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IT Director

Support digital retailing and customer-facing technology

Automates✓ Available Now

What You Do Today

Manage the technology stack for online sales—website platform, digital retailing tools, chat systems, and mobile apps. Ensure seamless integration between online and in-store technology experiences.

AI That Applies

AI monitors digital platform performance, identifies user experience issues from analytics data, and optimizes page load times and conversion funnel flow.

Technologies

How It Works

The system ingests digital platform performance 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 results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.

What Changes

Platform performance monitoring and optimization become more automated and data-driven.

What Stays

Choosing the right digital platforms, managing multiple vendor relationships, and ensuring technology serves the dealership's sales process rather than dictating it require strategic technology 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 support digital retailing and customer-facing technology, understand your current state.

Map your current process: Document how support digital retailing and customer-facing technology works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: Choosing the right digital platforms, managing multiple vendor relationships, and ensuring technology serves the dealership's sales process rather than dictating it require strategic technology 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 Dealer.com 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 support digital retailing and customer-facing technology 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 CIO or VP IT

What's our current capability gap in support digital retailing and customer-facing technology — and is it a people problem, a tools problem, or a process problem?

They're prioritizing which IT functions to automate

your cybersecurity lead

How would we know if AI actually improved support digital retailing and customer-facing technology — what would we measure before and after?

AI tools create new attack surfaces and new defense capabilities

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.