ATLASSIAN • B2B ENTERPRISE • 2025
Redesigning Jira Smart Defaults to fix 18% enterprise adoption
TIMELINE
2 months
ROLE
Product Designer (Me!)
TEAM
Product Owner
Six Engineers
Two QAs
Technical writer
TL;DR
Low adoption (18% overall, 52% in Enterprise) and high support friction revealed that users struggled with complex JQL syntax buried at the bottom of the side panel.
To solve this, I redesigned Smart Defaults into a dedicated modal featuring 1-click presets and a guided 3-step wizard, cutting setup time to seconds and converting 80% of research findings directly into shipped backlog items.
SOLUTION
Replacing complex JQL syntax with a guided modal
The core solution is a completely redesigned experience for Smart Defaults – moving the feature to a dedicated modal and replacing complex JQL syntax with an intuitive, self-service interface.
The core pillars of the new solution are:
Moving the entry point from the side panel to a dedicated modal window
This creates a spacious, clean workspace while maintaining a clear call-to-action button with an active rule counter in the issue context.
Introducing interactive 1-click presets for popular automations
Clickable cards for frequent rules (such as assigning reporters or setting due dates in business days) allow users to activate automations instantly without learning syntax or reading documentation.
Designing a guided 3-step selector wizard to replace manual coding
The step-by-step builder leads users through target fields, data sources, and source fields, turning complex JQL writing into simple dropdown choices.
OVERVIEW
Powering 1,300+ enterprise clients with automated Jira templates
The Issue Templates for Jira Cloud application (Deviniti) is a leading automation app on the Atlassian Marketplace with Cloud Fortified status. The product powers 1,342 paid instances, serving global enterprise brands (>1,000 users) such as WarnerBros, Mercedes, and JLL. The app automates repetitive issue and sub-task structures in Jira.
Smart Defaults as our core competitive differentiator
Our main competitive differentiator on the Atlassian Marketplace is Smart Defaults. An engine that calculates and populates field values dynamically, such as dates accounting for business days, reporter assignment, or copying data from Parent/Epic issues.
Issue Templates for Jira
DEVINITI
PROBLEM
18% overall adoption and high support friction in enterprise accounts
Product analytics gave us a direct reason to launch qualitative research by revealing a critical adoption problem: overall feature adoption was only 18% (237 out of 1,342 instances), and in the key Enterprise segment (>1,000 users), adoption reached 52% against a 70% business target.
Supporting qualitative signals from support tickets and surveys
These quantitative findings were backed by supporting signals from across the organization:
High support ticket volume: Customers frequently complained about configuration difficulties, syntax errors, and cryptic system messages like “No value or inconclusive”.
In-app Survicate survey results. Confirmed that users intentionally bypassed the feature, viewing it as complex and requiring extensive documentation.
INITIAL FINDINGS
Hidden interface, syntax complexity and heavy research procedures
After evaluating the feature within the interface, I formulated my first hypotheses: the feature was buried at the bottom of the side panel, lacked live hints or validation, and requiring users to write JQL syntax from memory could lead to rapid drop-offs on their very first try.
BEFORE
Bottlenecks in the existing research process
I wanted to quickly validate these hypotheses through user interviews, but the company's existing research process posed a major hurdle. Previous research initiatives had a very broad scope, making them infrequent.
Each study ended with a massive report and a mountain of insights the team couldn't digest efficiently – causing many valuable takeaways to get lost in archives.
GOALS
Raising enterprise adoption to 70% and slashing time-to-value
I aligned user needs with business goals:
User goal
Self-serve automated templates to eliminate manual work and accelerate team execution.
Business goal
Increase adoption in the Enterprise segment (>1k users) from 52% to 70% and shorten Time-to-Value.
North Star Metric and success evaluation
In-Product Completed Journey Rate. Percentage of organizations with at least 1 active Smart Defaults rule on their templates.
DESIGN PROCESS
Uncovering 4 core usability blockers through 30-minute live sessions
Instead of a long research project, I conducted short, 30-minute live sessions. Participants were tasked with configuring automatic date calculations (accounting for business days) and reporter assignment on their own Jira instance using a selected template.
Task execution observations and user struggles
Participants struggled significantly. Some were completely unaware that the feature existed at the bottom of the side panel. Others got lost when typing manual syntax (e.g., ) or hit cryptic system errors.
MICRO-DISCOVERY
Establishing a lightweight, agile research framework
After the successful research experiment, I shared these learnings with other designers on the team. Based on these experiences, I established the principles for the Micro-Discovery framework – a lightweight, agile research process for the team.
Core principles of Micro-Discovery:
Narrow research scope – Focusing on a single, specific feature rather than an entire module.
Fast operational cycle – 30-minute sessions with the entire study completed within 40 working hours from recruitment to recommendations.
Rapid synthesis in Miro – Immediately mapping insights on a board after each session allowing the team to spot recurring patterns instantly and feed the knowledge base.
Actionable backlog – Prioritizing items in Confluence and pushing recommendations directly as actionable tasks to JPD and Jira backlogs.
Collaborative workshop with engineering to map flows and estimate effort
After analyzing the research findings, I facilitated a workshop on a shared board with the product team. Based on the gathered materials, we analyzed the identified problems and co-created a solution that was UX-mature and realistic to implement technically.
Defining PostHog event analytics for conversion funnels
Together with the Product Owner and Dev Lead, I analyzed key interaction points in the new flow, and we defined a streamlined set of PostHog events: modal view, field addition with name and type parameters and successful rule save. This provided developers with a clear specification to implement event tracking quickly.
DELIVERY & QA
Figma cleanup, Storybook handoff, and QA testing
I began by cleaning up Figma files – organizing layers, component variants, and interaction states. Next, working with the delivery team, we identified which elements required new components and which could leverage existing library variants — after which they were built and documented in Storybook.
Product documentation updates with Technical Writing
I prepared a full specification for views and interaction states, allowing the Technical Writer to seamlessly update our product documentation.
Staging environment verification and event tracking QA
Working directly with QA on the staging environment, I verified interface behavior and ensured event tracking fired correctly in PostHog before releasing to production.
OUTCOME
Seconds-fast setup and pushing 80% of research insights into production
Self-service interface addressing business metrics
The new interface guides users step-by-step, reducing setup time to seconds. The redesign directly addressed low adoption (18% overall, 52% in Enterprise vs. 70% target), while event tracking in PostHog / GA4 enables precise conversion funnel measurement.
Research process breakthrough
Thanks to the Micro-Discovery framework, 80% of research recommendations were pushed directly into the JPD/Jira backlog as implemented tasks compared to previous reports where most insights got lost in Dovetail.
REFLECTION
Defending the modal shift and future visual improvements
What I would do differently
I would add a live structure preview inside the modal window so administrators could instantly see the generated field values on a live issue.
What I firmly defended
Moving from the side panel to a dedicated modal
Creating a proper workspace and eliminating side-panel clutter.
Preserving backward compatibility
Protecting paying enterprise clients from breaking their existing, active templates.
LET’S TALK
Happy to walk through the decisions this write-up compresses into a paragraph each.
