5.2Sales KPIs & forecasting
The essentials in 30 seconds
- 6 KPIs, activity + efficiency: calls/meetings, conversion, basket, cycle, pipeline coverage, win rate.
- Forecast on the weighted pipeline: amount x probability per stage, 3x the goal, weekly review.
- Diagnose by rates: each weak rate points at the worksite (L1, L2-L3, L4).
Threaded mini-case — Younes finds out his pipeline lies
Younes targets €100k this quarter with a €180k pipeline and a 15% conversion rate instead of 30%. He almost celebrates his goal — until he does the maths: €180k at 15% is only €27k likely. He adds prospecting and coaches his closing (L2 discovery, L3 closing). Sequel of case 5.1 — Younes now steers by the numbers, not by gut feeling.
Sequel of case 5.1 — Younes moves from a filled CRM to steering by rates.
1. 6 KPIs that steer: activity + efficiency
Calls/meetings (activity), conversion rate (efficiency), average basket (value), cycle (days: speed), pipeline (coverage: 3x goal), win rate (won/proposals). Activity without efficiency = agitation; efficiency without activity = under-revving.
2. Forecast: the weighted pipeline
Amount × stage probability (10/30/60/90 %) summed = forecast. Rule: pipeline at 3x goal (with 30 % average conversion). Forecast reviewed weekly (entries, exits, slips): a pipeline that never moves lies.
3. Diagnose by rates
Weak meetings → prospecting (L1); weak conversion → discovery/closing (L2-L3); weak basket → targeting/upsell (L4); long cycle → deciders/urgency. Rates point at the worksite: coach precisely, not everywhere.
🔎 Concrete example — 5-minute diagnosis
Younes's 3 numbers on one page.
Goal €100k | Pipeline €180k (1.8x: short!).
Conversion 15% (vs 30%) -> L2-L3 worksite (discovery/closing).
90-day cycle (vs 45) -> late deciders -> qualify earlier.
-> plan: +prospecting AND closing coaching.Reading: 3 numbers = 2 precise worksites.
Lesson: 3x coverage is the golden pipeline rule.
Section vocabulary
- Sales KPI
- Key indicator steering performance: few but relevant, tracked over time.
Simple example: Younes tracks 6 KPIs on one page, each tied to an action.
What it is not: 30 figures tracked to look pretty, with no action.
Reflex: does each tracked KPI trigger an action?
- Conversion rate
- Share of prospects becoming customers: the revealer of effectiveness.
Simple example: 15% instead of 30%: Younes diagnoses discovery/closing.
What it is not: praising call volume while ignoring conversion.
Reflex: where do we lose deals in the funnel?
- Average basket
- Average value of a sale; a lever via targeting and upsell.
Simple example: Basket sagging: Younes retargets and works the upsell (L4).
What it is not: slashing prices to "chase volume".
Reflex: how to grow value, not just count?
- Sales cycle
- First-contact-to-signature duration; a lengthening cycle signals a blockage.
Simple example: 90 days instead of 45: deciders qualified too late.
What it is not: following up without understanding where the deal sleeps.
Reflex: at which stage do deals stall?
- Forecast
- Likely sales = sum of amounts weighted by stage probability.
Simple example: €180k pipeline weighted at 15% = €27k likely, not 180.
What it is not: adding up gross amounts as a forecast.
Reflex: is my forecast built on my real rates?
In practice — Track KPIs and forecast sales
- Track a few relevant KPIs: conversion rate, average basket, cycle length, number of opportunities, revenue.
- Interpret them (against a trend, a goal): a low rate points to something to improve.
- Build sales forecasts from your pipeline and your conversion rates.
- Use your CRM data and adjust your actions based on facts rather than impressions.
Ready-to-say script — read your pipeline in 1 min
"Goal 100, pipeline 180 i.e. 1.8 times: short, we need 3 times. Conversion 15 instead of 30: discovery and closing worksite. 90-day cycle: we qualify deciders from the first call. This week: 20 more calls and 2 closing coachings."
Say in the weekly review facing the pipeline, figures posted, with 2 dated actions.
Copy-paste template — 5-min pipeline flash
GOAL: _______________ | GROSS PIPELINE: _______________ (x__)
REAL CONVERSION: ___% (vs ___%) | WEIGHTED FORECAST: _______________
BASKET: _______________ | CYCLE: ___ days (vs ___)
WORKSITE #1 (rate -> action): _______________
WORKSITE #2: _______________Solo / independent
Younes alone: 3 numbers suffice (pipeline x, conversion, cycle) on one page, a 15-minute Monday review.
Small business / tight budget
With no costly tool: spreadsheet + simple CRM, 10/30/60/90 probabilities, monthly ghost clean-up.
Algeria SME
Younes sets his forecast on local rhythms (peaks, travel): cautious probabilities, 3x pipeline all the more vital.
Starting team
Compare forecast vs actual each month: probabilities sharpen with experience, never with optimism.
✓ Best practices
- 6 KPIs, activity + efficiency, not revenue alone.
- 3x pipeline, weighted, cleaned and reviewed weekly.
- Each weak rate points at a precise worksite.
✗ Common pitfalls
- Steering by revenue alone, a rear mirror.
- Bloated pipeline of ghosts that never move.
- Coaching everywhere (hence nowhere) with no diagnosis.
Key takeaways
- Performance is managed with KPIs: conversion rate, average basket, cycle length, opportunities, revenue.
- KPIs combined with the funnel make it possible to build sales forecasts.
- Track few KPIs but relevant ones and interpret them (trend, goal).
- Managing by numbers turns selling into a measurable and improvable discipline.
48h challenge — apply tomorrow
Compute your weighted forecast (amount x probability) and your coverage (pipeline / goal): are you above 3x? If not, schedule 10 prospecting calls.
- I can name the 6 KPIs and the 3x rule.
- I can compute a weighted forecast.
- I have identified 1 worksite via my rates.
Frequently asked questions
Which sales indicators should you track first?
A few well-chosen KPIs suffice: the conversion rate (global and per stage — where do you lose deals?), revenue, the average basket, pipeline opportunities, cycle length, plus activity (calls, meetings) upstream. Few but relevant, tracked over time vs goals: each KPI should trigger an action. The CRM (5.1) supplies them if kept current.
How do you build reliable sales forecasts?
Weight each deal by its stage probability and sum, relying on real rates and an honest pipeline (neither optimistic nor bloated). Tell engaged deals apart from lingering "I will think about it", refine by comparing forecast and actual. A forecast is not a crystal ball: it is a regularly updated management tool, preferably cautious and honest.
€120k pipeline for a €100k goal, real conversion 30%. Verdict?