Using Spiich
29% Selling, 71% Admin: Why Your Reps Miss Quota
Research & Insights
Jan 26, 2026
Salesforce (2024) surveyed 5,500 sales professionals across 27 countries and found that reps spend just 29% of their workweek on selling activities. The remaining 71% goes to administrative work, data entry, and preparation - figures independently confirmed by both Bain & Company (2017) and McKinsey & Company (2023).
The problem has proven persistent. Salesforce (2024) identified only a two-percentage-points gain in selling-time between 2022 and 2024, despite significant technology investment. The consequences: 67% of reps didn't expect to meet quota in 2024, and 84% missed their quota in 2023 (Salesforce, 2024).
Want to know how much sales admin costs your company?
Salesforce (2024) breaks down how reps spend an average 40-hour workweek:
Activity | % of Week | Hours/Week |
|---|---|---|
Selling activities | 29% | 11.6 |
Meeting in-person with customers | 12% | 4.8 |
Connecting virtually with customers | 9% | 3.6 |
Prospecting | 8% | 3.2 |
Data handling | 28% | 11.2 |
Manual CRM data entry | 9% | 3.6 |
Administrative tasks | 9% | 3.6 |
Generating quotes/proposals | 10% | 4.0 |
Preparation | 26% | 10.4 |
Preparation and planning | 9% | 3.6 |
Researching prospects | 9% | 3.6 |
Prioritizing leads | 8% | 3.2 |
Internal | 17% | 6.8 |
Internal meetings and training | 9% | 3.6 |
Downtime | 8% | 3.2 |
Data handling and preparation account for 54% of the workweek - over 21 hours managing information rather than engaging customers.
McKinsey (2023) analyzed nearly 500 B2B companies and found that top-quartile performers generate 2.6 times higher gross margin per sales dollar than bottom-quartile teams.
The gap isn't just about effort - it's about focus. McKinsey found that underperforming teams spend more than 50% of their time serving customers who contribute 20% or less of revenue. Without accurate data on account potential, reps default to familiar relationships rather than high-value opportunities.
Leading companies offloaded up to 50% of non-selling tasks and automated core sales processes, resulting in:
Metric | Improvement |
|---|---|
Sales capacity | +20% (8 hours/week per rep) |
Productivity | Up to 30% improvement |
Revenue per sales FTE | +3-15% |
Cost-to-serve | Reduced 10-20% |
For a 10-rep team, 20% capacity gain equals 4,160 additional selling hours per year - the equivalent of adding 2 full-time reps without recruiting cost or ramp time.
Bain & Company (2017) found that top performers hold weekly pipeline reviews 50% more often than average teams - a tactic only effective with accurate CRM data. Bain further found that 40% of customer-facing time goes to lower-tier accounts. Without accurate CRM data, reps can't see which accounts deserve their attention.
Spiich is an AI sales assistant that handles your reps' non-selling work - doubling the time spent selling. It integrates deeply into your sales stack to manage qualification, buyer discovery, meeting prep, CRM admin, and follow-ups automatically. Spiich targets the specific activities identified in the research from Salesforce, McKinsey and Bain:
Activity | Current State | Hours/Week | With Spiich | With Spiich |
|---|---|---|---|---|
Manual CRM entry (9%) | Typing after calls | 3.6 hrs | CRM updated through voice | 3.6 → 0.6 hrs |
Preparation (9%) | Manual assembly of CRM, email, research | 3.6 hrs | Automated meeting briefs | 3.6 → 1.1 hrs |
Researching prospects (9%) | Manual lookup across systems | 3.6 hrs | Synthesized account summaries | 3.6 → 1.6 hrs |
Prioritizing leads (8%) | Manual pipeline review | 3.2 hrs | Proactive intelligent alerts | 3.2 → 1.7 hrs |
Total | 14.0 hrs | 14 → 5 hrs |
For a 10-rep team, 9 hours saved per rep and week equals 90 hours weekly - equivalent to adding more than two full-time sales reps.
Based on the research above, Spiich creates four measurable financial impacts:
1. More selling time = more revenue
McKinsey (2023) reports that redirecting time to customer-facing activities increases revenue per sales FTE by 3-15%.
Team quota | 3% revenue lift | 10% revenue lift | 15% revenue lift |
|---|---|---|---|
$500K/rep × 10 reps | $150,000 | $500,000 | $750,000 |
2. Better account targeting = lower cost, higher revenue
McKinsey (2023) reports that better account prioritization reduces cost-to-serve by 10-20% and increases revenue per FTE by 3-15%. The same research found that underperforming teams spend more than half their time on customers contributing less than 20% of revenue - a misallocation that stems from incomplete data on account potential.
3. Recovered missed follow-ups
Salesforce (2024) reports that 84% of sales reps missed quota in 2023. Many missed opportunities trace back to incomplete follow-ups and overlooked touchpoints. Research published in Harvard Business Review found that over 24% of U.S. companies took over 24 hours to respond to their leads and 23% of companies never responded at all (Oldroyd et al., 2011). 80% of deals are closed between 5 and 12 contact attempts, yet 48% of sales reps don't follow up after the initial call (Martal Group, 2025). Assuming 4% conversion rate on abandoned deals, that alone can increase revenue by 2%.
4. Better data quality = accurate forecasting
Salesforce (2024) reports that only 35% of sales professionals completely trust the accuracy of their organization's data. Further, 47% say inaccurate data is more challenging than a year ago (Salesforce, 2024). Poor data quality affects:
Process affected | % of teams impacted |
|---|---|
Forecasting accuracy | 39% |
Performance management | 39% |
Competitive intelligence | 36% |
Why is CRM data so unreliable? Bain & Company (2017) identified the root cause: self-reported data from CRM tools and time studies is "inherently flawed." Reps report what they intend to do, not what they actually do. In one case, account managers self-reported spending significant time with customers - but software analysis revealed they spent only one-third of their time in customer meetings.
Spiich solves this by capturing information in the moment, as it happens. When updating CRM requires speaking instead of typing, reps do it. Data completeness improves because friction disappears.
Category | Mechanism | Impact |
|---|---|---|
More selling time | Hours redirected to customers | Revenue per FTE +3-15% |
Better account targeting | Focus on high-value opportunities | Cost-to-serve reduced 10-20%, Revenue +3-15% |
Recovered follow-ups | Tasks captured and surfaced | Revenue +2% |
Better data quality | Complete, current CRM records | Forecast accuracy improved |
The Sales Productivity Calculator applies these research findings to your situation. Enter your team size, quota, rep salary and current selling time percentage to see projected Spiich impact across all four categories.
Bain & Company. (2017). How Do Salespeople Really Spend Their Time? Not the Way They Say.
Martal Group. (2025). Sales Follow-Up Statistics and Actionable Strategies for 2025.
McKinsey & Company. (2023). How top performers outpace peers in sales productivity. Growth, Marketing & Sales Practice.
Oldroyd, J. B., McElheran, K., & Elkington, D. (2011). The Short Life of Online Sales Leads. Harvard Business Review
Salesforce. (2024). State of Sales Report, Sixth Edition. Salesforce Research.