Sales Analytics
Regional sales manager compared rep win rates. CRM showed pipeline age in days. CPQ showed which reps send quote PDFs within forty-eight hours of configuration complete. Mercura sales analytics coaches from CPQ behavior, not stale CRM fields.
Rep activity
Quotes created and sent per rep
Win rate
Closed-won vs quoted configurations
Cycle speed
Hours from config complete to quote send
The challenge
Regional sales manager compared rep win rates. CRM showed pipeline age in days. CPQ showed which reps send quote PDFs within forty-eight hours of configuration complete.
A manufacturer of vertical lift modules for spare parts distribution centers runs inside sales across six regions. Each rep updates CRM when they remember. The regional manager exports a pipeline report showing opportunity age and stage, then asks why one rep closes twice as many hub retrofit quotes as another despite similar territory size.
CRM cannot show that the top rep completes configuration and releases quote PDFs within two days while others leave CPQ sessions open for a week before sending. It cannot show that losing reps skip optional kit lines that appear in eighty percent of winning VLM configurations. Coaching defaults to anecdote because commercial behavior lives in CPQ, not in opportunity notes updated last month.
CPQ analytics spans the full funnel from configuration through approval to order. Pricing analytics tracks margin and discount patterns on quoted lines. Quote analytics measures stage conversion and quote aging. Configuration insights surfaces option demand and abandoned configs. Sales analytics is different: Mercura rep-level dashboards from CPQ session data show quoting activity, win rates, configuration choices, and cycle speed so managers coach on behavior during the quote, not outcomes after the deal is lost.
Inquiry to config to price to approval to order should not depend on CRM fields reps update when they remember because actual quoting behavior is recorded in CPQ sessions.
How it works
How Mercura sales analytics works
Mercura captures rep-level CPQ events: configuration started and completed, price calculated, approval requested, quote PDF generated, and order submitted. Dashboards aggregate by rep, team, territory, product line, and time period. Managers compare quote volume, win rate, average deal size, and hours from configuration complete to quote send. Drill into individual rep sessions to see which option combinations appear in won versus lost quotes. Team pipeline views show active quote value and stage without waiting for CRM reconciliation. Data exports through API to BI tools for custom scorecards. Someone must define coaching metrics, set cycle-speed thresholds for alerts, and review rep dashboards after workflow or catalog changes.
What's included
What sales analytics covers
- Rep-level quoting activity: configs started, quotes sent, orders won
- Win rate by rep, product line, customer segment, and deal size
- Hours from configuration complete to quote PDF send per rep
- Team pipeline dashboard with value, stage, and aging from CPQ data
- Configuration choices in won vs lost quotes for coaching
- Territory and regional performance comparison
- New vs repeat customer quoting breakdown by rep
- Exportable rep scorecards for performance review cycles
The difference
Sales coaching before and after CPQ sales analytics
- Managers see opportunity stage updated when rep remembers
- Win rate analysis requires manual CPQ and CRM joins
- No view of hours from config complete to quote send
- Coaching reactive after deals are lost
- Top rep behaviors invisible to the rest of the team
- Rep activity tracked from every CPQ session
- Win rate and cycle speed available by rep and territory
- Configuration patterns in won quotes visible for coaching
- Managers intervene during quoting, not after close
- Scorecards export for formal performance reviews
Real-world application
Example workflow: VLM rep scorecard from CPQ session data
A builder of vertical lift modules for spare parts distribution centers compared rep win rates from CRM while losing reps left CPQ sessions open a week before quote send. After Mercura sales analytics, the regional manager saw cycle speed and kit-line attachment rates by rep, coached the team on configuration patterns from won hub retrofit quotes, and cut average hours from config complete to quote PDF send without changing territory assignments.
Business impact
Why sales analytics is rep coaching from CPQ behavior, not a replacement for CRM forecasting
Sales analytics puts quoting behavior in front of managers while deals are still open. It complements CPQ analytics for funnel visibility, quote analytics for stage conversion, pricing analytics for margin review, and configuration insights for product demand. Mercura does not replace CRM opportunity management, compensation planning, or external BI strategy. Someone must define which rep metrics drive coaching and review thresholds after process changes. If the pain is "CRM shows pipeline age but not who sends quote PDFs within forty-eight hours", sales analytics aligns inquiry, configuration, price, approval, and order with how reps actually work in CPQ.
See which reps send quote PDFs within forty-eight hours of configuration complete on one rep scorecard
Book a demo and walk sales analytics until rep cycle speed, win rate, and configuration patterns in won quotes match how your regional managers coach today.
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