Customer Support Automation Score
Two support teams with identical ticket volumes can have completely different automation prospects. The difference is intent mix, data access and how escalation is designed. This scores those.
What makes a support operation ready to automate?
Four things. First, a concentrated intent mix — a few questions making up a large share of volume. Second, the answers to those questions living in a system the AI can read, not in an agent's knowledge. Third, a helpdesk that can be written to, so resolutions and context are recorded automatically. Fourth, a clear escalation model, so it is already understood which cases must reach a person. A team strong on all four can deploy quickly and safely; a team weak on data access will spend most of the project on integration before any customer sees a benefit.
Methodology
How this is calculated
Published in full, so you can disagree with it. A tool that hides its model is a lead form.
- Twelve questions across five categories, scored 0–1 for readiness.
- Data access carries the highest weight because it decides feasibility; volume and intent mix carry the next because they decide value.
- The overall score is the weighted average of category scores, and the priority list shows the weakest answers with a specific action.
Assumptions and limits
- Self-assessment. If you have never classified your tickets by intent, treat the volume and intent scores as provisional.
- This measures readiness, not value. Use the Customer Support ROI Calculator for the size of the opportunity.
- A high score does not remove the need for a pilot with a measured baseline.
FAQ
Questions about this tool
If you want this built
Turn the number into a plan.
Send us the workflow behind your result. We will come back with how we would automate it, what stays human, and what it takes to build.