Performance Metrics on a Resume: 40 Examples That Get You Interviews

Open any "good CV" example and look at what makes the bullets pop. It's almost always the same thing: a number. Not because numbers are magic, but because they force you to be specific about what you actually changed.

Most people know they should add metrics. Most people don't know which ones, or how to find them for jobs that aren't obviously numerical. Here's the full playbook, with 40 examples by role.

Why metrics work

A recruiter reading a bullet without a number has to take your word for it. A bullet *with* a number is doing two things at once: it's claiming an outcome, and it's showing that you measured your own work. That second signal is what separates senior candidates from mid-level ones.

Compare:

• *Improved onboarding flow.*
• *Redesigned onboarding flow, cutting day-one drop-off from 41% to 17% across 120k weekly signups.*

Same project. Completely different read.

The four metric families

Almost every business metric falls into one of these:

1. **Money** — revenue, cost, margin, ARR, LTV, CAC, budget owned.
2. **People** — users, customers, employees managed, candidates hired.
3. **Time** — cycle time, time-to-X, time saved.
4. **Quality / Rate** — conversion %, retention %, NPS, defect rate.

If a bullet has none of the four, it's a soft claim. Find one before you submit.

40 examples by role

Sales (5)

• Closed €1.2M in new ARR against a €900k quota (133%) in FY24.
• Built a pipeline of 84 qualified opportunities worth €4.6M in 9 months.
• Reduced average sales cycle from 71 to 49 days by introducing a 15-minute fit call.
• Grew expansion revenue from existing accounts by 38% YoY (€2.1M → €2.9M).
• Mentored 4 new AEs; 3 hit quota within their first full quarter.

Marketing (5)

• Scaled paid acquisition from €40k to €310k monthly spend at a stable 3.2x ROAS.
• Grew organic blog traffic from 18k to 142k monthly sessions in 11 months.
• Cut CAC from €89 to €54 by re-targeting lookalikes off first-party data.
• Launched a lifecycle email programme delivering 14% of total monthly revenue.
• Owned a €1.8M annual budget across paid, content, and lifecycle.

Product management (5)

• Shipped a redesigned checkout that lifted mobile conversion from 2.1% to 3.4%.
• Led the launch of three premium tiers, contributing €4.2M ARR in year one.
• Reduced support tickets per 1,000 users by 28% by fixing top friction points.
• Ran 22 user interviews per quarter, feeding a roadmap that hit 4 of 4 OKRs.
• Owned a 6-person squad delivering 11 production releases per quarter.

Engineering (5)

• Cut p95 API latency from 820ms to 210ms by rewriting the rate-limit layer.
• Migrated 4 services from EC2 to ECS, reducing infra cost by €18k/month.
• Reduced production incident MTTR from 47 to 12 minutes.
• Mentored 3 junior engineers; 2 promoted within 14 months.
• Authored RFCs adopted by 4 teams (~40 engineers total).

Operations (5)

• Redesigned order routing, cutting average fulfilment time from 38h to 21h.
• Renegotiated 3 supplier contracts, saving €420k annually.
• Onboarded 14 new warehouse staff with a training programme that halved ramp time.
• Reduced inventory holding cost by 22% by tightening SKU rationalisation rules.
• Owned weekly S&OP across 6 regions and €30M of annual revenue.

Customer success (5)

• Managed a book of 38 enterprise accounts worth €6.4M ARR; 112% net retention.
• Reduced churn from 3.1% to 1.7% monthly by introducing 30-60-90 success plans.
• Launched a customer health score adopted by 4 CSMs; flagged 9 at-risk accounts before renewal.
• Delivered onboarding for 60+ new customers with a 96% on-time completion rate.
• Drove €780k of expansion revenue through structured QBRs.

People & HR (5)

• Hired 47 roles across engineering, product and design in 12 months; 91% offer-accept rate.
• Cut time-to-hire from 38 to 22 days by redesigning the interview loop.
• Rolled out a performance framework adopted by 130 employees across 4 countries.
• Reduced regrettable attrition from 14% to 8% over 18 months.
• Built a referral programme contributing 31% of senior hires.

Finance (5)

• Closed monthly books in 4 working days, down from 9, after automating reconciliations.
• Owned a €22M annual budget across 5 cost centres; landed within 1.8% of plan.
• Built the three-statement model used in the company's €18M Series B raise.
• Identified €640k of annual SaaS spend savings through vendor consolidation.
• Reduced DSO from 52 to 34 days.

Data / Analytics (5)

• Built the company's first revenue attribution model; informed €3.2M of budget reallocation.
• Migrated 140+ dashboards from Looker to Metabase, cutting tooling cost 70%.
• Authored a self-serve metric layer adopted by 4 teams (~60 weekly users).
• Reduced data freshness from 24h to 90 minutes across all core dashboards.
• Mentored 2 junior analysts; both promoted within a year.

How to find your metrics when you don't have them

If you're staring at a job where "nothing was measured," try these prompts:

• What was the situation **before** you arrived vs after?
• How many people, customers, items, or tickets did you touch per week?
• How much money flowed through the thing you owned, even loosely?
• How much time did something take before you changed it?
• What would your manager have said you were responsible for, in dollars or counts?

Reasonable estimates, clearly framed, are better than no number at all. "~€500k annual spend" is fine. "Owned ~120 weekly tickets" is fine. Don't invent precision you can't back up — but don't hide behind vagueness either.

One rule for every metric

Always pair the number with the baseline or scope. "Increased conversion by 30%" means little. "Increased checkout conversion from 2.1% to 2.7% on 90k weekly sessions" means everything.

That's the whole craft of metric writing.