First Time Experience, Astrato
Overview
A project to improve retention for Astrato users that opt out of white-glove sessions. This initiative also allowed us to assess the effectiveness of our visual-first approach.
Outcome
Developed a self-service flow for first-time users, providing onboarding guidance, and useful video content to quickly demonstrate value. We included service shortcuts, and tracked critical event metrics, validating a data-first approach.
Role
Head of Product Design
Leadership
UX/UI/Research
User Testing
Worked with
C-Suite
Sr Product Designer
Project Managers
Developers
BI Developers
Marketing
Brand
Astrato, by Vizlib
Initiate
Problem Statement
The project's core challenge was a critical user retention gap for Astrato. The data showed a disparity in product usage between Corporate and Social users, which was potentially caused by a lack of personalised onboarding for Social users.
The project presented a unique opportunity to challenge the founders' "visual-first" vision, which prioritised data visualisations over what users truly needed to get started.
Corporate user activity.
Social user activity.
Hypothesis
We hypothesised that we could increase user retention with a self-service experience for those who decline personalised onboarding. We believed a data-first approach, which allows users to immediately connect with their own data, would lead to higher conversion rates and be more effective than our existing visual-first vision.
Project Objectives
Increase user retention through a self-service flow: Review and optimise existing product tours, and introduce content to guide users through key features.
Determine the optimal user journey (visual-first or data-first) based on persona: Connect users to the appropriate service quickly to achieve their goals, based on their data analytics background.
Reduce time to complete key tasks: Remove unnecessary steps and clutter from the user interface.
Gain insights to inform future product development changes: Create event triggers to gather quantitative data on user activity, including sign-up, data connections, workbooks and visualisations.
Discover
Zero to Hero
An intended user journey map was created to serve the ‘Expert’ persona, who has strong data analysis skills.
The map focused on a data-first approach, prioritising key steps such as data connection, exploration, visualisation, and workbook sharing.
It also functioned as a feedback board to gather user insights, identify quick fixes, and prioritise new features like an enhanced table view.
This journey was visually represented as a swimlane diagram for a clear overview of the user's intended experience.
User Feedback
Feedback and insights were gathered from monitored and unmonitored user testing sessions, workshops with internal and external BI experts and Astrato Galaxy (external community).
This is all fed into Glean.ly, our scalable research repository, creating a score system to help inform priority and design decisions. This feedback wasn't just a list of feature requests; it was a clear signal that users needed a data-first approach to even get started.
EVIDENCE SCORE 10
Create tutorials/animation/step-by-step for Joins in the DVE
EVIDENCE SCORE 8
Help users to add/understand data in their visualisations.
Personas Summary
‘Joe’ the ‘Expert/Influencer’
A DataViz wizard and passionate about great storytelling. Has 10 years of experience on the job as a BI Developer.
“I deliver insights to senior stakeholders making business decisions”
Evaluates the data.
Cleans up the data.
Maintenance and updating workbooks.
‘Juste’ the ‘Business User’
A charismatic & confident Marketing Manager with 20 years of experience who uses insights to drive performance.
“I use insight to drive performance”
Minimise time to insight.
Understand users and trends.
Report on business targets, performance and KPIs.
Ideate
Address existing issues: The team first addressed challenges such as excessive Intercom messages, inconsistent product tours, and lengthy marketing surveys.
Explore new starting points: In collaboration with stakeholders, a new user experience was explored, considering options like start by defining a data view (data-first), or start with a workbook (visual-first).
Research competitor flows: The team researched how competitors like GoodData, Motion, and GRID handled video tutorials and animated walkthroughs to guide new users.
Develop a high-level flow: A new flow that Integrates all the research, and ideas to guide the project's next steps based on user goals and needs.
Define
Self-Service Flow
Flow finalisation: A new self-service flow was finalised with stakeholders, integrating three distinct getting-started services, a marketing survey, video content triggers, and an optimised Intercom help chatbox.
Marketing survey: To gather insights on the types of users signing up, a multiple-choice marketing survey was implemented using Intercom. The survey asks users to describe their day-to-day, what existing BI tools they use, and where they are on their cloud journey.
Video content and triggers: For video content, the team evaluated custom development versus a quick-win Intercom solution. After finding that their Intercom plan lacked ‘Series’ functionality, they implemented basic video triggers on screen transitions as a short-term solution.
Help content: The Intercom help widget was updated to show context-relevant content in a hierarchical display. This content assists users with their current tasks and can also link to a larger help section if needed.
Getting Started Services
Wireframes were created for a visible panel that offers three distinct services for quick access.
Service 1: Connect my data: Start by connecting your cloud-based data source and create a data view.
Service 2: Design my workbook: Start by designing the layout, adding charts and graphics using manual data.
Service 3: Explore a demo: Start learning by editing our guided demo workbook.
Design
Getting Started Panel UI
Design: A raised, clean white panel with branded illustrations was created to bring the three new services to the forefront of the Lobby user interface. The panel was designed using existing components and familiar language to balance a seamless feel with high visibility to capture the user's attention.
Functionality: The panel allows for quick access to a user's preferred service. For recurring users who need more space, the panel can be easily hidden and then reactivated via the general settings if needed.
Video Content Creation
Methodology: A new AI tool called Synthesia was used for video creation, which utilised a single front-facing personality.
Collaboration: The team collaborated with the Marketing team for branded assets, and with product managers and BI experts for technical approval.
Key advantage: This approach was chosen because the resource would not be dependent on one team, which was essential for a fast-evolving product.
Finished Videos
A Welcome Tour provides an overview of key Astrato areas, and the expected workflow.
Two product section videos offer overviews of the Data View Editor, and the Workbook Editor.
Astrato Welcome Tour, 1 minute overview of key areas and the expected workflow.
Astrato Data View Editor, 1 minute tour of the Data View Editor section.
Astrato Workbook Editor, 1 minute tour of the Workbook Editor section.
Develop
Technical decisions: The initial proposal was to customise video content display. However, due to technical restrictions related to stability and development, an automated workflow was created in Intercom to trigger relevant video content depending on the user's choice of service.
Primary delivery mechanism: The marketing survey, video content triggers, and an optimised help chatbox were developed using Intercom as the primary delivery mechanism, allowing for a modular and scalable solution.
Documentation: New components such as the Getting Started Panel were added to the Astrato design system Aurora, with designs clearly documented to be searchable for all team members.
Intercom Workflows.
Measure
User Testing
In addition to our monitored sessions, we used the platform UserTesting to conduct regular unmonitored sessions.
This approach ensured we consistently had fresh eyes on Astrato, which was crucial for a fast-paced working environment.
UserTesting Session.
UserTesting Metrics.
Metrics Goals
To improve data accuracy for user activity monitoring, and inform design decisions, I established clear metric goals
Goal 1: Conversion rate: To measure the impact of the new self-service flow.
What percentage of new users complete all critical events (Data connection, workbook creation, and visualisation) within the 14-day trial?
Goal 2: Drop-off funnel: To visualise the most common user journey and drop-off.
For converted users, what is the most common first completed event?
For non-converted users, what is the most common uncompleted event?
Metrics Workbook
The 'First Time Experience' metrics workbook was a work in progress, and this exercise helped the team set the best criteria to monitor user activity more accurately. The workbook was crucial in challenging the business's visual-first vision
The key insights were:
An overwhelming 91% of users chose "Data connection" as an early event. In contrast, only 7% chose ‘Workbook creation’ and 1% chose the ‘Demo Workbook’, showing a strong user preference for a data-first approach.
The self-service content showed a 60% increase in the conversion rate over the first six months, growing from 4.5% to 7.2%
This data validated that a ‘data-first’ approach was what users truly needed, shifting the conversation from what looked good to what was most valuable and actionable.
Personas, displaying sign-ups and personas.
Event Order, displaying common key events.
Conversion, displaying conversion and drop-off funnel.
Conclusion
The self-service flow initiative successfully enhanced the first-time user experience by leveraging a streamlined process, video content, and easily accessible help. This improved user activation and showed a positive trend in overall conversion rates.
The Getting Started panel's metrics were crucial, as they validated a data-first approach and confirmed that users were motivated by the actionability of their data.
The insights directly informed a new strategic pivot towards data-apps, which are designed to go beyond viewing data, by allowing users to interact with it, make updates, and trigger actions directly within a workbook. This new direction struck a balance with both user needs, and the business vision.