → AE) Capstone — SkilsMVP

What you'll produce

A tailored demo script plus a 5-objection handling playbook for your live deal — the document a real AE writes before walking into a demo. The script shows only the 3–4 capabilities that map to the pain you uncovered in discovery (Deliverable 3), framed as outcomes the buyer told you they want, not a feature tour. The playbook arms you for the demo and proposal call: the five objections this specific buyer is most likely to raise, each answered with a disciplined Acknowledge → Understand → Respond (with evidence) → Confirm structure, ending in a confident closing ask with honest urgency. This proves the Topic 7 skills — tailoring the demo to discovered pain, selling outcomes over features, handling objections with empathy and evidence, and asking for the business — which are exactly the skills a hiring manager tests in the "give me a demo / sell me this" portion of an AE or senior-SDR loop.

Instructions

Pull your three pains from discovery. Open your Deliverable 3 BANT notes and copy out the 3–4 quantified pains you confirmed (e.g., "first-response time 14 hrs," "~20% of 600 tickets/day are repetitive ≈ 50 agent-hrs/week retyping," "no clean view of the backlog"). Copy the exact numbers from D3 — do not round them up or invent new ones for effect, because every figure in this demo has to trace back to something the buyer actually said. If a pain isn't quantified, you can't sell outcomes against it — go back and put a number on it. These pains, not your product's feature list, are your demo agenda.
Map each pain to exactly one capability. For every pain, name the single product capability that fixes it and the outcome it produces. Write it as Pain → Capability → Outcome (with the prospect's own number). If two capabilities address one pain, pick the one that moves their metric most; if a capability doesn't map to a confirmed pain, it does not go in the demo.
Write the demo as a story, in order of pain severity. Lead with their most expensive pain. For each of the 3–4 segments write: (a) the bridge line that names the discovered pain in their words, (b) the show — what you click/point to, in one or two sentences, and (c) the so-what — the outcome and ROI in their numbers. Add a one-line check-in question after each segment ("Is that the part that's costing your team the most right now?") so it stays interactive, not a monologue.
Open and close the demo deliberately. Write a 2–3 sentence opening recap that plays back their goal and the agenda ("Last time you told me X, Y, Z — I'm only going to show you the three things that fix those") so they know it's tailored. Write a closing ask that proposes a concrete next step (e.g., a 14-day pilot with the support team, a proposal to the economic buyer) with honest urgency tied to their "why now," never fake scarcity.
List the 5 objections THIS buyer will raise. Don't use generic objections — predict the ones tied to this account: their incumbent tool, their budget cycle, their authority/committee, their timing, and their biggest risk. Aim for at least one price objection, one competitor/incumbent objection, one "now's not the time" objection, and one authority/champion objection.
Answer each with Acknowledge → Understand → Respond → Confirm. For every objection write four lines: Acknowledge (validate, don't argue), Understand (the question that surfaces the real concern behind it — remember "too expensive" usually means "I don't see the value yet"), Respond (your evidence: ROI math, a relevant proof point, a reframe, or a clarification), and Confirm (a check that you've resolved it before moving on). Keep responses to what's true about Lumadesk — no invented case studies.
Pressure-test it out loud. Read the demo script and each objection response aloud once. Cut any sentence that's a feature brag with no outcome, any number you can't defend, and any objection answer that argues instead of empathizes. The finished doc should be something you could hand to a new rep and have them run the call.

Worked example

(Account: GearGrid — 220-person DTC outdoor-gear retailer. Buyer/champion: Maya Chen, Head of Customer Support. Economic buyer: Devon Apraku, VP of Operations. Product: Lumadesk AI helpdesk, ~$40/agent/mo. Every pain and number below is lifted straight from the Deliverable 3 discovery notes — nothing new is invented here, because a number you can't trace to the call is a number you can't defend in the room.)

Pain → Capability → Outcome map

Discovered pain (D3's number)	Lumadesk capability	Outcome in their numbers
First response is ~14 hrs (was under 4 pre-growth); Trustpilot dropped to 3.1 with reviews saying "no one ever replied" — and aged-out tickets cost ~$6–8k/mo in goodwill refunds (~$72k–$96k/yr)	Shared inbox + SLA routing — all email/chat/social tickets in one queue, no duplicate replies, auto-prioritized by SLA breach risk	Work toward her stated goal of first response under 4 hrs and Trustpilot back above 4.0; recover the ~$6–8k/mo leaking out as goodwill refunds on tickets that age past the policy window
8 agents burn time on the ~20% of 600 tickets/day (~120/day) that are repetitive — at ~5 min each that's the ~50 agent-hrs/week ≈ ~$65k/yr Maya's notes quantify	AI reply drafting — drafts a tailored reply per ticket from past resolutions; agent edits and sends	Reclaim most of those ~50 hrs/week of retyping = roughly one full agent of capacity, easing the pressure behind the 3 hires she's adding to keep up with doubled volume
Whole team lives in a shared Gmail inbox + a spreadsheet; "by Monday it's chaos — we don't know what's been answered," so Maya staffs and reports to Devon blind	Live SLA dashboard — backlog, response/resolution times, and breach risk by channel in real time	Maya reports to Devon with data, not guesses; justifies the hiring plan against real volume instead of over-hiring into a broken process

(Lumadesk has 20+ features. Only these three are in the demo, because only these three map to a pain Maya confirmed and quantified in Deliverable 3. Everything else — knowledge base, CSAT surveys, integrations gallery — stays off-screen unless she asks.)

Demo script

Opening recap (60 sec): "Maya, last time you told me three things were hurting most: your first-response time is sitting around 14 hours — it was under 4 before volume doubled — and your Trustpilot has dropped to 3.1, with reviews literally saying 'no one ever replied.' Your 8 agents are stuck retyping the roughly 1 in 5 tickets that are repetitive — about 50 hours a week across the team. And you're running everything out of a shared Gmail inbox and a spreadsheet, so you don't have a clean view of the backlog to staff against. I built today around exactly those three — I'm not going to walk you through everything Lumadesk does. Sound right? Anything change since we talked?"

Segment 1 — the 14-hour response time (lead with the most expensive pain).

Bridge: "You said the slow replies are what's showing up in Trustpilot — the 3.1 and the 'no one ever replied' reviews your VP saw — so let's start there."
Show: "This is the shared inbox — email, chat, and your Instagram DMs all land in one queue, no more two agents answering the same email. See these red flags? Lumadesk auto-sorts by which tickets are about to breach your SLA, so your team always works the most at-risk ticket first instead of oldest-first."
So-what: "This is what moves first response back toward the under-4-hours target you told me you're aiming for. And it directly protects the $6–8k a month you said you're eating in goodwill refunds when returns and refund requests age out past the policy window — that's roughly $72–96k a year you're currently leaking."
Check-in: "Is the response-time-and-reviews piece still the one that's costing you the most right now?"

Segment 2 — agents retyping replies (the labor cost).

Bridge: "You told me about 1 in 5 of your 600 daily tickets is the same repetitive question — shipping delays, returns, sizing — and your 8 agents retype those answers from scratch all day."
Show: "Watch this. A 'where's my order' ticket comes in — Lumadesk reads it and drafts a complete, on-brand reply from how your team has answered before. The agent skims it, tweaks one line, sends. Three seconds instead of three minutes."
So-what: "That's the ~120 repetitive tickets a day — about 50 agent-hours a week, the ~$65k a year of retyping your own numbers spelled out. Claw most of that back and you've recovered roughly one full agent of capacity. You told me you're hiring three to handle the doubled volume; this lets those people work the hard tickets instead of the copy-paste ones."
Check-in: "If you got most of those 50 hours a week back, where would you want that time to go?"

Segment 3 — no visibility for staffing (the champion's own pain).

Bridge: "And you said by Monday it's chaos in the shared Gmail inbox — you genuinely don't know what's been answered, so you're staffing and reporting to Devon basically blind."
Show: "This is your live dashboard — backlog, response and resolution times, and breach risk, broken out by channel, updating in real time. No more spreadsheet."
So-what: "So when Devon asks 'do we actually need all three more agents,' you answer with data: here's our 600-a-day volume, here's where we breach, here's what AI drafting already absorbed. You're justifying the hiring plan, not guessing at it."
Check-in: "Is that the view you'd want in front of you on a Monday morning?"

Closing ask (honest urgency): "Maya, you told me the goal is to be live before your Q4 holiday rush, and that Devon — who already saw the Trustpilot reviews — owns the budget and wasn't in the room today. So here's what I'd suggest: let's run a 14-day pilot with your team on these three workflows, measure the real drop in first-response time on your actual tickets, and bring that number to Devon together as the business case. The holiday deadline is exactly why we start now — you want results in hand before peak, not a tool change mid-spike. I can get your team set up this week. Do you want to move forward with the pilot?"

Objection-handling playbook

1. "Lumadesk is too expensive — $40 an agent across the team adds up." (price)

Acknowledge: "Totally fair — at 8 agents now and 3 more coming, that's a real line item, and you should pressure-test it."
Understand: "Can I ask — is it the absolute number, or is it that you're not yet sure the return justifies it? Those need different answers."
Respond: "Let's do the math on your numbers. Even counting all 11 seats once you've hired, that's about $440 a month — roughly $5,300 a year. Against that: the ~50 agent-hours a week of retyping is about $65k a year at your loaded ~$25/hr, and the aged-out refunds are another $6–8k a month leaking out. Recover even a slice of either and the tool pays for itself in the first month — before we count the churn you avoid by fixing response time."
Confirm: "Does framing it against the agent-hours and refund leakage you get back change how the price feels?"

2. "Gmail and a spreadsheet are free, and we've added canned templates — why pay for a tool?" (incumbent / status quo)

Acknowledge: "Makes sense — the shared Gmail inbox is free and familiar, and your team already knows it. 'Free' is a fair thing to weigh this against."
Understand: "Help me understand what the Gmail-plus-spreadsheet setup is and isn't doing for you — is it actually getting your first response under control and stopping the duplicate replies, or is that still the Monday-morning chaos you described?"
Respond: "Here's the honest take: if Gmail and the templates were solving the 14-hour response time, you wouldn't have taken this call — you told me yourself nobody keeps the canned templates updated, and by Monday you don't know what's been answered. 'Free' isn't free when it's costing ~50 agent-hours a week of retyping and $6–8k a month in aged-out refunds. The gap you described — duplicate replies, VIP tickets buried, no SLA prioritization — is exactly where the shared inbox, breach-risk routing, and AI drafting change the math."
Confirm: "If we pilot it and your response time drops on your real tickets versus the Gmail setup, is that the proof you'd need that it's worth paying for?"

3. "This isn't the right time — we're heads-down hiring and onboarding three agents." (timing)

Acknowledge: "I hear you — onboarding three people is a lot, and adding a tool on top of that sounds like more chaos, not less."
Understand: "Can I flip that for a second — what does onboarding three agents into the current setup look like, where everything's manual and there's no clear backlog view?"
Respond: "That's actually the case for doing this now. New agents ramp far faster when AI drafts the reply and they learn by editing, versus the canned Gmail templates you told me nobody keeps updated. And you said you want to be live before the Q4 holiday rush — if we wait, you're hiring into the chaos and then changing tools mid-spike, which is the worst time. Doing it now means your three new agents start trained on the new system."
Confirm: "Would it help if the pilot ran in parallel with onboarding so the new hires learn on Lumadesk from day one?"

4. "I like it, but I can't sign off on this — it's Devon's budget." (authority / committee)

Acknowledge: "Of course — a spend like this should go through Devon, and I'd expect VP of Operations to want a say."
Understand: "When Devon evaluates a tool like this, what does he care about most — the hard ROI, the risk of switching, or how it affects the hiring plan?"
Respond: "Then let's build the case he'll respond to. The pilot gives us a real number — say, response time moving from 14 hours toward the under-4 target on your own tickets, and X of those ~50 weekly agent-hours reclaimed. I'll put together a one-page business case in his language: cost vs. reclaimed capacity vs. the $6–8k a month in refund leakage. You bring the team's experience, I bring the numbers. You'd be walking in with proof, not a pitch."
Confirm: "If I get you that one-pager and the pilot results, would you be comfortable championing it to Devon together?"

5. "How do I know the AI replies will actually sound like us and not embarrass us in front of customers?" (risk / trust)

Acknowledge: "That's exactly the right thing to worry about — a robotic or wrong reply to a customer is worse than a slow one, and your brand voice is part of why people buy from you."
Understand: "What would you need to see to trust it — is it the tone, or the accuracy on tricky tickets like returns and refunds?"
Respond: "Two things. First, the AI never sends on its own — it drafts, your agent reviews and sends, so a human is always the last step. Second, it learns from your past resolutions, so it picks up your voice; in the pilot you'll see it draft on your real tickets and you can grade it before you ever rely on it. You stay in control the whole time."
Confirm: "If you saw it draft accurately on your actual return-and-refund tickets during the pilot, would that put the brand-voice worry to rest?"

Rubric

The app's AI scores the learner's submission against these criteria and gives feedback. Levels: Needs work (1) / Solid (2) / Excellent (3). Passing = every criterion at Solid or above.

Demo is tailored to discovered pain (not a feature tour) — 1: generic walkthrough of many features · 2: shows 3–4 capabilities loosely tied to needs · 3: each segment opens by naming a quantified pain from discovery and shows only the one capability that fixes it, in order of severity.
Sells outcomes with the prospect's own numbers — 1: lists features/benefits in the abstract · 2: states outcomes generally · 3: every segment lands on a concrete result and ROI in the buyer's real numbers (hours, dollars, response time, review rating), each one traceable to a figure actually written in the discovery notes — no rounded-up or invented numbers.
Demo is interactive and well-framed — 1: a monologue, no open/close · 2: has an opening recap and a closing ask · 3: opening plays back their goal + agenda, a check-in question after each segment, and a close proposing a concrete next step with honest urgency.
Five objections are specific to THIS buyer — 1: generic textbook objections · 2: plausible objections for the deal · 3: objections clearly tied to this account's incumbent, budget, committee, timing, and biggest risk — the ones this buyer would actually raise.
Objection responses use Acknowledge → Understand → Respond → Confirm with evidence — 1: argues or jumps straight to rebuttal · 2: follows the structure with reasonable answers · 3: validates first, surfaces the real concern, responds with defensible evidence (ROI math, true proof points), and confirms resolution — never invents facts.
Coherence with prior deliverables — 1: disconnected from the deal · 2: reuses the account/contacts · 3: traces cleanly from the ICP → outreach → discovery/BANT into this demo and close, one continuous deal story.