Preparing QuickBooks for an adaptive, data-driven future

Intuit • 2023

Tasks

Research

Strategy

Design leadership

Usability testing

Role

Principal Designer

Mockups of the QuickBooks onboarding flow to show AI and personalization could be used to make understanding the product in the first 30 days much easier.

Project Goal

QuickBooks aimed to support both startups and large enterprises across various industries by offering a more personalized, adaptive accounting experience. My role was to establish key design principles and frameworks to guide multiple teams in integrating AI seamlessly into the user journey.

Challenge

We found new users were dropping off early. Our research indicated two core issues: 

  • We were asking for too much information upfront.

  • The onboarding experience didn’t adapt meaningfully to different business types or experience levels.

We had to consider the architecture of widgets on the analytics page to ensure that we could implement personalization in a scalable and consistent way.

Approach

Collaborating closely with a technical director, there were three main approaches we took to this work: 

Defining a data-aware onboarding strategy 

We mapped out data we legally needed to capture as well as what we could technically capture both pre and post authentication. This helped us simplify onboarding to capture the essential data and gave us a structure model we could use to drive persinalisaton downstream. 

Desiging a Personalization Framework 

Because personalization spanned multiple squads, I operated horizontally across the organization. I created interactive wireframes to show how data capture in one part of the journey could impact experiences elsewhere. This helped to guide the team without fragmenting the overall experience

Prototyping contextual support experiments
Finally, we ran small proof-of-concept tests, partnering with the YouTube content team to understand how help content videos are structured and tagged. This allowed us to explore how we could surface help contextually based on our key data parameters. 

Outcomes

  • Reduced friction in onboarding by limiting required inputs to essential data

  • Created a scalable parameter framework for AI-driven adaptation

  • Improved cross-team alignment around personalization strategy

  • Established foundational patterns for context-aware support during the first 31 days of product use

Design principles we created using the broad body of Intuit research used to guide personalization project teams.