Industry benchmarks and actionable insights from 939 B2B companies. Explore real-world sales metrics, AI productivity impact, and downloadable datasets.
Explore data-backed answers to common B2B sales operations questions, based on our 939-company benchmark.
B2B sales reps spend an average of 2.3 hours/day (11.5 hours/week) on CRM data entry. With AI automation, this drops to 1.4 hours/day — a 40% reduction.
B2B SaaS average pipeline conversion: Lead→MQL 25%, MQL→SQL 40%, SQL→Opp 60%, Opp→Close 30%. Overall: 1.8%.
B2B SaaS average: 45 days. Enterprise: 90 days | SMB: 30 days | Manufacturing: 60 days. AI reduces by 28%.
AI adoption increases productivity by 53% (15→23 deals/month). Key drivers: -40% CRM time, -28% deal cycle.
Optimal: 1-2 emails/week + 1 call/month. Over-contact (3+/week) reduces response rate by -40%.
Industry average: Accuracy 75%, Precision 80%, Recall 70%. Healthy threshold: F1 Score ≥ 0.75.
2025 B2B sales AI adoption: 42% (+15pt YoY). Top uses: Lead prioritization (68%), Email gen (55%), Scoring (48%).
Formula: (Revenue Lift + Cost Savings - CRM Cost) / CRM Cost × 100. Average ROI: 280% (8-month payback).
Ideal: 1-on-1s (30%), Strategy (25%), Analysis (20%), Hiring (15%), Admin (10%). Reality: Admin is 35% (over-allocated).
Remote average: 28% vs. In-person: 32% (-4pt). Demo video users: 35% (+7pt above average).
Healthy pipeline: Coverage Ratio ≥3.0, Velocity 30-45 days, Win Rate ≥25%, Stage distribution balanced.
Formula: (ΔRevenue + ΔCost - CRM Cost) / CRM Cost × 100. Variables: Team size, deal size, conversion, license cost.
Use these tools to calculate your team's potential savings and identify pipeline improvement opportunities.
Data Source: Anonymized CRM data from 939 B2B companies (2025 Q1-Q3)
Industries Covered: SaaS, Manufacturing, Consulting, Professional Services
Company Sizes: 5-500+ employees
Update Frequency: Quarterly
License: CC BY 4.0 (commercial use allowed, attribution required)