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Consultative Selling & Closing · Value propositions and objection handling · lesson 9 of 16 · 13 min

Crafting tailored value propositions

What a value proposition is

A value proposition is a clear statement of the outcome you'll help the buyer achieve, why it matters to them, and why you're a credible choice. It isn't a list of services. The best ones use the buyer's own words from discovery.

The formula

For [who] who [problem/goal in their words], we/I [do what] so that [outcome they care about]. Unlike [alternative], we/I [difference], as shown by [proof].

Example for an agency:

"For your bakery chain, which needs to capture festive-season orders across four branches, we'll run a creator and review-management programme so that your weaker branch catches up and online orders rise during the season. Unlike one-off influencer posts, every creator has a tracked code, so you'll see exactly which ones drive orders — as we did for a café group last year."

Example for a creator pitching a brand:

"For [Brand], launching women's running gear in the UAE and KSA, I'll create a three-part series that takes my audience from 'why I switched' to a tracked-code offer, so you can measure sales, not just views. My audience is mostly women aged 22–35 in Dubai and Riyadh who regularly ask me about running kit."

Features, advantages, benefits

Translate everything into benefits:

  • Feature: what it is. "Weekly reporting dashboard."
  • Advantage: what it does. "Shows which creators drive orders."
  • Benefit: what it means for this buyer. "You can justify the budget to your partner and stop wasting money on seeding that doesn't work."

Use the "so what?" test: after each statement, ask "so what?" until you reach something the buyer said they care about.

Quantifying value — carefully

Where possible, help the buyer estimate value in their own numbers. For example:

"You mentioned each new regular customer spends roughly X a month. If the programme brought in even a handful of new regulars per branch, how would that compare with the fee?"

Use their figures, label estimates clearly and avoid guarantees. Promising specific results you can't control ("guaranteed 10x sales") is misleading and may breach consumer-protection or advertising rules.

Proof that persuades

  • Case studies (with client permission), described accurately.
  • Your own verifiable results (analytics screenshots, tracked-code data).
  • Testimonials from real clients.
  • A small pilot or trial, which reduces risk for the buyer.

Presenting options

Offering two or three options often helps buyers decide:

  • Essential: solves the core problem.
  • Recommended: solves the core problem plus the main secondary need.
  • Comprehensive: everything, for buyers with bigger ambitions.

Each should be a genuine choice, clearly explained — not a decoy designed to trick. We'll look at the ethics of options and anchors in more depth in the advanced psychology course.

Worked example: rewriting a weak proposal

Weak: "We offer content creation, community management, influencer marketing and paid ads. Package: 150,000 PKR/month."

Strong: "Goal: fill weekday dinner slots at your Gulberg branch before Ramadan. Problem you described: good food, but few recent reviews and no creator content. Plan: 4 local food creators with tracked codes, weekly review responses, refreshed delivery-app photos. Measure: code redemptions and weekday covers. Option A (essential) … Option B (recommended) …"

Do and don't

Do use the buyer's words and priorities. Do connect every feature to a benefit they care about. Do show proof honestly.

Don't list every service you offer. Don't guarantee results you can't control. Don't invent case studies or numbers.

Hands-on: a one-page business case the buyer can forward

Your champion usually has to sell your idea internally when you're not in the room. Give them a one-page business case written in their numbers:

PROBLEM (in their words): "______"
COST OF THE PROBLEM TODAY (their estimate, labelled): ______ per month
  - e.g., hours lost × loaded hourly cost; missed orders × average margin
PROPOSED CHANGE: ______
EXPECTED IMPACT (range, their assumptions): low ______ / likely ______
INVESTMENT: ______ (one-off) + ______ (monthly)
PAYBACK (illustrative): ______ months at the "likely" estimate
RISKS AND HOW WE REDUCE THEM: pilot / phased rollout / exit terms
DECISION NEEDED BY: ______ because ______ (a real reason)

Keep every number traceable to something the buyer said or provided, and label estimates as estimates. Never present a range you can't defend as a promise.

Value propositions for different buyers in the same deal

B2B decisions involve several people. Tailor the same core proposition:

| Role | What they care about | Example angle | |---|---|---| | Finance director | Cost, risk, payback | "Payback within the year on your own estimates; cancel after the pilot if it doesn't hold." | | Operations manager | Workload, reliability | "Removes the manual reconciliation your team does every Friday." | | IT / security | Integration, data protection | "Integrates with your existing systems; data stays in-region; security documentation ready." | | Owner / CEO | Growth, reputation, control | "Gives you weekly visibility across branches without adding headcount." |

Before and after: a value proposition for a creator pitching a brand

Before: "I'm a lifestyle creator with 45k followers and great engagement. My rates are attached."

After: "For [Brand]'s Ramadan launch in the UAE and KSA: most of my audience are women aged 22–35 in Dubai and Riyadh who ask me about modest activewear every week. I'll run a three-part series ending in a tracked-code offer, so you can measure sales rather than views. Last Ramadan, a similar series drove [verifiable result — screenshot attached]."

Using AI to draft — with your discovery notes

An AI assistant can turn your discovery notes into a first draft using the formula above. Paste your notes (remove personal data you don't need), and instruct it to use only the buyer's stated problems and numbers, to label estimates, and to avoid guarantees. Then rewrite so it sounds like you and check every number against your notes.

Video lecture: Crafting tailored value propositions

Lecture coming soon · 11 chapters · about 8 minutes. Read the full transcript below.

  1. Crafting value propositions
  2. Why it matters
  3. The formula
  4. Features → benefits
  5. Example 1: creator → brand
  6. Quantify honestly
  7. Example 2: Nadia, Karachi (illustrative)
  8. Watch me do it: one proposition, four roles
  9. Proof, options, AI
  10. Common mistakes
  11. Recap + try this now

Lecture transcript

Crafting value propositions

Here's a proposal opening I see all the time. We offer content creation, community management, influencer marketing and paid ads. Package: one hundred and fifty thousand rupees a month. It's accurate. It's also almost useless, because it's about the seller. In this lecture you'll learn what a real value proposition is, a formula to write one, how to translate features into benefits with the so what test, how to quantify value honestly in the buyer's own numbers, and how to tailor one proposition to several people in the same buying group.

Why it matters

Why does this matter? Because buyers don't buy services. They buy outcomes. A value proposition is a clear statement of the outcome you'll help the buyer achieve, why it matters to them, and why you're a credible choice. It isn't a list of what you do. The best ones borrow the buyer's own words from discovery, which is why the SPIN and Jobs to Be Done questions in the last lessons matter so much. If you didn't hear their words, you can't use them.

The formula

Here's the formula. For who, who has this problem or goal in their words, we will do what, so that they get the outcome they care about. Unlike the alternative, we offer this difference, as shown by this proof. It's a skeleton, not a script. Think of it like a good estate agent's description of a house. Not four bedrooms and a boiler. Instead: for a growing family who want a garden and a short school run, this home puts you five minutes from two good schools, unlike the new-builds further out, as the neighbours with three children will tell you.

Features → benefits

Next, features, advantages and benefits. A feature is what it is: a weekly reporting dashboard. An advantage is what it does: it shows which creators drive orders. A benefit is what it means for this buyer: you can justify the budget to your partner and stop wasting money on seeding that doesn't work. The trick is the so what test. After every statement, ask, so what? Keep asking until you reach something the buyer said they care about. Weekly dashboard. So what? Shows which creators drive orders. So what? You can justify the budget to your partner. That's the one to lead with.

Example 1: creator → brand

First example, the simple one. A creator pitches a brand. Before: I'm a lifestyle creator with forty-five thousand followers and great engagement; my rates are attached. After: for the brand's Ramadan launch in the UAE and Saudi Arabia: most of my audience are women aged twenty-two to thirty-five in Dubai and Riyadh who ask me about modest activewear every week. I'll run a three-part series ending in a tracked-code offer, so you can measure sales rather than views. Last Ramadan, a similar series produced this result, with a screenshot attached. It's about their launch, their customer and their measurement problem. The creator's follower count doesn't even appear.

Quantify honestly

Now quantifying value, carefully. Where possible, help the buyer estimate value in their own numbers. You mentioned each new regular customer spends roughly this much a month. If the programme brought in even a handful of new regulars per branch, how would that compare with the fee? Use their figures, label estimates clearly, and never guarantee results you can't control. Promising guaranteed ten times sales is misleading and may breach consumer-protection or advertising rules. A range based on the buyer's assumptions is honest. A promise based on hope is not.

Example 2: Nadia, Karachi (illustrative)

Now a realistic business-to-business scenario, with illustrative numbers. Nadia sells accounts-payable automation to a manufacturing group in Karachi. The finance director told her: my team of four spends about two days a week matching invoices, and late payments have cost us supplier discounts. Nadia builds a one-page business case using only his figures. Problem, in his words. Cost today: his estimate of hours times loaded cost, plus lost discounts, clearly labelled as estimates. Proposed change. Expected impact as a range, low and likely, based on his assumptions. Investment. Illustrative payback. Risks and how a pilot reduces them. And a real reason for the decision date: the new financial year. The finance director forwards it to his managing director unchanged. That's the test of a good business case.

Watch me do it: one proposition, four roles

Watch me do it. I'll tailor one core proposition for four people in the same deal, using the table in the lesson. The finance director cares about cost, risk and payback. So: payback within the year on your own estimates, and you can cancel after the pilot if it doesn't hold. The operations manager cares about workload. So: it removes the manual reconciliation your team does every Friday afternoon. IT cares about integration and data protection. So: it integrates with your existing systems, data stays in-region, and our security documentation is ready now. And the owner cares about growth and control. So: weekly visibility across all branches, without adding headcount. Same product. Same facts. Four different doors into the same room.

Proof, options, AI

A few more tools. Proof that persuades: case studies used with permission and described accurately, your own verifiable results, real testimonials, and a small pilot, which reduces risk more than any slide. Presenting options: two or three genuine choices often help people decide. An essential option that solves the core problem, a recommended one that adds the main secondary need, and a comprehensive one for bigger ambitions. Each must be a real choice, not a decoy designed to trick. And AI can help: paste your discovery notes, with unnecessary personal data removed, and ask for a first draft using the formula, only the buyer's stated problems and numbers, estimates labelled, and no guarantees. Then rewrite it in your voice and check every number.

Common mistakes

Common mistakes. Listing every service you offer. Leading with your company instead of their outcome. Stopping at features and never reaching benefits. Using numbers the buyer never gave you. Guaranteeing results you can't control. Inventing case studies. And writing one proposition for a buying group of five people with five different concerns. How do you measure it? Track whether proposals reach the economic buyer, how often your business case is forwarded internally, and your win rate on proposals that included the buyer's own numbers versus those that didn't.

Recap + try this now

Recap. A value proposition states the outcome, why it matters to this buyer, and why you're credible. Use the formula and the buyer's own words. Push features up to benefits with so what. Quantify with their numbers, as labelled ranges, never guarantees. Tailor the same proposition to each role in the buying group. Your try-this-now action: write a one-page business case for a live opportunity, using only numbers the buyer gave you, and make it good enough to be forwarded unchanged. Next, we'll build an objection-handling library.

Key takeaways

  • A value proposition states the outcome, why it matters and why you're credible.
  • Translate features into advantages and benefits with the 'so what?' test.
  • Quantify value using the buyer's numbers and label estimates.
  • Offer two or three genuine options; never guarantee uncontrollable results.

Try it

Write a value proposition for a real prospect using the formula, then run each feature through the 'so what?' test.