CPQ Analytics
Monday pipeline review counted CRM closed-won. Nobody could say how many quotes were still in CPQ approval or stuck before quote PDF send. Mercura CPQ analytics shows the full funnel in one place.
The challenge
Monday pipeline review counted CRM closed-won. Nobody could say how many quotes were still in CPQ approval or stuck before quote PDF send.
A manufacturer of sortation conveyor modules for parcel hub upgrades sells through inside sales, regional dealers, and a buyer self-service portal. Every Monday the sales VP opens CRM for closed-won totals and ERP for shipped orders. When the CFO asks how much pipeline is still configuring, awaiting engineering approval, or waiting for quote PDF release, someone exports CPQ sessions into Excel and spends half a day joining CRM opportunity IDs.
Quotes that stall in approval for nine days look like active pipeline in CRM because the rep marked the opportunity as proposal sent. Deals stuck after configuration but before quote document release disappear from both systems until someone manually checks the CPQ queue. Product management cannot see which divert options appear most in open quotes versus closed orders.
Sales analytics focuses on rep activity and win rates from CPQ sessions. Pricing analytics tracks margin leakage and discount patterns on quoted lines. Quote analytics measures conversion and cycle time through quote stages. Configuration insights surfaces option demand and abandoned configs. CPQ analytics is different: Mercura cross-functional dashboards span configuration, pricing, approval, and quote pipeline so leaders see the full CPQ funnel in one place without manual CRM-CPQ-ERP joins.
Inquiry to config to price to approval to order should not require a spreadsheet join every Monday because CRM closed-won and CPQ stage data sit in separate tools.
CPQ funnel
Quotes tracked from config to order
Stage aging
Days deals sit before approval or send
Cross-channel
Same view for rep, dealer, buyer sessions
How it works
How Mercura CPQ analytics works
Mercura records stage events at each CPQ step: configuration started and completed, price calculated, approval requested and resolved, quote PDF generated, and order submitted. Dashboards aggregate by product line, territory, channel, rep, and time period with role-appropriate views for sales leadership, product management, and finance. Stage aging highlights quotes waiting in approval or before quote send. Filter by dealer portal, self-service, or inside sales sessions to compare channel behavior. Analytics data exports through API to BI tools such as Tableau, Power BI, or Looker for custom reports. Someone must define which stages matter for forecast reviews, set aging thresholds for alerts, and validate dashboard definitions after workflow changes.
What's included
What CPQ analytics covers
- Cross-functional dashboards from configuration through order submission
- Quote pipeline by stage with value and aging indicators
- Approval queue visibility with time-in-stage metrics
- Configuration and pricing activity grouped by channel and rep
- Option mix analysis on open and closed quotes
- Conversion metrics from config start to quote send to order
- Time-series trends for volume, margin, and stage duration
- API export to BI tools for custom executive reporting
The difference
CPQ visibility before and after Mercura analytics
- Pipeline reviews count CRM totals without CPQ stage detail
- Approval queue invisible until someone opens CPQ admin
- Quotes stuck before PDF send missing from forecast
- Cross-channel sessions require separate spreadsheet joins
- Product teams see orders but not in-flight option demand
- Full CPQ funnel visible alongside CRM pipeline context
- Stage aging surfaces stalled approval and quote send deals
- Rep, dealer, and buyer sessions in one filtered view
- Option mix on open quotes informs product and pricing reviews
- API feeds BI tools without weekly export routines
Real-world application
Example workflow: parcel hub pipeline review with CPQ stage data
A builder of sortation conveyor modules for parcel hub upgrades ran Monday reviews from CRM closed-won while CPQ held quotes in engineering approval and pre-PDF stages. Finance underestimated near-term revenue because $1.4M in configured pipeline never appeared in CRM totals. After Mercura CPQ analytics, the sales VP opened one dashboard showing config, approval, and quote send stages by territory and saw nine-day approval delays on divert module quotes before month-end forecast.
Business impact
Why CPQ analytics is funnel visibility, not a replacement for specialized analytics modules
CPQ analytics gives leadership one view across configuration, pricing, approval, and quote stages before drilling into rep, price, quote, or configuration detail. It complements sales analytics for coaching, pricing analytics for margin review, quote analytics for conversion funnels, and configuration insights for product demand. Mercura does not replace CRM forecasting, ERP order history, or external BI strategy. Someone must own dashboard definitions and aging thresholds. If the pain is "Monday review counts CRM closed-won but CPQ approval queue is invisible", CPQ analytics aligns inquiry, configuration, price, approval, and order with what is actually moving through the CPQ funnel.
See CPQ approval queue and pre-send quotes beside CRM closed-won in one Monday review dashboard
Book a demo and walk CPQ analytics until stage aging, channel filters, and option mix on open quotes match what your pipeline review actually needs.
Let’s build together.
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