LZ Books Transaction Review

Q2 - Q3 2024

THE CHALLENGE
Improve the process of reviewing transactions to make it more clear and efficient for customers by redesigning the reviewing experience, introducing rules, and offering AI assistance with categorizing expenses.

ROLE
As the design lead for this project, I advocated for our team to invest in bookkeeping improvements for the quarter, owned the discovery phase, and delivered all the detailed designs, partnering with product and engineering closely along the way.

Background

This project was started because what we thought was going to be an easy fix ended up not being very easy. Based on observations from customer interviews, we noticed that people were struggling with how to review transactions and organize their books. We thought that we could keep the existing experience and make a minor change, but the further I dug into the problem, the more I saw that we needed to change the whole paradigm of reviewing all together.

After making improvements and introducing rules we saw a 285% increase in transactions monthly active users since the beginning of 2024. 44% of activated customers have reviewed and confirmed transactions, something we weren’t able to track before with the previous design. Also since launching rules, 84% of customers that see a rule suggestion end up creating a one, and an average of 20% of transactions have been confirmed via rules.

Project Highlights

Review takeover

From: a table with no guidance or requirement to review categories

To: a focused takeover where customers can select transaction purposes & categories and explicitly confirm that it has been reviewed.

Redesigned transaction drawer

Transaction details used to live in-line on the table, but it was not very scannable, so I updated the design to be a drawer. Then all the info could stack and not disrupt the table.

Rules

Designed a feature that suggests rules for speeding up and automating the reviewing process, which saves customers time and energy. Since launching, 84% of customers that see a rule suggestion end up creating a rule.

AI categorization

Designed an experience that helps give customers more guidance on what category their expense is, based on a short description, which is our first customer facing AI experience for LZ Books.

Process snapshot

  • We were only able to identify a problem with our designs because we noticed people struggling in interviews to understand what reviewing a transaction means. Based on these observations I was able to put a case together for redesigning the experience.

  • Usually I tend to think in pretty high fidelity, but this time I wanted to focus more on different paradigms for reviewing transactions and not get lost in the UI. So, I generated many different options in mid-fidelity to help guide conversations

  • Whenever I got stuck with a design, I ask other designers for help. For this project I had multiple meetings with my design partners, PM, and engineers where we just explored in Figma together and bounced ideas off each other. It helped to get unblocked, and designing live helped us make quicker decisions.

This is just a high level sneak peek of what my process was like during this project. I’m happy to dive into deeper detail upon request.

SKILLS TO HIGHLIGHT

Influencing the roadmap

I was able to identify a problem and advocate for the design time needed to properly address the issue. I dug deeply into the experience, made sure our team was aligned, contributed to scoping conversations, and delivered designs in a phased approach.

Contributing to design systems

In addition to this being a heavy interaction design project, we also ended up introducing some new patterns and contributing them back to the design system, such as a right drawer that opens on top of content.

Interaction design

This project was tricky since it required understanding how customers were interacting with and understanding the original design, seeing the shortcomings, and reimagining the underlying paradigm for reviewing transactions. I couldn’t just think in screens, but had to use diagrams and other visualizations to make sense of everything.

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