The funnel: from stranger to customer
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Sales Academy · from no sales experience to landing an AE job, with a UK life-sciences & health-tech specialism. UK English. No prior sales experience assumed; every term is defined at first use.
If you have ever moved people from first contact to a committed decision — recruited for a team, won a sponsor, raised money, driven a project through sign-off — you have run an informal version of this module without the vocabulary.
This module supplies the formal language and — critically — the arithmetic, because interviewers for quota-carrying roles test pipeline maths out loud, and fluency there is the easiest way for a candidate with no sales history to sound like an operator.
What you'll learn
- The end-to-end sales funnel — lead → MQL → SQL → opportunity → closed — and what each conversion point actually means.
- The standard sales stages, what "exit criteria" are, and why stage discipline is the difference between a pipeline and a wish list.
- Pipeline mathematics: coverage ratios, win rates, ACV/ARR/TCV, sales cycle length, and how to work backwards from a quota to required pipeline and required weekly activity — with four fully worked examples, including the funnel numbers one NHS-facing startup published in its adverts.
- Forecasting: commit / best case / pipeline categories, why a VP of Sales lives or dies by forecast accuracy, and the twin sins of sandbagging and happy ears.
- CRM discipline: what Salesforce and HubSpot actually store, why hygiene matters, and how to talk about a deal in a pipeline review without embarrassing yourself.
- The sales velocity formula and its four levers.
1. The funnel: from stranger to customer
The sales funnel (or pipeline funnel) is the standard model of how a stranger becomes a customer. It's drawn as a funnel because volume shrinks at every step: lots of names go in the top, few signed contracts come out of the bottom. Every B2B sales organisation you interview with runs some version of it, and the jargon below is universal.
Lead. Any person or company that might buy — a name and some contact details, nothing more. Sources:
- someone filling in a form on the website
- a trade-show badge scan
- a list of NHS trusts the team wants to target
- a LinkedIn connection
If you have ever staffed a stand at a conference, every badge you scanned became a lead the moment you had the details. A lead is unproven: you don't yet know if they have a need, money, or any interest.
MQL — Marketing Qualified Lead. A lead that marketing's rules say is worth sales' attention. Marketing teams score leads on:
- fit — right industry, right job title, right company size (e.g. "Head of Pathology at an NHS trust" scores high for a diagnostics platform);
- engagement — downloaded a whitepaper, attended a webinar, visited the pricing page.
Cross a scoring threshold and the lead is stamped MQL and passed to sales. The lead→MQL conversion point is automated or rules-based — no human has necessarily spoken to this person yet.
SQL — Sales Qualified Lead. An MQL that a salesperson (often an SDR/BDR — Sales/Business Development Representative, the junior role that does first-touch outreach) has actually spoken to and confirmed is real: there's a genuine problem, the person is relevant, and a proper conversation is worth having. The MQL→SQL conversion point is a human judgement after a first call. (Some companies insert SAL — Sales Accepted Lead — between the two; it just means acceptance and validation are tracked separately.)
Opportunity. The big one. An opportunity (informally a "deal" or "opp") is a CRM record representing a specific potential purchase, with three defining attributes:
- an estimated value (£),
- a stage (section 2),
- an expected close date.
Creating one is a formal act — "I believe this account may buy this product, for roughly this much, by roughly this date" — and from that moment the deal appears in the pipeline number management scrutinises.
The SQL→opportunity conversion point is qualification: a real need, plausible budget, an engaged stakeholder, some intent to act. (Qualification frameworks like BANT and MEDDICC get their own module — for now, qualification is the gate between "interesting conversation" and "deal I'm forecasting".)
Closed-won / closed-lost. The two terminal states. Closed-won: contract signed, revenue counts. Closed-lost: the deal is dead — they chose a competitor, lost budget, or chose to do nothing (the most common competitor in health tech).
Marking a deal closed-lost is healthy, not shameful: it keeps the pipeline honest. The dishonest alternative — endlessly pushing the close date on a dead deal — is a classic hygiene failure (section 6).
Conversion rates are simply the percentages between steps: what fraction of leads become MQLs, MQLs become SQLs, SQLs become opportunities, opportunities close won. These rates power the arithmetic in section 3 — and a rep who knows theirs can self-diagnose ("my demos convert fine; my problem is top of funnel") instead of just "working harder".
Voice from the field"Number of, and pipeline dollar value of, qualified opportunities created per month. This is the most important leading indicator of revenue!"
— Aaron Ross, Predictable Revenue (2011)
Two more funnel terms: inbound (buyers come to you — they filled in the form) versus outbound (you go to them — cold email, calls, LinkedIn). Inbound converts better but you don't control the volume; outbound is harder per lead but scalable on demand. Most AE roles in this market are a mix, and "how much of your pipeline will you self-source?" is a fair interview question.
2. Sales stages in practice — and exit criteria
Once something is an opportunity, it moves through stages — named steps that describe how far the purchase has progressed. Names vary by company, but the standard sequence looks like this. What matters more than the names is the exit criterion for each stage: the verifiable event that must have happened before the deal is allowed to advance.
Voice from the field"Defining the sales methodology enables the sales training formula to be scalable and predictable. The three elements of the sales methodology are the buyer journey, the sales process, and the qualifying matrix."
— Mark Roberge, The Sales Acceleration Formula (2015)
| Stage | What's happening | Exit criterion (what must be true to advance) |
|---|---|---|
| Discovery | Structured conversations to understand the buyer's problem, current process, stakeholders and constraints. Questions, not pitching. | You can articulate their problem, its cost, and who cares about it — and the buyer has agreed a next step. |
| Qualification | Testing whether this is a real, winnable, worthwhile deal: budget, authority, need, timeline. Often blended into discovery rather than a separate stage. | Confirmed need, an identified budget or funding route, access to people who can say yes, and a reason to act now. |
| Demo / evaluation | Proving the product fits: tailored demonstrations, then often a POC (proof of concept — a structured trial against agreed success criteria) or a pilot. | Evaluation completed against success criteria agreed in advance, with the buyer confirming the criteria were met. |
| Proposal | A written offer: scope, pricing, implementation plan, commercial terms. | Proposal delivered to, and acknowledged by, the person with the authority to approve it — not just your day-to-day contact. |
| Negotiation | Working through price, terms, scope adjustments with the decision-maker. | Verbal or written agreement on commercial terms. |
| Procurement / legals | The buyer's purchasing machinery: contract review, security/data-protection review, framework compliance, purchase-order raising. In the NHS this can mean DTAC (Digital Technology Assessment Criteria), DSPT (Data Security and Protection Toolkit) evidence, clinical safety documentation and information-governance sign-off — a real stage with real elapsed time, not a formality. | Signed contract / issued purchase order. |
| Closed-won / closed-lost | Done. | — |
Why stage discipline matters. A stage is a claim about evidence, and every stage carries an assumed probability of closing (e.g. discovery 10–20%, proposal 50%, negotiation 70–90% — each company calibrates its own). Forecasts, coverage calculations and hiring plans are all computed from stage data; if reps grade deals on optimism — "the demo went great, I'll call it Negotiation" — the whole management system is built on sand.
The discipline: a deal sits in the stage its evidence supports, not the stage your excitement suggests. The best exit criteria are buyer-verifiable: not "I sent the proposal" (seller activity) but "the decision-maker has reviewed the proposal and agreed next steps" (buyer behaviour). In an interview, "I'd rather have an honest pipeline than a flattering one" signals maturity many experienced reps lack.
A target-world example. Selling a radiology AI platform to an NHS trust, you might have a wildly enthusiastic consultant radiologist after a demo. Stage discipline asks:
- Has anyone with budget authority engaged?
- Is there a funding route (trust digital budget, regional imaging network, national programme)?
- Has procurement been mapped?
If not, the deal is still in qualification however warm the clinical champion is — NHS deals die precisely in that gap between clinical enthusiasm and financial sign-off.