ThoughtSpot acquires Mode to define the next generation of collaborative BI >> Learn More

Case Study

Cash App accelerates product innovation

Cash App, functioning as a startup within Block, Inc, is a mobile payments provider that empowers its customers to instantly send and receive money—anytime, anywhere.

Data Stack

Snowflake

Tableau

Looker

Mode

Mode enables me to do my job better, and if I can empower other people to do their jobs better, then we can grow together.

Neil Chainani
Data Science Lead at Cash App

Challenge

Existing BI tools too slow for quick experimentation

At Cash App, the data team works alongside the product team to ensure product problems are approached with data-driven perspectives. They ensure the product is performing well, and also want to make sure it's competitive, which requires constant innovation. With this in mind, Data Science Lead, Neil Chainani, wanted his team to quickly and easily run experiments that would help the product team make these strategic decisions.

When Chainani joined the Cash App team he found the existing BI tool slow and frustrating to use; the data team ended up spending more time managing the tool than using it for analysis. “It would just give you this little loading circle that would sometimes take minutes, and by that time, I would be onto something else.” Chainani explained. Further, sharing insights with the wider team, like downloading large reports for stakeholders, was slow and would each take minutes.

Without Mode, it would have taken at least 15 hours of my time to put together all of the metrics we are interested in.”

Neil Chainani Data Science Lead

Solution

Mode saves time and enables faster product innovation

Since implementing Mode, the Cash App team has been able to expedite the experimentation process fueling more data-driven decisions with the product team. Not only has using Mode saved time by improving the data team’s general productivity, it has allowed the Cash App team to put living knowledge directly in the hands of stakeholders.

Mode is also helping Cash App democratize their data. A data scientist can now quickly build dashboards for other internal teams, and pass over controls on the data to product managers so they can build their own dashboards.

The Cash App team even created a custom Mode guide that highlights Mode’s key features for other internal teams for broader usage. Mode clears the way allowing the Cash App team to focus on the bigger picture, and as Chainani explained, “it enables me to do my job better, and if I can empower other people to do their jobs better, then we can grow together.”

Impact

Cash App built their own experimentation platform using Mode

After seeing the team struggle with their existing tool, Chainani decided to make the case for Mode. He’d used Mode at a prior company, and knew Mode could streamline the team’s day to day tasks. The goal was to free the data team up to focus on deeper analysis and drive more strategic product experimentation.

It was a success. Using Mode, the Cash App team built their own experimentation platform for the product team. With the guardrail of parameters, the product team can now run as many queries as they would like on top of reports, which lets them dig deeper into their product usage.

The product team can also easily customize the parameters behind a query, allowing them to run more results, faster. Using the power of parameters, combined with Mode’s Visual Explorer, their data scientists can run experiments and explore product data even faster, putting insights directly into the hands of their product team.

They are now able to easily customize the parameters behind a query, allowing them to run more powerful queries, quicker.

Mode saves approximately 30% of my productivity, so that I can focus on the big questions.”

Neil Chainani Data Science Lead

30%

increase in data team productivity

25

data scientists focused on deep analysis

100s

of experiments run on a single query

30%

increase in data team productivity

25

data scientists focused on deep analysis

100s

of experiments run on a single query

Get more from your data

Your team can be up and running in 30 minutes or less.

Try for free