Prediction Performance

What is a Good Sales Forecast Accuracy Benchmark?

Updated: November 27, 2025 | Source: Optifai Forecasting Study 2025 (N=287 companies)

TL;DR

Sales forecast accuracy benchmarks 2025: Top performers achieve ±5-10% variance, median companies ±15-25%, struggling teams ±30%+. By forecast horizon: 30-day forecast 85-90% accuracy, 60-day 75-80%, 90-day 65-75%. AI-assisted forecasting improves accuracy by 15-25%. Key drivers: CRM data quality, deal stage definitions, and rep sandbagging/happy ears. Source: Optifai Forecasting Study 2025 (N=287 companies).

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Related Resources

Pipeline Coverage RatioWin Rate by StagePipeline VelocityMethodology

Key Data

Forecast Variance by Performance

Top Quartile
±5-10%variance
Median
±15-25%variance
Bottom Quartile
±30%+variance
Elite Performers
±5%variance

Source: Optifai Forecasting Study 2025

Updated: 2025-11-27

Accuracy by Forecast Horizon

30-Day Forecast
85-90%accuracy
60-Day Forecast
75-80%accuracy
90-Day Forecast
65-75%accuracy
Accuracy Decay
5-8%per month

Source: 287 B2B companies

Forecasting Method Accuracy

Rep Roll-Up
±25-35%variance
Weighted Pipeline
±18-25%variance
Historical Trend
±15-20%variance
AI/ML-Assisted
±8-15%variance

Source: Method comparison

AI Forecasting Impact

Accuracy Improvement
15-25%better
Setup Time Required
12+months data
CRM Data Quality
Criticalrequirement
ROI Timeline
3-6months

Source: AI vs traditional methods

Accuracy by Forecast Horizon

30-Day Forecast

Deals closing this month

85-90%
accuracy

Deals in late stages with clear close dates. Most predictable.

60-Day Forecast

Deals closing in 1-2 months

75-80%
accuracy

Mid-stage deals with some uncertainty. Timing can slip.

90-Day Forecast

Quarterly outlook

65-75%
accuracy

Early-stage deals, longer cycles. Most variance.

Accuracy by Forecasting Method

MethodTypical AccuracyEffort LevelBest For
Rep Roll-Up
Sum of rep commits
±25-35%LowSmall teams, simple sales
Weighted Pipeline
Stage × probability
±18-25%MediumStandard B2B sales
Historical Trend
Past performance analysis
±15-20%MediumStable markets
AI/ML-Assisted
Predictive scoring
±8-15%High (setup)Data-rich environments

AI Impact: Companies using AI-assisted forecasting report 15-25% improvement in accuracy. Key requirements: clean CRM data, 12+ months of historical deals, and consistent stage definitions.

The 5 Forecast Accuracy Killers

1

Sandbagging

Reps hide deals to beat quota later. Creates artificial pipeline lumpiness.

2

Happy Ears

Over-optimistic deal assessment. "They loved the demo!" = not a commit signal.

3

Zombie Deals

Stale opportunities never cleaned up. Inflates pipeline artificially.

4

Stage Confusion

Inconsistent criteria for stage advancement. "Proposal sent" means different things.

5

End-of-Quarter Stuffing

Deals mysteriously accelerate at quarter end—often with heavy discounts that hurt margins. Creates false seasonality patterns.

About This Data

This benchmark is based on forecast accuracy data from 287 B2B companies collected in 2025. Data is segmented by forecast horizon, method, and performance quartile to ensure relevant comparisons.

Read full methodology
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Update History

Data last updated: November 27, 2025

v1.0November 27, 2025
  • ✓Initial publication with forecast accuracy benchmarks from 287 companies
  • ✓Added accuracy by forecast horizon (30/60/90 day)
  • ✓Included forecasting method comparison
  • ✓Documented AI-assisted forecasting impact (15-25% improvement)
  • ✓Added common accuracy killers and improvement strategies

Impacted metrics:

Forecast accuracy benchmarks

Regularly updated with latest industry data