Ella Zhou

Contact

Alibaba

AI User Journey Analysis Tool

B2B Internal Tool / AI Product Design / End-To-End prototyping

2025.05 - 2025.08

An AI user journey analysis tool, helping product designers to improve journey generation accuracy to 85% and reducing journey creation and analysis time by 70%

company

Ele.me

Ele.me is Alibaba’s key local services ecosystem. It provides instant food delivery and last-mile logistics within cities, serving millions of users every day.

Team

AI Design Team (Under Logistics System Design Team)

1 Sn. Design Team Lead, 2 Technical Consultants, Ella

Importance of User Journey

On average, Ele.me designers spend 2 - 4 weeks creating journey maps to reconstruct behavior paths and identify issues. This tool streamlines the process, cutting time, cost, and effort while accelerating Ele.me’s design output.

Problems

At Ele.me, the effectiveness of journey mapping is hindered by incomplete or unreliable user behavior data and inconsistent practices, making it difficult for designers to generate accurate insights and guide design decisions

1. Data Collection Problem

low data quality & time-consuming

2. Journey Creation Problem

low journey quality

Goal

Create an end-to-end AI user journey analysis tool that：

Automate and standardize user behavior data collection

Automate journey map creation with consistency and high-quality insights

How might we create this tool:

User Behavior Data Collection

Automatic Screenshots-to-Journey Map

1. User Behavior Data Collection

INITIal proposal

Create a company-specific desktop plugin that integrates an internal auto-screenshot tool to automatically capture user behaviors, alongside a system that records raw user data at the system, browser, and page levels.

problems

Time-consuming

Resource-intensive

Redundant effort

Current method

Leverage open-source screenshot tools and the internal Analytics & Event Management (AEM) system to capture user data—including images and behavior data—at both browser and page levels.

pros

Time-saving

Easy to test

Resource-efficient

Future blueprint

Replace the open-source screenshot tool with an internally developed one, improving AEM system to add the capture of raw data at both system and real-life levels.

improvements

Data safety

Targeted features

2. Automatic Screenshots-to-Journey Map

1. Single User Journey Mapping

Automatically generate individual user journey

2. Journey Integration

Aggregate multiple user journeys

3. User Interface

UI design for the tool

2.1 Single User Journey Mapping

standards

90%

Image Consistency

80%

Image Completeness

70%

Title Accuracy

Model Iteration 1 | One multimodal model to handle all tasks

Model Iteration 2 | Model Collaboration

Final performance

> 85%

Image Consistency

> 90%

Image Completeness

> 80%

Title Accuracy

2.2 Journey Integration

How

Analyzed the logic and process of integrating user journeys, distilled two key elements—branching and unification—and mapped the critical steps across phases.

Model Iteration 1 | Define the AI’s task & Data Input

Model Iteration 2 | Add Task Logic & Structure

2.3 User Interface

Design the user interface for an AI journey tool from scratch based on Alibaba's Ant Design System.

Data input

Image upload

iteration 1

Add error feedback

add retry shortcut

iteration 2

iteration 3

generate & Pause journey map

Iteration 1

After

Journey Visualization

Replacing icons with text labels for frequently-used features, improving clickability and ease of use

Adding links to

reduce cognitive

load.

Manual edit process

Level 1

Level 2

Level 3

Level 4

Deletion is hierarchical: if a Level 1 item is deleted, all its associated Level 2, Level 3, and Level 4 items are also removed.

Additional Contribution

1. Vibe Coding

Integrate AI workflows and ML models, allow user input via the UI, and visualize the output on the front-end

2. AI Problem Analysis

Use AI to connect insights across the user journey and help designers identify problems and opportunities more efficiently

AI single-journey workflow

Image Analysis Model

Model for linking journeys

Model for integrating journeys

User behavior data

Code

AI workflows & models

User input via the UI, store user input

Journey visualization on the frontend

Call model API

Save model output

vibe coding

AI problem analysis

standards

Blue print

Utilized AI workflows and different internal resources to evaluate problems in line with design standards.

What I learned

What if no single AI model can produce the ideal outcome on its own?

Break down the task and analyze its structure, assigning subtasks to different models according to their strengths.

Combine the outputs of specialized models through a workflow to achieve the overall task.

It is common that when designing with AI, its capabilities may not reach the state we want. How should this be addressed?

Define standards, test and iterate to meet them, and establish a future vision for continued progress.

How to address design challenges arising from standards, creativity, or business logic constraints?

Explore methods by leveraging company resources alongside self-directed research and exploration.

Ella Zhou

Project

Resume

Contact

AI User Journey Analysis Tool

B2B Internal Tool / AI Product Design / End-To-End Prototyping

2025 Summer

An AI user journey analysis tool, helping product designers to improve journey generation accuracy to 85% and reducing journey creation and analysis time by 70%.

company

Ele.me

Ele.me supports Alibaba’s key local services ecosystem. It provides instant food delivery and last-mile logistics within cities, serving millions of users every day.

Team

2 AI Design Team (Under Logistics System Design Team)

1 Sn. Design Team Lead, 2 Technical Consultants, Ella

Design tools and platforms to enhance designer’s working efficiency.

Importance of User Journey

Problem

Data Collection Problem

low data quality & time-consuming

Journey Creation Problem

low journey quality

Solution

Create an end-to-end AI user journey analysis tool that：

Automate and standardize data collection of user behavior

Automate journey map creation with consistency and high-quality insights

Part 1 — Automate data collection

INITIal proposal

problems

Time-consuming

Resource-intensive

Redundancy-prone

Current method

Leverage open-source screenshot tools and the internal Analytics & Event Management (AEM) system to capture user data—including images and behavior data—at both browser and page levels.

pros

Time-saving

Easy to test

Resource-efficient

Future blueprint

Replace the open-source screenshot tool with an internally developed one, improving AEM system to allow the capturing of raw data at both system and real-life levels.

improvements

Better data safety

Targeted features

Part 2 — Automatic Screenshots-to-Journey Map

01. Journey Mapping for Single User

🤔

How can we design an AI tool when its final performance and potential are still unknown?

define Desired standards

90%

Image Consistency

80%

Image Completeness

70%

Title Accuracy

Explore Internal tools & AI prototyping

Used Alibaba’s internal AI models to prototype the AI journey-mapping workflow.

🤔

How can I, as a designer, contribute to improving and elevating the quality of AI tools?

I translated user needs and design thinking into actionable conditions for the underlying models.

🙋‍♀️

design thinking into AI improvement

AI tool improvement process

Final performance

> 85%

Image Consistency

> 90%

Image Completeness

> 80%

Title Accuracy

02. Journey Integration for Multiple Users

🤔

AI models can’t grasp how designers integrate multiple journeys. They rely on algorithms. How should we translate design intuition into learnable system logic?