The problem: customer experience is fragmented and opaque

Customer journeys unfold across disconnected systems. Whether it’s IVR menus, AI agents, employee desktops, or back-office workflows, each channel captures data independently, but the overall experience often remains invisible.

That means customer effort builds in places teams can’t easily see:

• Repeating information after escalation
• Restarting conversations after transfers
• Re-authenticating across touchpoints

Traditional reporting focuses on containment and handling time, while surveys reach too few customers to reflect the full journey. As automation expands, this fragmentation makes friction harder to diagnose.

You can’t improve what you can’t measure

Customer experience improvement starts with knowing where effort is introduced and why. Without interaction-level measurement, teams struggle to determine:

• Where does automation break down?
• Which handoffs increase friction?
• What does the journey feel like from the customer’s perspective?

Metrics focused only on deflection or containment may show short-term gains while masking rising customer effort elsewhere in the journey. CX Diagnostics provides a shared source of truth grounded in real conversations so organizations can align priorities more quickly and make confident trade-offs. 

What is CX Diagnostics?

CX Diagnostics is a generative AI-powered analytics solution that connects fragmented customer interactions into a single journey, turning conversations into actionable insight.

Traditional customer experience analytics platforms report what happened within a system, but rarely explain how customers experienced the journey across systems.

In contrast, CX Diagnostics operates at scale, so insight remains consistent as volumes grow and new channels are introduced. Teams gain a shared source of truth for experience performance, enabling faster alignment across CX, operations, and technology.

• End-to-End Effort: Customer journeys are analyzed from start to resolution, revealing how effort accumulates across channels, handoffs, and escalations.
• Automation Effectiveness: Performance is measured across both AI agents and human agents, showing where automation helps and where it creates friction.
• Measure Journey Outcomes: Interaction-level visibility highlights where experiences break down, stall, or resolve efficiently.
• Root Cause Insights: AI-driven analysis surfaces the drivers behind outcomes, connecting behavior, language, and journey structure to results.

Measure experience the way customers live it: from start to resolution

Customers experience service as a continuous flow that may include self-service, escalation to an agent, transfers between teams, or follow-up interactions across channels.

CX Diagnostics stitches these interactions together from start to resolution, revealing how effort accumulates and where handoffs succeed or fail.

Customer Effort Score, reimagined with AI

An AI-powered Customer Effort Score replaces surveys with continuous, interaction-level measurement.

Traditional CES programs rely on post-interaction surveys that reach a small percentage of customers and often miss critical moments. CX Diagnostics analyzes language, journey structure, and behavioral signals to infer effort directly from real conversations.

This approach allows organizations to:

• Track effort over time
• Detect rising friction early
• Tie effort reduction to loyalty and retention

Lower effort is one of the strongest predictors of customer loyalty, and CX Diagnostics makes it measurable at scale.

Turn conversations into clear, actionable insight

CX Diagnostics transforms conversational data into insight teams can act on immediately, including:

• Where customers struggle most
• Which interactions should (or shouldn’t) be automated
• How effective AI agents and human agents truly are
• Where time, cost, and effort are being wasted

With these insights, customer experience leaders can prioritize roadmap investments and product teams can refine automation with evidence rather than intuition.

Beyond the experience teams, finance and operations leaders can understand the true cost of friction, including repeat contacts, extended handle times, and unnecessary escalations. Identifying where effort compounds across journeys helps organizations reduce cost-to-serve without degrading the experience.

Designed for real-world complexity

Enterprise customer service environments operate across voice and text, with interruptions, transfers, and exceptions as the norm. CX Diagnostics supports analysis across any voice or text interaction, measuring experience as it actually happens.

Reflecting real-world behavior turns AI in customer experience into a practical tool for improvement rather than a theoretical model based on ideal conditions.

From insight to action — fast

CX Diagnostics functions as both an entry point for fast strategic insight and a durable capability for long-term improvement. Organizations can begin with a fast-track assessment to identify high-impact opportunities in a short timeframe. From there, ongoing analytics provide continuous visibility as automation scales and journeys change.

Built to power better automation, better agents, and better outcomes

CX Diagnostics connects insight directly back into the broader customer service ecosystem. As customer behavior changes and new intents emerge, insight from real conversations highlights where journeys drift from expectations. 

Teams can adjust automation, update agent guidance, and refine workflows based on evidence rather than lagging indicators. This creates a continuous feedback loop where automation, agents, and customer experience improve together.

A smarter way to improve customer experience

CX Diagnostics helps enterprises reduce friction, optimize automation, and improve outcomes at scale. Learn how AI can improve customer experience in practice with end-to-end journey visibility and AI-powered effort measurement. 

Talk to an expert to see CX diagnostics in action.

Frequently asked questions about CX Diagnostics.

How is CX Diagnostics different from traditional contact center analytics?

Traditional analytics focus on isolated metrics and channels. CX Diagnostics observes interactions end-to-end, measuring effort and performance across the entire journey.

Does CX Diagnostics replace customer surveys or Customer Effort Score (CES) programs?

CX Diagnostics can complement or replace surveys by continuously measuring effort across all interactions, not just the small percentage captured by surveys.

Is CX Diagnostics only used with AI agents? 

No. CX Diagnostics analyzes journeys that include AI agents, human agents, and handoffs across channels.

How do AI Customer Effort Scores work in CX Diagnostics? 

AI analyzes conversation patterns, language, and journey behavior to infer effort at scale, delivering a continuous, interaction-level view of customer effort across every customer journey.