Expanding job market horizons
for outdoor care providers.

Two feature screenshots displaying work done by Nancy for her case study on Lawnstack

Lawnstack

Maximizing time spent on outdoor care maintenance through optimizing the tools provided to service providers.
Role
Product Design
Intern
Timeline
Summer 2024
Team
1 Product Manager
2 Developers
2 Designers
Skills
Product Thinking
User Research
User Testing
Interaction Design
Outcome
Handed off two new features to developers. Improved efficiency of scheduling feature by 164%.
Schedule jobs according to proximity of other existing clients.
Have a visual representation on where your already-scheduled jobs are to see which day will provide the most optimal route distance-wise. Easily compare and contrast by selecting different dates.
See an overview of the work you have for the day.
A place where all of your jobs for the day will be displayed. View details of individual jobs, submit before and after photos, and get paid upon completion.
Find the route that best suits your current conditions.
A place where all of your jobs for the day will be displayed. View details of individual jobs, submit before and after photos, and get paid upon completion.
Context
Lawnstack’s Mission
Lawnstack is a one-stop shop for homeowners looking to have all of their outdoor maintenance taken care of throughout the year. Lawnstack provides internal tooling for its service providers to effectively manage and execute their jobs.
Landing page for Lawnstack with the title phrase, 'Never worry about your outdoor chores ever again'
The Problem
Many of Lawnstack’s providers do not arrive to their scheduled appointments on time.
“The results were good, but he came 30 minutes late. When I tried to call, there was no response.”
Homeowner A
“I scheduled a job with him twice, and both times he didn’t come at the time scheduled.”
Homeowner G
“We scheduled for 3:30 but he came at 12.”
Homeowner B
User Research: Ethnography
I followed around a provider for a day.
A lawncare worker mowing a suburban lawn
In order to understand their day-to-day process, I hopped into the truck of a lawn care provider. Through this, I gained insights on what aspects influence their daily schedules and workflow.


Rather than scheduling jobs in advance, providers select which houses they will go to that day.
In the first five minutes of their day,
providers base their schedule on
these three factors:
Home Proximity
How close their clients are to each other. Closer homes means less travel.
Co-workers
Who they are working with that day (can spontaneously change)
Job Urgency
Spontaneously assigned jobs that need to be done within the same day
User Testing
It takes 3.4x longer to schedule a job on Lawnstack than via pen and paper.
I user tested the existing Lawnstack scheduling feature on four existing providers on the platform.

I found that on average, it took 3.7 minutes to schedule 1 job. Thus, to schedule 6 jobs for the day, it would take 22.2 minutes, which is a 344% increase from what a provider usually does via pen and paper.

This occurred because providers needed to consider their previously scheduled jobs in order to think about proximity, co-workers, and urgency.
V0
Three homeowner testimonials in text boxes highlighting punctuality issues with Lawnstack's providers but positive remarks about the quality of work. Homeowner A: "The results were good, but he came 30 minutes late. When I tried to call, there was no response." Homeowner B: "We scheduled for 3:30 but he came at 12. Unexpected, but he was very detail-oriented." Homeowner F: "Came late, but got the job done. It’s what I expected for a cheap service."
Regardless of punctuality, homeowners displayed satisfaction with the work being done by Lawnstack’s providers.
The original scheduling feature contained rigid time slots, which heightened homeowner expectation.
Goal #1
How might we make the scheduling feature less disruptive & more seamless with providers' existing workflow?
Iteration and A/B Testing
Considering Proximity
In my first iteration, I made sure to firstly remove rigid time slots. Thus, jobs would now be scheduled simply by day. With this in mind, I also made sure to display jobs already scheduled that day so that providers can take proximity into account.
The image compares two scheduling interface versions: V1 reduced scheduling time by 76% but had usability issues with a horizontal scroll and job proximity being unclear. V2 replaced it with a traditional calendar and a map, improving clarity and reducing scheduling time by 164%.
Goal #2
How might we accommodate for dynamic changes (co-workers and urgent jobs) that occur throughout the day?
Colorful, angular lines in blue, red, green, and gold run across a dark background, resembling routes or pathways. Centered white text reads "Routes!" with the subtitle "Accommodating Dynamic Changes."
Structuring a New Feature
Organizing a Day's Work
Providers organize their client work by day due to dynamic changes. Thus, to accommodate for these dynamic changes, I suggested a new post-scheduling feature that providers can use to plan out their route for the day.
The flowchart shows Lawnstack's user flow, with Discover, Work, Inbox, and Profile. "Work" includes scheduling jobs, routing tasks, and adding co-workers.
User Flow and Information Architecture
Iteration
Exploring 'Work and Routes'
In my explorations for the new ‘Work’ feature, I created different layouts that prioritized different factors.
A calendar interface highlights a selected day with filters for urgency and proximity, showing lawn care jobs with homeowner details and distances for future planning.
Prioritizes future planning
through a calendar
The interface tracks completed and upcoming jobs, showing earnings, job details, and distances, with a “Start this job” button for tasks scheduled today.
Prioritizes tracking of completed/future jobs
Screenshot displaying a day’s route with stops marked and connected, alongside a job list showing details, earnings, and distance, prioritizing route visualization for planning.
Prioritizes visualization of
route for the day
Final Design Recommendation
Providers Value Visualization
Upon bringing my explorations to Lawnstack providers, 7/8 providers preferred a visualization of their route. This is because many providers also have jobs scheduled outside of Lawnstack, and therefore a visualized route allows them to think about ways to fit their external jobs into their Lawnstack route.
A map visualizes routes using the Law of Proximity/Visual Hierarchy, clarifying how routes are calculated. Feedback highlights that route visualization helps providers consider external jobs, with 7/8 Lawnstack providers valuing visualization of routes during a day’s work.
Prototyping the design~
Accommodating Urgent Jobs
Find your optimal route for the day.
Create optimal routes best suited for your current conditions. A new urgent job you need to tend to? Select route by urgency. Want to find the next closest home? Select route by distance.
Accommodating Co-Workers Joining your Route
Re-adjust your route with co-workers in mind.
Easily incorporate your co-worker’s schedule for the day into your own without needing to manually compare physical addresses. If a co-worker ends up joining or leaving your truck, easily edit your route by adding/removing them.
Reflections
ACHIEVING MY PERSONAL GOALS
My goal as a designer is to create digital products that make our communities more equitable. Through Lawnstack, I was able to contribute to a product that targets an underrepresented audience in the tech world: outdoor care providers. It was greatly enlightening putting myself in the shoes of an audience that doesn’t usually receive much attention from innovators.
SHOOT FOR IMPERFECTIONS
Throughout my internship, I had conducted over 24 user testings. My designs had imperfections scattered throughout, yet it was through these imperfections that I was able to understand my user and the industry they work in more. It’s okay to fall down, because you’ll come back stronger!

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