AI Customer-Journey Use-Case Map
Map AI initiatives to attract, convert, close, and delight customers
- Difficulty
- Easy
- Time to result
- ~weeks to results
- Steps
- 5
- Confidence
- 96%
This model uses the modern customer journey as the organizing spine for AI strategy. Rather than beginning with vendors, model capabilities, or disconnected demonstrations, a team examines four stages: attracting an audience, converting interest into qualified demand, closing customers, and delighting or supporting them after purchase. At every stage, the team identifies costly, unscalable, or previously impossible customer outcomes and then matches AI capabilities to those use cases. Each proposed initiative receives an owner, an outcome metric, and a bounded pilot. The result is a balanced portfolio connected to how the business actually grows and retains customers, while technology remains subordinate to the use case it serves.
Origin
Extracted from Marketing Against The Grain, where the hosts organized HubSpot’s practical AI opportunities across attract, convert, close, and delight.
Core principles
- 01Organize AI around customer outcomes rather than technologies
- 02Audit the complete journey instead of one isolated department
- 03Give each initiative a defined journey stage
- 04Measure stage-specific business results
How to run it
- 1
Draw the journey
Represent the business journey as attract, convert, close, and delight. Define what success means for customers and the company at each stage.
Pro tip Use the company’s actual funnel definitions while preserving the four-stage logic.
Watch out Do not let departmental boundaries hide gaps between stages.
- 2
Inventory constrained outcomes
For every stage, list desirable outcomes that are too expensive, slow, generic, or difficult to provide today.
Pro tip Look for activities limited by human production or coverage capacity.
Watch out Avoid starting with a list of AI vendors.
- 3
Match capabilities to use cases
Connect each constrained outcome to capabilities such as generation, prediction, personalization, translation, or conversational interaction.
Pro tip Require a clear input, process, and customer-facing output.
Watch out Do not accept vague proposals to add AI without a defined use case.
- 4
Score and select pilots
Rank ideas by customer value, business impact, data readiness, feasibility, and risk. Select a manageable set rather than attempting every stage simultaneously.
Pro tip Choose at least one use case with a short feedback loop.
Watch out A balanced map does not require equal investment in all four stages.
- 5
Measure stage outcomes
Evaluate each pilot with the metric appropriate to its journey stage, then expand, revise, or stop it.
Pro tip Compare against the existing human or conventional-software baseline.
Watch out Do not use model activity or content volume as a substitute for business results.
In the wild
A SaaS team maps creative variation to attract, individualized email to convert, personalized video to close, and AI ticket resolution plus churn analysis to delight. It selects one pilot per stage and measures acquisition cost, conversion, win rate, and resolution quality.
→ The company gains a customer-centered AI roadmap rather than a miscellaneous tool stack.
Common mistakes
Organizing around vendors
Vendor categories fragment the strategy and encourage teams to buy technology before defining customer outcomes.
Stopping at acquisition
Ignoring close and delight opportunities leaves sales productivity, support coverage, and retention gains unexplored.
Using one metric everywhere
Every journey stage has different objectives, so a single generic AI metric cannot establish business value.
Is it for you?
Best for
It is best for go-to-market teams deciding where AI can improve acquisition, conversion, sales, and retention.
Not ideal for
It is not ideal for back-office AI projects with no meaningful relationship to the customer journey.
From the transcript
“the way that we are thinking about AI is basically across the modern customer journey from a track convert to close to light.”
“What we're doing here, and what we're gonna try to do today is obsess about the use cases.”
“how do I tactically do and use AI to attract customers, convert those customers into qualified leads, close them into customers, and then delight them…”
From the episode
Steal HubSpot’s Go To Market Strategy With Ai For 2025