RevOps Jobs-to-Be-Done
- Dynamic pricing optimisation — AI recommends the right price for each customer and deal context based on historical win/loss data. KPI: Gross margin improves 2–5% without volume loss.
- Complex product configuration and quoting — Sales reps configure complex products and generate accurate quotes in minutes rather than hours. KPI: Quote generation time drops from days to minutes; quote accuracy improves.
- Discount governance — Enforce margin guardrails and approval workflows to prevent excessive discounting. KPI: Discount depth decreases; deal margin increases across the portfolio.
Key Features
- AI price optimisation: ML-based price recommendations by customer, segment, and deal context.
- CPQ engine: Complex product configuration with guided selling and rules engine.
- Quote management: Quote generation with multi-level approval and versioning.
- Discount governance: Margin guardrails and approval workflows for discounting.
- CRM integration: Native Salesforce integration for opportunity-linked quoting.
How It Fits Your Stack
Primary system of record: Salesforce
Key integrations: Salesforce, SAP, Oracle, Microsoft Dynamics
Data flows: CRM opportunity → PROS configuration and pricing → quote document → CRM approval and close.
Implementation & Ownership
- Time to first value: 3–6 months
- Implementation complexity: Very High
- Typical owners: RevOps, Pricing, Sales Ops, IT
Pricing & Contracts
- Pricing model: Enterprise license
- Indicative range: Custom; typically $100k–500k+/year
- Free tier: Yes
Who It's Best For
Enterprise manufacturers, distributors, and service companies with complex pricing and high SKU counts.
Good fit if:
- Companies with 10,000+ SKUs and dynamic market pricing
- Manufacturing or distribution companies where pricing science drives margin
- Enterprise sales teams quoting complex configured products
Probably not ideal if:
- You're a SaaS company with simple subscription pricing
- Your product catalog has fewer than 100 products
Proof & Buyer Signals
Ratings: G2 4.2 / 5 (80+ reviews)
What buyers praise:
- Pricing AI accuracy
- Complex CPQ capabilities
- Manufacturing expertise
Common complaints:
- Very long implementation timeline
- High cost
- Complex administration
Pros
- Industry-leading AI pricing for manufacturing and distribution
- Handles the most complex CPQ scenarios in the market
- Proven at enterprise scale across many verticals
Cons
- One of the most expensive and complex CPQ implementations
- Long time to value — not suitable for quick wins
Often Compared With
- Salesforce CPQ — Salesforce CPQ is simpler and CRM-native; PROS adds AI pricing optimisation for complex pricing environments.
- Vendavo — Both target manufacturing/distribution; PROS has stronger AI pricing, Vendavo has stronger deal management.
