Thriftbooks uses Mode to make better buying decisions
Thriftbooks is the largest second-hand book selling platform, with over 13 million titles and 900 employees.
With Mode, we can rapidly prototype, which increases time to value and saves our developers’ time, which really matters to us.
Siloed data was a bottleneck for decision-making
At Thriftbooks, the engineering team was the “source of truth” for any questions about data. Since the developers built the applications generating the data, they were the only employees who knew what information existed and where. The engineers became bottlenecks for data requests, which resulted in business stakeholders not getting the information they needed in time.
“The primary challenge we experienced was that all our data was with the engineering organization. Developers ended up acting as “data people,” which took them away from building the features and tools they were excited about.”
Every day, the team made decisions on whether or not to buy shipments from specific suppliers, like Goodwill and other second-hand stores. In order to make data-driven decisions on these investments, the supply team would frequently ask the engineering team questions like, “How likely is this shipment to sell?” and “How has this supplier performed in the past?”
Answering these questions was critical to the business operations of the organization, but it was inefficient for engineers to spend time answering them. The team also couldn’t look at data in the right way to teamfind these answers using the company’s BI tool of choice, PowerBI, so Trevor began looking for a new solution.
Thriftbooks built internal applications to empower domain experts and free up engineering bandwidth
Trevor rolled out Mode to get data out of the engineering organization and into the hands of domain experts. His goal was to both increase his team’s bandwidth and improve operational processes.
In less than 30 minutes, Trevor used Mode to build an internal tool that allowed the supply team to input a list of 10,000+ ISBN numbers (an International Standard Book Number). This helped them immediately make data-driven decisions on which suppliers to accept orders from without the help of engineering.
Being able to see not just the favorability of individual ISBNs, but also predict the amount of revenue Thriftbooks would get from a supply or the average demand of a bundle of books, allowed the supply team to make decisions without relying on engineering.
“Mode makes it easy. I don’t have to create a new project or put it into source control - I can just write a query to pull in thousands of ISBNs - the fact that it’s ’all web-based makes it so simple and fast.”
Thriftbooks increased profit margins by enabling better buying decisions
This internal application in Mode improved the supply team’s workflow. They were quickly able to forecast how much revenue a certain bundle of books may bring in and use that data to say ‘yes’ or ‘no’ to the shipment. This led to better investments and increased profit margins for Thriftbooks.
Mode also continues to save engineering time on a daily basis. The supply team can answer impactful questions for themselves, which means that the engineering team is no longer distracted from their other projects with ad hoc requests. Ensuring that the engineers spend their time on strategic projects is key to the growth of Thriftbooks as a technology company.
“We’ve been able to use Mode as an application without having to build an application—that is something we couldn’t have done with any other data reporting tool.”
Data teams move faster in Mode