At its core, the Lexer software takes in data from multiple sources (ex. Mailchimp, Shopify, Klaviyo, etc) to build a complete customer profile for people in retail marketing by focusing on a snapshot of singular data points, like average order value or date of last purchase. When it comes to demonstrating insights based on a specific event, like buying a top as part of a purchase made on Black Friday in 2023, the software breaks.
This project shifted the fundamental data structure in the backend and needed the overall workflow to account for this technical change without alienating users to how the flow previously worked.
Given the short timeline, there was also no room to create completely new componentry for the interface even though the user feedback asked for better data visualisation methods. This limitation also meant any UI elements that were not crucial to the feature to be usable or caused too much excessive dev effort would be removed.
SOLUTION
- Ask for help from the developers to understand the backend changes
- Study technical documentation and common interface patterns from competitors
- Assess and audited the existing workflow and design patterns for continuity opportunities
- Scour the existing design system for ways to update the feature with limited new component creation
- Set a minimum acceptable and usable workflow with clear indications of stretch goals