Customer experience reflects how the work gets done
Customers feel the effects of ownership, handoffs, data, tools, and frontline decisions. Fixing one touchpoint without looking at the work around it rarely solves the real problem.
About Cadence Lab
Customer problems don’t stay in one department.
I’m Matt Rabah. I help organizations find where customer experience breaks across teams, systems, and decisions, then turn what we learn into practical change.
Founder & CXO
Matt Rabah
I’ve spent 12 years in customer experience and customer success. I started Cadence Lab to help organizations understand why customer problems keep coming back and fix the way the work gets done.
Official bio
Experience across the full customer journey.
Matt Rabah is the Founder and CXO of Cadence Lab, an independent customer experience practice. He works directly with organizations on service operations, customer lifecycle programs, CRM workflows, and practical AI adoption.
His background includes 12 years in customer experience and customer success. His work has included Salesforce, HubSpot, Gainsight, Zendesk, Delighted, and Oracle.
Matt’s AI experience includes ChatGPT, Gemini, Claude, local models, Salesforce Agentforce, and building task-specific agents. He helps organizations choose useful applications, define where people need to stay involved, and prepare the workflows and data those applications need.
Cadence Lab is a solo practice, and Matt leads every engagement. Clients work with him from the first diagnosis through recommendations, workflow design, and measurement planning.
Point of view
The problem you see isn’t always where the problem starts.
A problem may show up in service, retention, CRM reporting, or an AI project. Its cause may sit in another team, system, rule, or decision. I follow those connections without losing sight of what the customer experiences.
A good diagnosis protects your next investment
Before you buy a platform, launch a program, or expand AI, a focused diagnostic shows what is known, what is still unclear, and which decision matters first.
AI readiness starts with the workflow
Useful AI needs a clear purpose, reliable inputs, clear owners, a usable workflow, human review, and a way to catch when something goes wrong.
How I work
The recommendation has to work in real life.
The goal is a decision people can understand, own, carry out, and improve as new evidence appears.
Follow the evidence
Separate what you can observe from what people assume. Be clear about what the evidence supports and where uncertainty remains.
Name the owner
Make it clear who decides, who does the work, who handles exceptions, and who owns the customer outcome.
Design for the work people actually do
Work with the real limits of teams, systems, incentives, data, and frontline behavior. A process diagram or technology launch will not change the work by itself.
Measure what changed
Choose the customer, adoption, workflow, and performance measures that should improve. Review the results and adjust.
System view
Follow the problem from the customer to the root cause.
I trace each problem through four connected layers. This keeps the customer experience visible while we look deeper into the work, technology, ownership, and results.
Customer reality
What customers are trying to do, where they get stuck, and what the problem costs them.
Frontline work
The decisions, handoffs, and service habits that shape what happens next.
Systems and signals
The CRM data, workflows, automation, and feedback people rely on to act.
Ownership and results
Who makes the decision, who owns the outcome, and how the team knows the change worked.
Working together
The best work starts with honesty on both sides.
A diagnostic works best when your team wants to understand the problem before choosing a solution and is willing to act on what we find.
Cadence Lab brings
A clear way to turn a messy problem into a decision
- One clear diagnostic question, not a broad consulting exercise.
- A view across customer friction, teams, workflows, systems, and ownership.
- A clear separation between facts, assumptions, limits, and decisions.
- A practical recommendation that shows what to do first and what can wait.
The engagement requires
The access and authority to get to the truth
- A customer or business problem worth solving.
- Access to the people, data, and examples around the work.
- A sponsor who can help teams make decisions together.
- A willingness to change ownership or workflows when the evidence points there.
Start with an honest fit check
Sometimes the honest answer is that I’m not the right fit.
Share what customers are experiencing, which people and systems are involved, and what needs to change. I’ll review it and tell you plainly whether Cadence Lab is a useful next step.
Start a fit check