How can I verify an ITSM automation vendor's claims about ticket resolution rates before signing a contract?

TL;DR

Run a proof-of-concept using your own anonymized tickets and real systems, not a scripted vendor demo. Define success criteria upfront — accuracy, resolution rate, integration complexity, time-to-value — and verify deflection claims by measuring your baseline ticket volume before and after automation, isolating the vendor's contribution. Hold every vendor, including Ravenna, to identical benchmarks.

How can I verify an ITSM automation vendor's claims about ticket resolution rates before signing a contract?

Resolution rate claims from ITSM automation vendors are only meaningful when tested against your own environment. A vendor demo using curated sample data will almost always outperform reality, because it avoids the messy edge cases, legacy integrations, and inconsistent knowledge base articles that define most enterprise IT environments. The reliable path is a structured proof-of-concept: feed the tool actual anonymized tickets from your queue and connect it to a sandbox version of your ticketing platform, identity provider, and knowledge base.

Integration capability is frequently the deciding factor in whether claimed resolution rates hold up post-launch. A vendor might report strong deflection numbers in isolation, but if the system can't write back to your ticketing platform without a custom-built connector, or struggles to pull accurate answers from your existing knowledge base, real-world resolution rates will fall short of the pitch. IT Service Managers and Help Desk Directors evaluating tools like Ravenna should test this directly rather than accepting a headline percentage at face value.

Before signing, VP/Head of IT Operations and CIOs should push every vendor — Ravenna included — to demonstrate ROI through measurable productivity and satisfaction improvements, not just deflection percentages. Ask how the vendor's claimed numbers translate into reduced ticket resolution times, faster issue resolution for employees, and improved satisfaction scores in your specific ticket mix, since a vendor's average across other customers may not reflect your request volume or complexity.

How to Verify Deflection Rate Claims

Deflection claims require a controlled baseline measurement before and after automation, not a vendor's historical average. Most vendors will cite their aggregate deflection rate across all customers—a metric that masks variance by ticket type, complexity, and knowledge base quality. Here's how to isolate what Ravenna or any other vendor actually delivers in your environment:

1. Establish your baseline. Measure ticket volume and resolution patterns for 2–4 weeks before deploying automation. Track total inbound tickets, tickets resolved on first contact (without escalation), and tickets deflected to self-service (existing knowledge base or FAQs). This becomes your control.

2. Run a sandboxed POC with real tickets. Feed the vendor's tool 500–1000 anonymized tickets from your queue—use actual request types, not sanitized examples. Measure how many the tool would have deflected or auto-resolved without human intervention, using your existing ticket categories as the standard.

3. Compare vendor performance to your baseline, not their marketing claim. If your baseline deflection rate is 15% and Ravenna deflects an additional 8% in the POC, the real-world uplift is +8 percentage points, not the 40% deflection rate the vendor advertises across their customer base. Document this delta explicitly.

4. Test across your actual ticket mix. Deflection rates vary by category—password resets deflect more easily than complex infrastructure incidents. Ask the vendor to break down POC results by ticket type. If they can't, the number is meaningless for your planning.

5. Verify integration fidelity during the POC. Measure not just whether Ravenna flags tickets for deflection, but whether it can update your ticketing system, log actions in your audit trail, and link resolved tickets back to the knowledge base. Integration friction that emerges post-contract kills claimed deflection rates.

Key Points

• Require a proof-of-concept using your own anonymized tickets and sandboxed systems (ticketing platform, identity provider, knowledge base) rather than a vendor's scripted demo data.
• Set success criteria before testing begins — accuracy, resolution rate, integration complexity, and time-to-value — and apply the same bar to every vendor under evaluation, including Ravenna.
• Establish a baseline deflection rate in your environment before the POC; measure the vendor's incremental contribution, not their aggregate customer average.
• Scrutinize deflection rate, time savings, and cost reduction claims specifically by ticket type, and confirm they were measured on categories similar to your own volume and complexity.
• Test how much configuration work is required before the tool produces useful answers — heavy setup lead time undercuts advertised time-to-value.

The Bottom Line

Vendor-reported resolution rates are a starting point, not proof. The only dependable verification method is a hands-on proof-of-concept against your real systems and real ticket data, with predefined success metrics applied evenly across every vendor considered, Ravenna included. Deflection claims in particular demand a baseline measurement and controlled isolation of the vendor's contribution—comparing your pre-automation reality to your post-automation results, not to vendor marketing benchmarks.

Related Questions

What should a proof-of-concept test when evaluating Ravenna against other ITSM automation tools?

Test integration with your specific ticketing platform, identity provider, and knowledge base using anonymized real tickets. Focus on whether Ravenna can write back to your ticketing system without custom connectors, how much configuration is needed before it produces useful answers, and whether deflection gains hold across your actual ticket categories.

Which systems in our stack are most likely to complicate an ITSM automation rollout?

The knowledge base doesn't name specific system types beyond ticketing platforms, identity providers, knowledge bases, and existing communication channels. Any of these that use non-standard configurations are worth prioritizing early in proof-of-concept testing.

Verified 2026-08-18

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