KYLIGENCE ZEN METRIC STORE

A Data Tool for Everyone in SMBs

OVERVIEW
The 0-1 launch of an end-to-end data analytics tool for SMB
TYPE
Web, 0-1, SaaS, Data Service
DURATION
01/2022 - 12/2023

TEAMProduct Manager 3
UX Designer 4
Graphic Designer 1
Product Marketing 2
Engineer 15

MY ROLE
Lead UX Designer
KEY CONTRIBUTIONDesign principles
0-1 design framework
Main feature design
Usability test
UX measurement
Design pattern library

OUTCOME40+ new customer subscriptions within 6 months, 70%+ attracted through the self-serve trial

The company seeks to scale quickly by offering a Metric Store to SMBs

OPPORTUNITYWe’ve assisted many large-scale enterprises in building their metric stores. However, small to medium-sized businesses (SMBs) typically can't afford this luxury. As data-driven decision-making becomes increasingly crucial, and with our expertise in this area, we can offer SMBs an affordable standardized metric store product.

BUSINESS GOAL

The 0–1 process consists of 3 stages

PROCESS

THE PROBLEM SPACEThrough interviews with target audiences and industry experts, I collaborate with the product managers to clarify the problems and solutions.

USER ROLES

USER JOURNEY MAP

THE DESIGN
Create Metric
Challenge: Balance business users VS experts Learn more

Provide three ways to create metric, tailed to different roles

Retrieve Metric

Efficient to retrieve metrics using catalog or tags, and determine their credibity

Analyze Metric - Root Cause Analysis
Challenge: Make it easier for business users to understand Learn more

With one-click to uncover the fundamental reason for abnormal fluctuation

Dashboard

Easy-to-use through “add metrics in bulk” and “drag&drop”

DATA-DRIVEN ITERATION

Challenge: Balance trial users VS long-term users

*I have omitted and obfuscated the data due to confidentiality reasons.

As mentioned, we use a self-serve trial as the primary way for potential customers—attracted through marketing campaigns—to explore and evaluate the product. In this process, the users aim to use their own data to navigate through the entire user journey.

However…

👀 Data Observation - Trial users drop outMany of them drop out early, making the evaluation process incomplete or invalid.
🤔 Problem - Why drop out?

Too many steps
Creating data models is overwhelming

I analyze the problem using flow analysis and user interviews.

💡 Solution - How to keep them Streamline the journey:

Provide a more prominent entry point
Provide a simplified version of creating data model
Provide a shortcut to create metric from data model

✌️ Outcome - Completion rate +73%
Meanwhile, the completion rate of “Create Data Model” rises by 60% with the simplified design.

OUTCOME

WHAT PEOPLE SAY

LESSONS LEARNT

Pattern libraryEnsure consistency when multiple designers are contributing to the project

Get resource fixed
Ensure UX issues get fixed within an aggressive timeline

Measurement system
Measure user experience consistently