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Director of Customer Experience

Design and optimize digital customer experiences

Enhances✓ Available Now

What You Do Today

Collaborate with digital product teams on website, app, and self-service experience design. Ensure digital channels meet customer expectations while achieving business goals like cost reduction and conversion.

AI That Applies

AI analyzes user session recordings, identifies UX patterns that cause abandonment, and recommends design improvements based on successful patterns across similar digital experiences.

Technologies

How It Works

The system ingests user session recordings as its primary data source. The analytics engine aggregates data across sources, applies statistical analysis to identify significant patterns and outliers, and presents the results through visualizations that highlight what needs attention. The output — design improvements based on successful patterns across similar digital experien — surfaces in the existing workflow where the practitioner can review and act on it.

What Changes

UX optimization becomes more precise with AI identifying specific interaction patterns that predict success or failure.

What Stays

Designing digital experiences that feel intuitive and human—not just efficient—requires understanding customer psychology and creative design thinking.

What To Do Next

This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.

1

Establish Your Baseline

Know where you are before you move

Before adopting AI tools for design and optimize digital customer experiences, understand your current state.

Map your current process: Document how design and optimize digital customer experiences works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: Designing digital experiences that feel intuitive and human—not just efficient—requires understanding customer psychology and creative design thinking. These are the boundaries AI won't cross.
Assess your data readiness: AI tools for this area need data to work. Check whether your organization has the historical data, integrations, and data quality to support FullStory tools.

Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.

2

Define Your Measures

What to track and how to calculate it

Time per cycle

How to calculate

Measure how long design and optimize digital customer experiences takes end-to-end today, then after AI adoption.

Why it matters

The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.

Quality of output

How to calculate

Track error rates, rework frequency, or stakeholder satisfaction scores before and after.

Why it matters

Speed without quality is just faster mistakes. Measure both.

When to check: Check after 30 days of consistent use, then quarterly.
The commitment: Give new tools at least 30 days before judging. The first week is always awkward.
What NOT to measure: Don't measure AI adoption rate as a KPI. Adoption follows value — if the tool helps, people use it.
3

Start These Conversations

Who to talk to and what to ask

your VP Customer Experience

How would we know if AI actually improved design and optimize digital customer experiences — what would we measure before and after?

They're setting the AI strategy for the service organization

your contact center technology lead

What would a pilot look like for AI in design and optimize digital customer experiences — smallest possible test that would tell us something?

They manage the platforms that AI tools plug into

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.