Redesign B2B - Ecommerce Product
Over view
After the application of POC Products Telio has proven the ability "Product Market Fit".
My team began to collect data to improve their experiences based on behavior based on their behavior on the application.
Case study is part of that phase. The goal is that I like the interface to help customers find and browse better products.
my role
UI/UX Designer - User Research, Interaction, Visual design, Prototyping & Testing
timeline
3 months
DeSIGN team
Thanh Pham
Tam Do
Quang Vu
Collected purchase behavior data revealed: While checkout flows worked, adding items to cart showed clear optimization opportunities for faster interactions.
User characteristics
Open a small store at home
Non Tech-savvy
Average age: 42
Daily multiple-steps ordering process from checking prices, inventory, promotions...
Unique method to identify SKU during ordering process
Each store sellings 300+ differents SKUs which purchased from 40+ vendors.
CleverTap behavioral data revealed unique B2B user patterns, especially among older demographics (avg. age 42+)
Product search
Overwhelming search results caused cognitive overload and poor scannability
Browse category
We identified UI improvement opportunities that maintain user focus while enhancing product discovery features
Key problem
What does the system say about our user
Data-driven analysis of user interactions with search/browse components revealed optimization opportunities
Tool
CleverTab
First click testing
Customers often add a certain product to their shopping carts through the approval through category rather than the searching behavior
How users interact with search results?
The conversion rate of the search results
Customers only need the first 6 results to find the product they want. Among them, the first 2 suggestions accounted for 70%
This is also in accordance with a popular UX law called Miller's Law
The behavior "Add to cart"
When the proposal list does not have the product you want to find. This tends to be that the product is in a different category than the products displayed in the search results
The factor of browse behavior
Collect information from users by observing how they interact with the app to order and perform personal/group interviews to see the common model in their behavior.
Tool
Observing, Interview, Focus group
Users identify products
Users often scan through the image first to identify the product and then read the product name to confirm
Product name - Image size
The goal is how to make the biggest image possible while ensuring the user still read the full name of the product
The length needed to display ~95% of the names of the products is 67 characters
Information is meaningful for the user's daily work
Help user daily work faster even without searching
Purchase decision
During the user research process, we have found some of regular models to make purchase decision. We tried to match it with system data to find out meaningful information
By taking advantage of the user's data, we can provide meaningful information to each specific user
How to solve the problem by design
Bring data from the system and customers to become a solution
