Rebuilding the framework for a scalable future

How might we support the estimating processes of all moving companies, regardless of their size?

In the moving industry, accurate estimating and surveying are crucial elements of the sales process, enabling companies to provide precise quotes, secure deals with clients, and effectively manage inventory throughout the entire move. Supermove is an all-in-one software designed to streamline various aspects of moving companies' operations, including those of their sales teams.

Despite the success of the Estimator app with small residential customers, challenges arose as larger clients were onboarded. A single inventory library led to bottlenecks in performance, hindering the salespeoples’ jobs. Recognizing the need for major improvements, the team shifted focus to meet the diverse needs of all customers.

I led the research, scoping, and design overhaul for the entire Estimator experience. This case study focuses on the behind-the-scenes setup of inventory libraries.

Team
Product Manager
→ Product Designer
2 Engineers

Year
2023, 4 weeks*
This case study covers one of two parts of this initiative.

Skills
User Research
Information Architecture
Systems Design

︎ The Challenge

Surveying the surveyors

Through the hard work of our customer success team, we had a good understanding of the technical issues that our customers were facing when using the Estimator app: it's inflexible and laggy.

To dig deeper, I asked salespeople at 5 different companies to conduct a residential move survey to understand:

At which step does the frustration begin?
What is their thought process as they walk through a house?
How are they making sure that the information is accurate?

One key discovery was that everyone had their own routine when surveying. For instance, one salesperson would survey all the standard rooms such as the living room, kitchen, bedrooms, and so on, before any non-standard spaces, like a crawl space or a sunroom.

From there, it became apparent that the frustration stemmed from the beginning of the survey. The Estimator app would populate all rooms and items indiscriminately, regardless of the move type. To record a couch in the living room, they had to sift through all the rooms to find the living room and then all the items to add the couch. The tool’s performance suffered, becoming slow and unresponsive due to loading all the data at once.

Our customers were already struggling with residential moves. The challenges faced by moving companies undertaking commercial moves (think: moving an office of 1,000 people to another building) could only be worse with a single inventory library. It was clear we needed to address the behind-the-scenes before we could improve the current Estimator's experience.

︎ The Goal

Create a platform that works for our customers, and not the other way around

Surveys are a vital part of any moving company’s operations, and some of our larger customers couldn’t be fully deployed until we made the necessary improvements. We knew that delays in development could have a real impact on our customers’ operations, so I set some high-level goals to ensure we stay focused.

Speed it up

Improve performance not only for our customers, but also behind the scenes so it's easier to maintain

Streamline inventory

Provide each moving company—no matter the size—the flexibility they need to get their job done right

Slash time spent

Give our users the freedom to focus on their customers' needs instead of wrestling with our platform

︎ The Process

For mom and pop shops to big city movers

I collaborated a tech lead to rethink how our inventory library could be reorganized to be more flexible and scalable without sacrificing the simplicity of setup. This involved unraveling hard-coded settings without disrupting existing files.

Multiple inventory libraries were introduced to help customers keep track of specific items and categories for different types of moves. With the ability to set a default library per move type, loading an entire library per survey is no longer necessary. Categories were also reworked so that items could be sorted and set as a default per room. Customers can also customize default rooms and their order per project type and add rooms as needed, so there's no need to assume that every house has a crawl space.

On the user experience front, we addressed an issue where editing anything in the library had to be done individually through a tedious CSV export-import process. Moreover, the lack of proper error messaging made CSV troubleshooting challenging.

We implemented bulk editing to enable customers to edit items simultaneously. For customers who preferred maintaining their libraries in a CSV, or new customers wanting to import information from other software, we launched an improved file uploading experience that identifies errors and ensures that uploading a CSV won’t erase the existing library.

︎ The Results

Set and forget

Since the release of this feature, our customers and implementation team spend 50% less time setting up inventory libraries. For our smaller companies satisfied with their inventory library as is, we transferred it over without them having to lift a finger. This feature paved the way for a more streamlined experience on the new Estimator app, which resulted in an 88% increase in engagement within a month of its launch in March 2023 and deployed our largest customer at the time.

*For privacy reasons, I've hidden some exact metrics. Get in touch for a more detailed version.

︎ Reflections & Learnings

Taking inventory of my thoughts

Looking forward, I want to explore giving our customers even more flexibility for the way they work. For example, I’ve learned that there are default items that customers would like to automatically have in each room (it’s safe to assume every bedroom has a bed). Additionally, we currently only provide one default library to all our customers, but implementing something like a library for inventory libraries—so meta—could help our larger customers onboard to this tool even faster.

valerie wong ︎

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valerie wong