SmartIntellect

Redesigning a CDP for cross border merchants

B2B

B2B

SaaS Product Design

SaaS Product Design

Industry

Industry

Cross-Border E-commerce

Cross-Border E-commerce

My Role

My Role

Product Designer

Product Designer

Company

Company

SHOPLINE in JOYY Inc

SHOPLINE in JOYY Inc

Tools

Tools

Figma, Jira, Notion, Zoom

Figma, Jira, Notion, Zoom

Timeline

Timeline

2024.06 - 2024.09 (3 months)

2024.06 - 2024.09 (3 months)

Business Impact

Business Impact

40% Paid Conversion Rate

40% Paid Conversion Rate

Project Type

B2B Product Version Iteration

Company

SHOPLINE in JOYY Inc

Role

UX Designer

Industry

Cross-Border E-commerce

Tools

Figma, Jira, Notion, Zoom

Timeline

2024.06 - 2024.09 (3 months)

SmartIntellect is a CDP for e-commerce merchants using SHOPLINE, an all-in-one commerce SaaS platform, that connects and unifies multi-channel customer data to build comprehensive profiles, enabling actionable insights and more targeted marketing campaigns.

SmartIntellect is a data-driven Customer Data Platform (CDP) product that powers e-commerce merchants using SHOPLINE(An all-in-one commerce SaaS platform). It enables merchants to build omni-channel customer profiles, and gain actionable insights by analyzing behavior, preferences, and purchase history, execute targeted marketing.

SmartIntellect is a CDP built for e-commerce merchants using SHOPLINE (an all-in-one commerce SaaS platform). It helps merchants connect and unify customer data from multiple channels—such as their website, Google, and social media—to build complete customer profiles. With these profiles, they can gain actionable insights into customer behavior, purchase history, and ad performance, and run more targeted marketing campaigns.

Overview

The Problem

The product launched its MVP, but people weren’t willing to pay for it

SmartIntellect was built to help merchants drive sales and conversions more efficiently. It launched its MVP and passed basic market validation. But even though most merchants saw its value, very few were actually willing to pay for it.

Why it happened

There are three factors that design can help improve

In research, most merchants felt the product was difficult to use, missing essential features, and visually inconsistent, leading to high learning costs and low operational efficiency.

Key factors merchants consider when subscribing to the CDP product

What I did

Streamlined workflows, added new features, and rebuilt the design system

After identifying these needs, I conducted competitive analysis and mapped design strategies. I streamlined workflows and prompts to lower the learning curve, introduced new features like dashboard to expand product value, and rebuilt an new design system with design guidelines and reusable components.

Impact

Redesigned Version Boosted Merchant Paid Conversions by 40%

Merchant satisfaction reached 80% for usability and 79% for completeness, while tasks such as creating segments and comparing data were completed in nearly half the time.

7 of 9 trial participants showed strong interest, and 80% of potential merchants expressed willingness to pay — up from only 3 before.

12%

Feature Satisfaction

(Design Value)

48%

Task Completion Time

(Design Value)

40%

Paid Conversion Rate
(Business Impact)

Archetype Mapping

Business Operators and Data Analysts

To better understand how users work with our product, I identified Business Operators and Data Analysts as the core target users, and focused my research on their key tasks, needs, and pain points.

Core target users

By analyzing the tasks and needs of these two key roles across different scenarios and integrating previous research findings, I identified two key scenarios: Customer Management and View Analytics Reports.

Scenario Analysis I

In Customer Management scenario

Users require smooth, efficient flows and clear feedback

In the Customer Management scenario, the business operator is the primary user. They focus on connecting customer data to SmartIntellect, as well as viewing, managing, and editing that data.

User journey map: Customer Management

Problem I

The current segmentation workflow is too time-consuming for operators

Although the current process allows them to fulfill the requirement of creating new customer segments, it is widely regarded as overly cumbersome. Operators often need to repeatedly make selections, leading to a prolonged process.

Current segmentation workflow

The current rule layout creates high cognitive load and slows down review for operators

All rules are listed in creation order, regardless of type. When editing a segment, operators must review each previously created rule to check for updates or missing logic. Over time, older rules become harder to locate and understand, increasing cognitive load and slowing down the workflow.

Current page display

As a result, users struggle to quickly locate, compare, or edit specific rules. The lack of visual hierarchy and grouping not only impacts readability, but also increases the time needed to complete segmentation tasks.

Solution I

Simplified segmentation flow for better clarity and usability

I redesigned the segmentation workflow to reduce friction and improve clarity—removing the rule selection step, introducing a vertical layout with grouped conditions, and applying conditional displays to streamline the interface. The result: a simpler, more readable process that helps operators complete tasks faster.

/ 01

Fewer steps help operators complete tasks faster

Eliminate the Segment Rule selection box and introduced a vertical layout that displays rules directly on the page. Operators can click “Add this sort” to configure rules inline.

/ 02

Logical grouping to improve readability for operators

Rules within the same category will be connected using “and”, with a nested card design to ensure readability.

/ 03

Use progressive disclosure to reduce friction in event setup

Show “Add property” only when the selected event supports properties and has available slots to reduce unnecessary actions.

Scenario Analysis II

In View Analytics Reports scenario

Users require flexibility, clarity, and efficient cross-view analysis

In the View Analytics Reports scenario, the data analyst takes the lead. They are responsible for creating various reports based on business needs and extracting key data from these reports to support business decisions.

User journey map: View Analytics Reports

Problem II

No centralized workspace for data analysts to compare reports

Although data analysts can conduct analysis using the current system, data is scattered across multiple reports and real-time feedback is lacking—making the process inefficient and delaying decision-making.


Every time I want to compare charts, I have to click back and forth across multiple pages.

Solution II

Designing a dashboard MVP for data analysts to address their most pressing pain points

Based on user needs and competitive insights, I led the design of the Dashboard MVP to help data analysts organize and analyze key charts more clearly and flexibly.

Under tight timelines and limited resources, I made strategic design trade-offs—removing complexity and prioritizing the most critical pain points. The result was a scalable and efficient workspace that addressed user needs while laying a foundation for future system growth.

Design System

Designed 23 core UI components for the product

I led the creation of the product’s initial design component library, modularizing common UI elements and interaction patterns. The final output included 23 core UI components along with corresponding usage guidelines.

Designed 23 core UI components