The Reality of CPQ: What Customers Expect vs. What Vendors Deliver

Based on insights gathered from 128 customer reviews through out my research journey for Configure, Price and Quote (CPQ), this blog explores the gaps between customer expectations and what CPQ vendors actually offer. While CPQ solutions promise streamlined configuration, accurate pricing, and fast quoting, many still struggle with critical technical and operational challenges that impact real-world usability.

Configuration: The Complex Reality of Customization

What Customers Expect:

1. Dynamic, Rule-Based Configurations: Customers want robust configuration logic that ensures only valid product combinations can be created, reducing order errors.

2. Seamless CAD & 3D Visualization Integration: Industries like manufacturing demand real-time 3D visualizations and CAD exports to validate configurations.

3. Needs-Based Guided Selling: The system should intelligently guide sales reps or customers through complex configurations without requiring deep technical knowledge.

4. Low-Code/No-Code Customization: Businesses want the ability to modify configurations without depending heavily on IT teams.

5. Performance and Scalability: Large enterprises expect CPQ systems to handle high-volume transactions without lag or performance bottlenecks.

Where Vendors Fall Short:

• Rigid Configuration Logic: Many CPQ platforms require predefined, hardcoded rules, making real-time adjustments difficult. Any change often requires extensive admin work.

• Limited CAD & 3D Support: While some vendors offer CAD automation, real-time visualization is often clunky or limited to specific use cases, making it less effective for complex engineering-to-order (ETO) workflows.

• Complex Needs-Based Configuration: Some solutions claim to offer AI-driven guided selling but still require significant manual input to build valid configurations.

• High Technical Dependency: While some CPQ platforms market themselves as no-code, real customization still demands experienced admins who understand backend rule structures.

• Scalability Issues: Performance bottlenecks arise when processing highly complex configurations, leading to slow response times, especially in high-volume environments.

Pricing: Accuracy vs. Complexity

What Customers Expect:

1. Real-Time Dynamic Pricing: Prices should auto-update based on configurations, discounts, and market conditions.

2. Multi-Tier & Subscription-Based Pricing: Businesses with subscription or consumption-based models need flexibility in structuring and applying complex pricing rules.

3. Intelligent Margin & Discount Controls: Automated workflows should ensure that discounts and pricing remain within predefined margins.

4. Seamless Integration with ERP & CRM: Pricing should pull from ERP systems while remaining synchronized with sales tools like CRM.

5. AI-Driven Competitive Pricing: Businesses expect AI-driven insights that recommend optimal pricing based on market trends and historical data.

Where Vendors Fall Short:

• Lack of Truly Dynamic Pricing: Many CPQ systems still rely on static pricing tables, requiring frequent manual updates rather than dynamically adjusting to changing conditions.

• Complexity in Multi-Tier Pricing: Vendors often struggle to support layered pricing logic, making it difficult to implement multi-tier, consumption-based, or region-specific pricing strategies.

• Limited AI in Pricing Decisions: While some solutions claim AI capabilities, few actually use predictive analytics or market intelligence to optimize pricing in real time.

• ERP/CRM Integration Issues: Pricing synchronization between CPQ, CRM, and ERP is often unreliable, leading to mismatches in quoted vs. final pricing.

• Manual Effort in Discounting Workflows: Many solutions lack automated checks for margin protection, requiring manual approvals that slow down deal closures.

Quoting: The Balance Between Speed and Flexibility

What Customers Expect:

1. Fast, Error-Free Quote Generation: Quotes should be accurate, structured, and instantly generated without requiring extensive manual review.

2. Flexible Customization of Quotes: Sales teams should be able to edit proposals easily, adjusting line items, discounts, and terms without disrupting workflows.

3. Approval Automation & Compliance: Discount thresholds and deal approvals should be automated to prevent unnecessary delays.

4. Multi-Format Output & E-Signature Support: Quotes should be exportable in PDF, Word, and Excel, with built-in e-signature workflows.

5. Customer Engagement Analytics: Sales teams need visibility into quote engagement—who opened the document, when, and what sections were viewed the most.

Where Vendors Fall Short:

• Slow Quote Generation in Complex Scenarios: While basic quotes are easy to generate, large, multi-product, or highly customized deals still require significant manual adjustments.

• Limited Flexibility in Quote Customization: Making changes to an existing quote often disrupts workflows, requiring re-approvals or backend modifications.

• Manual Approval Bottlenecks: Despite automation claims, many CPQ platforms still require human intervention for discount approvals, slowing deal velocity.

• Weak Document Customization: Some CPQ tools restrict branding, formatting, and conditional content within quote templates, limiting personalization options.

• Lack of Advanced Engagement Analytics: Most CPQ solutions don’t offer real-time analytics on how customers interact with quotes, making it harder for sales teams to follow up strategically.

The Role of AI in CPQ: A Reality Check

While AI is marketed as a game-changer in CPQ, actual implementations remain limited. Where AI could make a difference—such as intelligent pricing recommendations, predictive quoting, and automated configuration corrections—most vendors still rely on static rule-based approaches. AI in CPQ is still in its infancy, and businesses expecting full AI-powered automation will likely be disappointed.

Final Thoughts

While CPQ software has come a long way, customers are still dealing with significant gaps between expectations and vendor offerings. Configuration tools remain too rigid, pricing automation lacks real-time intelligence, and quoting processes are often slowed down by manual interventions.

As an analyst at QKS Group, we focus on accelerating technology advancement and adoption. If you want to explore market insights, vendor analysis, or future trends in CPQ, let’s connect!