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VP of Customer Experience

Digital Experience Optimization

Enhances✓ Available Now

What You Do Today

Optimize the digital customer experience — website, mobile app, portal, and digital communications. You're working with product and engineering to ensure digital touchpoints are intuitive, efficient, and aligned with the overall CX strategy.

AI That Applies

AI-powered digital experience analytics that identify friction in digital journeys, personalize experiences based on customer behavior, and A/B test experience variations at scale.

Technologies

How It Works

The system ingests customer behavior as its primary data source. Machine learning models identify the patterns in historical data that most strongly predict the target outcome, then apply those patterns to score new inputs. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context. The experience vision.

What Changes

Digital optimization becomes continuous and automated. The AI identifies that mobile users drop off at the document upload step and suggests a simplified flow that tests 40% better.

What Stays

The experience vision. Deciding what the digital experience should feel like, how it integrates with human touchpoints, and where digital should hand off to a person requires CX design expertise.

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 digital experience optimization, understand your current state.

Map your current process: Document how digital experience optimization works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: The experience vision. 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 Behavioral Analytics 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 digital experience optimization 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 board chair or lead independent director

What data do we already have that could improve how we handle digital experience optimization?

They shape expectations for how AI appears in governance

your CTO or CIO

Who on our team has the deepest experience with digital experience optimization, and what tools are they already using?

They own the technology infrastructure that enables AI adoption

a peer executive at a company further along on AI adoption

If we brought in AI tools for digital experience optimization, what would we measure before and after to know it actually helped?

Their lessons learned are worth more than any consultant's framework

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.