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Module 5

Precision & Evidence

Trade vague adjectives for concrete numbers and nouns.

By the end you can
  • Replace vague intensifiers with specifics
  • Anchor claims in evidence a skeptic would accept
  • Translate data into a single clear insight

Executives discount vague language automatically. 'Significant', 'soon', 'a lot', 'much better' carry almost no information. Precision builds trust: when you're specific, people believe you've actually looked. The skill is converting impressions into concrete, checkable claims.

Specifics beat intensifiers

'We grew a lot' is weaker than 'We grew 18% quarter over quarter.' 'It'll be ready soon' is weaker than 'It'll be ready Thursday.' Whenever you reach for an intensifier (very, really, significantly), ask whether a number, date, or concrete noun would say more.

Data to insight, not data dump

Don't make the reader interpret your numbers. State the insight, then show the number that supports it. 'Mobile is now our primary channel — 62% of signups came from phones last month' beats listing six metrics and hoping the reader connects them.

What → So what → Now what

An insight still isn't a decision. After the fact (what) and why it matters to this audience (so what), name the action or decision you're asking for (now what). 'Mobile is 62% of signups (what), but our checkout is desktop-first (so what) — I want to fund a mobile checkout rebuild this quarter (now what).' This three-beat chain is what turns analysis into a call to action.

Pass the skeptic test

Imagine your most skeptical stakeholder reading the claim. Would they accept it, or ask 'based on what?' Pre-empt that question by attaching the evidence to the claim itself.

Why it works — the evidence

Concrete, specific language is recalled better than abstractions (the 'concreteness effect'), and pairing a claim with its evidence pre-empts the skeptic. HBR's 'What → So What → Now What' chain turns raw data into a decision: the fact, why it matters to this audience, and the action you want.

Before & after

Before

Customer satisfaction has improved significantly since the redesign.

After

Customer satisfaction rose from 3.4 to 4.2 stars in the eight weeks since the redesign — based on 1,900 reviews.

The vague 'significantly' becomes a number, a baseline, a timeframe, and a sample size a skeptic can trust.
Before

We looked at a bunch of metrics and overall things are trending in a positive direction across the board.

After

The headline: activation is up 12% this month. Retention and revenue held flat; nothing regressed.

A data dump becomes one insight with honest detail about what didn't move.

Practice

Write a response, then get coached. Revise and re-score as many times as you like — iteration is the point.

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