- Features > CPQ Analytics
CPQ Analytics
Track every stage of your CPQ process with real-time analytics. Understand what is being configured, how pricing performs, where quotes are lost, and which products drive the most revenue.
Real-time
Dashboard refresh rate
100%
CPQ activity captured and reportable
Zero
Manual data export required
The Challenge
Sales Leaders Cannot See What Is Happening Inside Their CPQ Process
Most CPQ implementations generate data but surface very little insight. Sales leaders can see closed orders in their ERP, but they cannot see how quotes are moving through the pipeline, where they are stalling, or which configurations are winning versus losing in the market.
Without visibility into CPQ activity, pricing decisions are made on intuition. Product management cannot identify which features or configurations are most commonly requested. Sales managers cannot coach reps based on individual quoting behavior.
When analytics data does exist, it typically requires manual extraction and manipulation in spreadsheets — a process that is slow, error-prone, and produces results that are already outdated by the time they are reviewed.
The result is a strategic blindspot at the exact point in the sales process where the most revenue is won or lost: configuration, pricing, and quoting.
How It Works
How CPQ Analytics Works
Mercura captures structured data at every step of the CPQ process — from initial product selection through configuration, pricing, quoting, approval, and order submission. This data is available in real-time dashboards organized by function: sales performance, pricing health, configuration patterns, and quote pipeline status. Dashboards are accessible to sales leaders, product managers, and finance teams with role-appropriate views. Data can be filtered by product line, customer segment, sales territory, time period, or channel. All analytics data is available via API for integration with BI tools such as Tableau, Power BI, or Looker.
What's Included
Key Capabilities
- Real-time dashboards for quote volume, win rate, and pipeline value
- Configuration frequency analysis — which options are selected most often
- Pricing performance tracking — margin by product, customer segment, and sales rep
- Quote-to-order conversion funnel with drop-off analysis by stage
- Sales rep quoting activity and productivity metrics
- Approval workflow analytics — approval rates, rejection reasons, and cycle times
- Time-series analysis for trend identification across any metric
- BI tool integration via API for custom reporting in Tableau, Power BI, or Looker
The Difference
Before and After CPQ Analytics
- Sales leaders cannot see quote pipeline or CPQ activity in real time
- Pricing decisions made on intuition with no performance data
- Configuration trends invisible — product development flying blind
- Analytics require manual export and spreadsheet manipulation
- Individual rep quoting behavior unobservable for coaching
- Full CPQ pipeline visible in real time — no manual data collection
- Pricing performance tracked by product, segment, and rep — decisions backed by data
- Configuration trends surface automatically — product teams act on real demand signals
- Live dashboards update continuously — no export process required
- Rep-level quoting analytics enable targeted coaching and performance management
Real-World Application
Example Use Case: Capital Equipment Manufacturer
A capital equipment manufacturer had no visibility into their quoting process beyond closed orders. Their sales VP could not answer basic questions: How many quotes were outstanding? Which products had the best win rates? Where were quotes losing momentum? After implementing Mercura CPQ Analytics, the sales VP had real-time access to a live quote pipeline showing value, stage, and days in stage for every active quote. Within 60 days, two patterns became visible — a specific product configuration had a win rate 40% below average, and quotes that sat in internal approval for more than 5 days had a 35% lower close rate. Both insights led to corrective action: the underperforming configuration was repriced, and the approval threshold was raised to reduce the number of quotes requiring formal review.
Quote turnaround dropped from 3 days to under 4 hours.
Business Impact
Why CPQ Analytics Matters
CPQ analytics transform quoting from a transactional activity into a strategic asset. When you can see precisely how configurations, pricing, and deal structures correlate with win rates and margins, you can make better product decisions, better pricing decisions, and better coaching decisions. Mercura's analytics layer ensures that every quote generated in your CPQ system contributes to a growing base of commercial intelligence — not just to a closed transaction.
Get Full Visibility Into Your CPQ Process
Book a demo to see how Mercura analytics surface the insights that drive better pricing, configuration, and sales decisions.
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