First Time Experience
Overview
We observed higher levels of usage with personalised onboarding. To improve retention for users opting out of white-glove sessions, we aimed to create a self-service experience. This initiative also allowed us to assess the effectiveness of our visual-first approach.
Outcome
Developed a self-service flow for Astrato 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 that led to a new data-app strategy.
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
What Problem Are We Solving?
Data analysis indicates that Corporate users have consistently higher levels of product usage than Social users. This disparity is potentially caused by a lack of personalised onboarding for Social users and/or an over-prioritisation of a visual-first approach, which may hinder the data exploration experience.
Corporate user activity.
Social user activity.
Hypothesis
We believe a comprehensive self-service experience, including interactive tutorials, will increase Social user retention by enabling independent product learning. To determine which approach (visual-first or data-first) results in higher engagement and adoption, we will present users with distinct entry points, one that starts with a data connection flow, and one that starts with a pre populated visualisation, and measure full journey completion rates, segmented by data analytics background. We believe that users will exhibit a higher completion rate when experiencing Astrato using their own data, hence prioritising a data-first approach.
Project Objectives
Increase user activation through a self-service flow: Review and optimise existing product tours, and introduce content to guide users through key features.
Reduce time to complete key tasks: Remove unnecessary steps and clutter from the user interface.
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.
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
Intended User Journey Map
We developed a user journey map, "Zero to Hero" focusing on a data-first approach to maximize value for "The Expert". This persona, characterised by strong data analysis skills, benefits most from connecting with their data. The journey map outlines key steps, including data connection, data exploration, visualisation, and workbook sharing. This map also functioned as a feedback board, allowing us to surface user feedback, identify quick fixes (e.g., improving copy), and prioritise new features (e.g. enhanced table view). This journey is visually represented as a swimlane diagram, providing a clear overview of our intended user's experience.
User Feedback
Feedback and recommendations were gathered from monitored/unmonitored user testing sessions, workshops with internal/external BI experts and Astrato Galaxy (external community).
This is all fed into Glean.ly, our scalable research repository, creating a points system to help inform priority and design decisions.
Glean.ly score card examples:
EVIDENCE SCORE 27
“Create tutorial/animation/step-by-step for Actions”
EVIDENCE SCORE 20
“Help users more with joins in the DVE.”
Personas Summary
Joe “The Expert / Influencer”
“I deliver insights to senior stakeholders making business decisions”
BI Developer
10 years of experience on the job.
BS in MIS, Marketing, Finance, etc.
Data wizard and passionate about great storytelling.
Juste “The Business User”
“I use insight to drive performance”
Marketing Manager
20 years experience.
MBA in marketing & Business.
Charismatic & confidant.
Ideate
Following the resolution of excessive Intercom messages, inconsistent product tours, and lengthy marketing surveys, I collaborated with stakeholders to explore service starting points. We considered 'Start with data' (define data view) and 'Start with a workbook' (visual templates), along with feature-specific video tutorials and animated walkthroughs. Inspired by competitor onboarding flows (GoodData, Motion, GRID), we tailored these to our user goals and needs, creating a high-level flow to guide next steps.
Define
Video Content Solutions
We evaluated custom development, and quick win solutions with Intercom. Finding our Intercom plan lacked ‘Series‘ (message/video types on custom triggers), we implemented basic video triggers on screen transitions as a short-term solution. After completing the core self-service flow, we will measure performance and reassess upgrading Intercom.
New Self-Service Flow
We finalised a new self-service flow with stakeholders, integrating marketing surveys, three getting-started services, video content triggers, and an optimised Intercom help chatbox.
Marketing Survey Questions
Using Intercom we ask the following multiple choice questions to gather insights on the types of users signing up.
What best describes your day to day?
What existing BI tools do you use?
Where are you on your cloud journey?
Getting Started Services
We created wireframes for a visible and descriptive panel, surfacing three distinct services for the user.
This can be hidden once the user does not require the additional assistance, and resurfaced if needed again.
Connecting your data - Start by connecting your cloud-based data source, and create your data view. The preferred journey for users who wants to explore their own data quickly.
Designing your workbook - Start by designing the layout, adding charts and graphics using manual data. The preferred journey for users who wants to explore visualisation capabilities quickly.
Exploring a demo workbook - Start learning by editing our guided demo workbook. The preferred journey for user who wants to view the end results quickly.
Each journey will trigger additional engaging video content that is unique to the chosen service, and product section.
Video Triggers & Scripts
We mapped out exactly where the welcome video, product section videos, and the feature specific video tutorials would be triggered in the user journey.
Welcome tour: 1 minute tour of the Lobby section, and the expected workflow.
Product section tour: 1 minute tours of the different product sections, Data Connection Wizard, Data View Editor, and Workbook Editor.
Feature specific: 30 second tutorials of the top features in the different product sections e.g. DCW: Connecting To My Data, DVE: Using The Data Explorer, WBE: Actions.
The order of the product section videos, along with subtle content differences would change depending on which of the three getting started journeys the user takes.
All the videos would only be intrusive once, if (when) the videos are skipped the user can access them again at their own leisure from the Intercom help chat box.
We then proceeded to create draft scripts for these, always keeping in mind the objective of quickly showing the value of Astrato to the user.
Help Content
The Intercom help widget will be updated to show help content that is context relevant, and display these topics in hierarchy.
This will help the user complete their current task, but can also link to a larger help section if needed.
Design
Getting Started Panel UI
A raised clean white panel, and branded illustrations brings the new three getting started services to the very front of the Lobby user interface.
Using existing components, and familiar language, we balanced seamlessness with high visibility to grab the users attention.
The panel is easily hidden for recurring users that require more space in their Workbook section, and reactivated via the general settings if needed.
Video Content Creation
With our confirmed video list, trigger events, and scripts, we discussed the best process for the video creation, collaborating with the Marketing team for branded assets, on video editing tools and consistent language.
We decided to go with a tool called Synthesia, utilising AI for a single front-facing personality that would not be dependent on one team’s resource, essential for a fast evolving product.
Product Managers, and our BI Solution experts were responsible for approving the videos from a technical perspective, and the final results were extremely well received by all involved, including stakeholders.
Finished Videos
The below video examples include a welcome tour, providing an overview of key Astrato areas and the expected workflow, and two product section videos, offering overviews of the Data View Editor and Workbook Editor.
Astrato’s key areas, 1 minute welcome tour of the Lobby section and the expected workflow.
The Astrato Data View Editor, 1 minute tour of the Data View Editor section.
The Astrato Workbook Editor, 1 minute tour of the Workbook Editor section.
Develop
Development's primary concern was our initial proposal to customise video content display within Astrato, rather than using Intercom. Technical restrictions related to stability and development time. We adjusted the flow early in the process to accommodate these limitations.
Intercom
We created automation workflows in Intercom, triggering the relevant video content depending on which service the user chooses.
Intercom Workflows.
Data View Editor Workflow.
Design System Documentation
New components were added to the Astrato design system Aurora on Zeroheights, clearly documenting designs to be searchable for all team members.
Measure
User Testing
We used the platform UserTesting, doing regular unmonitored sessions on top of our monitored sessions, ensuring regular fresh eyes on Astrato for a fast-paced working environment.
UserTesting Session.
UserTesting Metrics.
Metrics Goals
To improve data accuracy for user activity monitoring to inform design decisions, we established clear metric goals.
Key objectives:
Measure conversion rate: Percentage of users completing a critical event during the 14-day trial.
Track key feature events (FTE) and visualise drop-off using a funnel diagram.
I partnered with a BI analyst to clean data, define questions, and set criteria.
Goal 1: Conversion rate
Question: What percentage of new users complete the critical event within the 14-day trial?
Criteria:
Timeframe: 14 days (trial period).
Critical event: Completion of data connection, workbook creation, and visualisation.
Conversion formula: (Users completing critical events within 14 days / Total new users) x 100%.
Goal 2: Drop-off funnel
Questions:
For converted users, what is the most common first completed event trigger?
For non-converted users, what is the most common uncompleted event trigger?
Criteria:
Timeframe: 14 days (trial period).
Trigger events: Data connection, workbook creation, visualisation.
Output: Funnel diagram illustrating user progression through the workflo.
Metrics Workbook
Data cleaning and visualisation for the 'First Time Experience' metrics workbook were ongoing, making it a work in progress.
Overview, displaying sign-ups and personas.
Conversion, displaying conversion and drop-off funnel.
Activity Order, displaying common key events.
This exercise improved how we monitored user activity, giving us more accurate data, surfacing patterns, and raising new questions for us to answer. Insights and questions examples:
Data connection is the most common early-journey event.
Workbook and visualisations is the most common post-mid journey event.
What is the sign-up rate over a 6 month period?
What is the rate of conversion over a 6 months period?
What are the customer personas types and prospect personas types?
Conclusion
Vizlib's acquisition by Insightsoftware, a US company, resulted in the closure of the London-based design team. Consequently, I was unable to observe the full impact of the self-service videos, and Intercom updates for Social usage. However, the 'get started' event metrics indicated a data-first approach, deprioritising the visual-first approach and contributed to a new data-app strategy.