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SMART
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The SaaS Sales Playbook

Know · Say · Show · Do
Terms like PQL or ICP? Glossary →
What to Know. Your foundation — who you sell to, what you're worth to them, and the numbers that matter. Fill these in once as a team, and every rep speaks from the same script. A playbook is only as strong as the clarity underneath it.
01

Ideal customer & personas

Define who you're built for — and who you're not. The sharper the ICP, the shorter the cycle.
See examples
  • Mid-market SaaS, 50–500 staff, already using a CRM
  • Series A–C, has a RevOps or sales-ops hire
  • Recently raised funding or entered a new market
  • Feeling pain from spreadsheets breaking at scale
See examples
  • Economic buyer — VP Sales/Revenue; cares about ROI and forecast
  • Champion — Sales Manager; cares about their team hitting quota
  • Technical buyer — RevOps/IT; cares about integration & data security
  • End user — the rep; cares about less admin, more selling
See examples
  • Pre-revenue or no budget owner identified
  • Wants a fully bespoke build, not a product
  • Single user with no team-expansion path
  • Buying only on lowest price, no value conversation
02

Value propositions

Not features — outcomes. What changes for the customer because you exist?
See examples
  • 'We help SaaS teams turn product usage into pipeline — automatically.'
  • 'Cut your sales admin in half and never miss a renewal.'
  • 'Know which accounts to call today, and why.'
See examples
  • VP Sales: 'A forecast you can trust.'
  • Manager: 'Your team focused on the right deals.'
  • RevOps: 'Clean data flowing into your CRM, no manual work.'
03

The metrics that matter

The SaaS numbers your team should know cold — yours and the prospect's.
What to Say. The words that move a deal forward — discovery that uncovers real pain, a demo narrative that lands value, and templates that keep momentum between conversations.
01

Discovery questions

Great discovery is 80% listening. These open the door; the follow-ups do the work.
See examples
  • 'What's driving you to look at this now?'
  • 'How are you solving this today — and where does it break?'
  • 'What happens if nothing changes in the next 6 months?'
  • 'Who else feels this pain alongside you?'
  • 'What would success look like 90 days after rollout?'
02

Demo talk track

Demo the outcome, not the interface. Tie every click to a pain they named in discovery.
See examples
  • Open: replay the exact pain they named in discovery
  • Show only the one path that solves it — resist the feature tour
  • Tie each click to an outcome: 'so you'd save X hours a week'
  • Close: 'Does this solve the problem you described?'
03

Templates & cadences

The follow-ups that keep deals warm without nagging.
See examples
  • Subject: 'Recap + next step'
  • Recap their pain in their words
  • Name the cost of inaction (time, money, risk)
  • Confirm the agreed next step and date
See examples
  • Subject: 'Following our demo'
  • One line on the outcome they're chasing
  • Attach the one asset that matters (ROI / case study)
  • Propose a specific time to progress
What to Show. Proof beats promises. The assets that turn interest into belief — and give your champion what they need to sell internally for you.
01

Proof library

List what you have, where it lives, and which persona each piece is for.
See examples
  • '[Customer] cut onboarding time 40%' — for the economic buyer
  • '[Customer] doubled expansion revenue' — for the VP
  • Logo wall of similar-sized customers — for credibility
See examples
  • Simple calculator: hours saved × loaded cost
  • Payback period in months
  • Before/after on their key metric
See examples
  • Recorded 3-min product walkthrough
  • 2–3 reference customers willing to take a call
  • G2 / review-site rating and quotes
02

The champion's internal kit

Your champion sells when you're not in the room. Arm them.
See examples
  • One-page business case they can forward
  • ROI summary tailored to their numbers
  • Security & compliance overview for IT
  • A short deck for their internal stakeholders
What to Do. The mechanics that make it repeatable — your pipeline stages, qualification framework, and follow-up rhythm. Consistency here is what turns a good rep into a good team.
01

Pipeline stages

Define each stage by buyer action, not rep optimism. What must be TRUE to advance?
02

Qualification framework

MEDDICC is the SaaS default — fill it to your world, or swap for your own.
03

Follow-up cadence & tools

See examples
  • Day 1: personalised email + connect request
  • Day 3: value-led follow-up (share an asset)
  • Day 5: call + voicemail
  • Day 8: multi-thread to a second stakeholder
  • Day 12: 'breakup' email to prompt a reply
See examples
  • CRM: where the deal & PQL flags live
  • Engagement tool: sequences & alerts
  • Shared drive: where proof assets live
Objection handling. Objections aren't rejection — they're requests for more confidence. Each below has a proven response you can use as-is, plus room to tailor it in your voice. Acknowledge, reframe as a question, and hand control back to the buyer.
Common objections
Enterprise-specific objections
Product Qualified Leads. In a product-led world, your best leads aren't the ones who filled in a form — they're the ones already getting value from your product. This section helps you define what a PQL is, score it, and turn it into fast sales action. A PQL is the right user, showing the right behaviour, at the right time.
01

Your value moment

The single action where a user first gets what you do. This is your activation baseline — the floor every PQL must clear.
See examples
  • First report created
  • First integration connected
  • First team member invited
  • First automation switched on
02

High-intent behaviours

The actions that correlate with buying — the closer to monetisation, the stronger the signal.
See examples
  • Hit a usage limit (seats, storage, exports)
  • Used a key feature repeatedly in a week
  • Invited 3+ teammates
  • Turned on an advanced feature (automation, analytics)
See examples
  • 'Invited ≥3 teammates AND used feature X 5+ times → 3× conversion'
  • 'Hit export limit within 14 days → 2× conversion'
  • '2+ logins/week for 3 weeks → strong renewal signal'
03

Your threshold rules

Turn the signals into a few clear, trackable criteria. Keep it tight — a PQL definition no one can remember is one no one uses.
See examples
  • Activated (finished onboarding)
  • ≥5 sessions in the last 7 days
  • Used a key feature ≥3 times
  • ≥2 users invited
See examples
  • Hit a plan limit, OR
  • ≥5 active users with weekly usage
  • Champion + economic buyer both active
04

Score & prioritise

Not all PQLs are equal. Weight the signals so reps work the hottest first.
05

Segment by customer type

Different buyers signal intent differently. Don't use one threshold for all.
See examples
  • Activated within 48 hours
  • Daily logins in week one
  • Single owner driving fast setup
See examples
  • 3+ departments active
  • Connected to their core systems
  • Procurement or security has engaged
See examples
  • Hit the free-plan ceiling
  • Viral team invites spreading
  • Multiple workspaces created
06

Action & refine

A PQL is only as good as the speed and relevance of the follow-up — then treat the whole model as living.
See examples
  • PQL auto-routed to the owning rep
  • First touch within 24 hours
  • Slack alert fires on threshold hit
See examples
  • 'Noticed your team hit reporting limits — teams at your stage usually unlock X.'
  • 'Saw you connected [integration] — here's how others get the most from it.'
  • 'You've invited 5 teammates — want a quick group walkthrough?'
See examples
  • Track PQL→paid conversion vs MQL
  • Watch deal size: PQL vs non-PQL
  • Cull signals that produce false positives
  • Re-segment thresholds SMB vs enterprise

The PQL formula

PQL = Activated  +  Engaged  +  Showing purchase intent

A PQL firing on an existing account is an expansion signal — capture it as white-space in the SMART Key Account Director planner.

The KPIs that matter. In SaaS, account management lives or dies on retention, growth, and value. Track these, in this order: retention first (protect revenue), growth second (scale accounts), adoption always (it predicts both). Fill in your current number and your target for each.
01

Core revenue

The numbers that decide whether the business compounds or leaks.
KPI Current Target
02

Customer value & health

The leading signals of whether revenue will stay and grow.
03

Relationship & experience

How the customer feels — and how deep you're embedded.
04

Activity & pipeline (leading indicators)

The early actions that predict the lagging revenue numbers.

The simple rule

Retention first (GRR) — protect the revenue you have.
Growth second (NRR, expansion) — scale the accounts worth scaling.
Adoption always (usage) — it quietly predicts both.

Part of the SMART Commercial Suite. These KPIs live at portfolio level here — but they're won or lost account by account. Track them per-account in the SMART Key Account Director planner: NRR and churn show up there as renewal horizons, health scores and white-space. Together: the team's targets, and the individual's book.

Tip · analyse these numbers with AI

Don't just record KPIs — interrogate them. Paste this table into any AI assistant and ask the right question.
Try this prompt
"Here are my account KPIs with current vs target. Which gaps matter most, which are early warnings, and what would you look into first? Give me your reasoning, not just the numbers."

Then apply judgement: AI reads the numbers, not the context in your head. Ask "what does it not know that I do?" — and own the call. The full method is in the free SMART AI guide library, including a worked example, Working With Your Numbers.

Put AI to work on your commercial motion

A capable AI can help you qualify harder, sharpen a discovery call, and read your pipeline honestly — if you brief it well. These prompts use the 4Ds from SMART AI: a clear role, your real context, a constraint, and a request to show its reasoning so you can check it.

Replace the [bracketed] parts and paste into whichever AI you use. Anonymise anything you're not permitted to share.

Qualify a deal honestly
Discernment
Use on the PQL tab when a deal feels good but you want to check you're not talking yourself into it.
You are a disciplined sales qualification coach who has seen every happy-ears mistake. Here's a deal in my pipeline: "[describe the prospect, the need, budget, decision process and what they've actually done, not just said]". Qualify it hard against a framework like MEDDIC. Where am I light on real evidence versus hope? What's the one thing I don't know that could kill this deal? Show your reasoning and give it a realistic, not optimistic, read.
Why this shape: "evidence versus hope" and "realistic, not optimistic" push against the natural bias to believe your own pipeline — the discipline qualification is supposed to enforce.
Sharpen a discovery call
Delegation
Use before a first real conversation, to prepare questions that uncover the actual problem.
Act as a discovery-call expert who believes the best questions uncover pain the buyer hasn't articulated. I'm meeting: "[describe the prospect, their likely situation, and what I think they need]". Give me eight questions that go beneath the surface need to the business problem, cost of inaction, and decision process — ordered so the conversation flows naturally. Avoid anything that sounds like a survey. Flag the two most likely to surface something I'm not expecting.
Why this shape: "beneath the surface need" and "avoid a survey" steer the AI away from generic checklists toward questions that actually open a conversation.
Handle an objection at value
Description
Use on the Objections tab to prepare a response that reframes rather than caves.
You are a commercial negotiator who anchors on value, not price. My prospect said: "[paste the objection in their words]". Context: "[the deal, what they care about, where the real value for them is]". Give me three ways to respond — one that reframes to value, one that isolates the real concern, one that trades rather than discounts. For each, the risk of using it. Don't default to lowering the price.
Why this shape: "don't default to lowering the price" blocks the AI's laziest answer, and giving three distinct tactics with their risks lets you pick what fits the relationship.
Read your pipeline for what's really there
Diligence
Use before a forecast or pipeline review to separate real commit from wishful thinking.
Act as a sceptical sales director reviewing my forecast. Here's my pipeline: "[paste each deal — stage, value, close date, and what's actually happened recently]". Which deals am I probably over-calling, based on activity versus stage? Which look quiet but real? Give me a realistic commit number and the reasoning behind each adjustment. Flag any deal where the close date has already slipped once — I want the honest picture, not the hopeful one.
Why this shape: "activity versus stage" is exactly how experienced leaders spot inflated pipeline, and asking for reasoning per deal lets you challenge it where you know better.
One rule that keeps you safe. AI is a fast thinking partner, but it doesn't sit in your deals and it will sound confident when it's guessing. Treat every answer as a sharp colleague's opinion — useful, worth testing against what you know, never the final word. And never paste customer data you're not permitted to.
Plan with intention. Execute with precision.
Workbook