DATA FACTORY MIGRATION
Overview:
Azure Data Factory is a Microsoft cloud-based data integration service that has been around for over a decade. This work is about designing the experience that drives customers to migrate to Fabric, Microsoft's modernized platform, as part of a multi-year plan to fully sunset ADF.
About Microsoft Fabric:
Fabric Data Factory is Microsoft's modernized data integration platform, launched in 2023, built on the foundation of ADF but brought into a unified SaaS experience with Copilot, advanced orchestration, and centralized governance.
My role:
As principal designer, I owned the end-to-end UX across research, facilitating cross-team collaboration and stakeholder alignment, design, and a phased public launch. I also participated in a working group to define migration guidelines for the greater Fabric design studio.
Duration:
Led design and research through a phased approach. The first 6 months focused on the initial release, followed by an additional 6 to 9 months designing and building out additional capabilities.
Why migrate?
ADF has been the go-to for enterprise data integration for over a decade. But the data landscape has shifted. Microsoft Fabric brings everything together in one place and ADF as a standalone tool just doesn't fit that world anymore.
Migrating to Fabric isn't just a lift and shift. For customers it's a chance to simplify governance, modernize their workflows, and tap into what Fabric offers today.
The catch? Customers have years of pipelines, connectors, and workflows already built. Walking away from that without a clear, trustworthy path forward isn't realistic.
Pandemic Strategy
With so many businesses closed during this time, this was an opportunity to convert prospects who were open to making business changes.
More were willing to switch if we committed to doing the work, so we had to move quick.
They were spending a lot on other marketing tools (ie. Mailchimp, Hubspot) and wanted to cut costs.
Others liked Boulevard’s platform, but were currently on competitor software (ie. Mindbody, Millenium) with built-in marketing tools.
So where did we start?
User
research
To narrow in on what’s important, we chatted with customers and prospects to understand key metrics they needed to evaluate campaign performance.
Deep dive on competitors
Partnered with our product marketing manager to understand key marketing features of our wellness competitors as well as other marketing platforms.
A lot of brainstorming
We were starting from scratch, so what we built had to fit our timeline and was feasible without losing sight of what customers needed most.
All the artifacts.
These were created to map out our thoughts and
bring others up to speed on where we were at.
Where are we at today?
To get buy-in from our main stakeholder (CEO) on our phased approach, we needed to discuss where we were at and how to scale users permissions while we build marketing.
This also identified features to group under the marketing umbrella.
Merging mental models
As we chatted with businesses, we identified the differences in how they approach their brand and marketing to see how we could build a flexible platform.
Scaling from SMBs to Enterprise
80% of our customers have 1-2 locations, but to target enterprise customers, we wanted to understand how they market.
Thinking ahead helped lay the foundation for our current customers who were aiming to grow.
Exploring the possibilities
There were a lot of iterations throughout our discovery phase until we nailed down a strategy and landed on a clear design approach and mapped out the workflows.
A clear design approach
Key decisions
Focus on email campaign types for now and address text campaigns later. (ie. sending out a reminder to book after # of days)
Create campaign management experience for small businesses (1-2 locations) with consideration on how it can scale to enterprise.
Release a set of default email designs that could work across all verticals (ie. hair salon, barber, medspa, etc.), while we continued to refine the template editor.
So what’s the release plan?
1
Alpha
Have 1-2 customers test out metrics with one email campaign type to start, and see how campaign performance looks for them.
2
Closed Beta
Invite more customers to try out the marketing suite and add appointment booking data.
3
Open Beta
Include more email campaign types, and additional metrics.
4
General Release
Edit experience based on feedback and prep for releasing to all customers.
Final Designs
Key Features
Summary view of performance across all campaigns
List view of Individual campaign performance
Set up and management experience for each campaign type
Setting permissions for one vs multi-location businesses
Learnings
It takes a lot of discussions to get aligned.
The challenge was coming to an agreement between product and leadership. It was an ongoing discussion of pushing a pricing plan sooner than later to create revenue.
But product pushed back because we wanted to get the right viable product out before charging.
Pick a direction and pivot later as we learn.
We didn’t know what to focus on at first. Did we want to focus on email campaigns or in parallel explore and build text campaigns too since it was highly requested also?
But starting with emails, we kept users excited to try this first while bringing them along the journey as design partners.
Users need to be confident about the data.
We played with data visualizations which came with its struggles to nail down the accuracy of the UI.
At the end of the day, our users assured us that it’s more about the numbers and if they were accurate, so we omitted the data chart work for general release.
