Salesforce CPQ Limits You Should Know Before Breaking Your Org!

In a previous post, I shared a curious case where an intern managed to break Salesforce CPQ. But let’s be honest—would you know where CPQ’s limits actually are before pushing them too far?

Understanding these boundaries is crucial because some configurations and tests might be unfeasible in a sandbox if these limits aren’t clear from the start. To help you navigate potential roadblocks, I’ve compiled a list of key Salesforce CPQ limitations that can impact your implementation and performance.

1. Price Rules: Some Features Just Won’t Work

If your Price Rules have the Evaluation Scope set to Configurator and the Target Object set to Product Option, be aware that Price Action Formula and Price Condition Tested Formula fields are not supported. If your logic relies on these formulas, you might need an alternative approach before hitting an unexpected limitation.

2. Too Many Price Rules Can Slow You Down

Salesforce doesn’t enforce a hard limit on Price Rules, but it is recommended to avoid excessive rules—keeping it around 50 rules in total. However, well-defined conditions can help mitigate performance issues, allowing for a higher number of rules without significant slowdowns.

3. The Hidden Limit of Price Actions Per Rule

The Salesforce documentation does not explicitly define a cap on Price Actions, but from experience, I’ve faced performance issues that required Salesforce Support intervention, and their recommendation was a maximum of 10 Price Actions per rule.

Pro Tip: Use the "Order" field in Price Actions to execute them sequentially rather than all at once. This helps prevent unnecessary load on the system.

4. Product Bundles: Bigger Isn’t Always Better

While Salesforce CPQ allows up to 500 options (Options) inside a Product Bundle, loading too many options into the Quote Line Editor (QLE) can severely impact performance.

My recommendation: Keep it around 100 options for optimal performance and usability.

5. The Maximum Number of Quote Lines

The maximum Quote Lines supported depends on your environment and configuration, but Salesforce documentation suggests staying under 200 Quote Lines per quote.

However, if you have 100 Price Actions per Quote Line, your CPQ configuration will likely break—so keep an eye on your pricing automation logic!

6. MDQ (Multi-Dimensional Quoting) Has Strict Limits

If you’re working with MDQ Quote Lines, be mindful of time segment limits.

Recommended: 12 segments per MDQ Quote Line ?? Maximum allowed: 99 segments

If you have monthly terms exceeding 120 months, MDQ won’t work!

7. Quote Templates Have a Surprising File Size Limit

When generating a Quote Template, the maximum file size is 2MB.

?This limit includes PDF attachments inside the template.

For many companies, this is one of CPQ’s biggest constraints when generating documents. If you deal with complex quotes that require detailed attachments, consider external document management solutions.

8. UI Performance & Configurator Slowness

The CPQ Product Configurator and Quote Line Editor (QLE) can become slow or unresponsive in certain situations:

• Bundles with 400+ options trigger Large Configurations Mode, which slows down product selection. Consider breaking bundles into smaller nested bundles to improve responsiveness.
• Guided Selling questions that return too many products can lead to Apex CPU timeouts. To avoid this, filter down product selections gradually instead of loading everything at once.
• If CPQ recalculates prices on every edit, performance can degrade. Consider disabling "Calculate Immediately" to improve QLE performance, especially for large quotes.
• Salesforce CPQ heavily relies on JavaScript, which means older browsers and slow computers can struggle with performance. Users with modern hardware and browsers (e.g., Chrome, Edge, Safari) experience faster interactions compared to those using older machines.

Final Thoughts: Avoid Breaking Your CPQ Org!

Knowing Salesforce CPQ limits is essential to avoid performance issues, system crashes, or frustrating roadblocks. By planning ahead and keeping these constraints in mind, your team can build scalable, efficient, and high-performing solutions.

Have you encountered any of these limitations before? Or maybe you’ve faced a completely different challenge in CPQ? Share your experience in the comments!

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