Emerge Lands $130M in Series B & Cuts Snowflake Compute Costs by 32% with Sigma
The digital freight marketplace pioneer Emerge is disrupting a critical segment of the logistics industry. Emerge’s cloud-based procurement software efficiently matches shippers with a network of carriers to find capacity for freight while simultaneously helping carriers bid on and optimize their workloads to minimize unused capacity. The company has $150M in venture capital.
Emerge has been undergoing significant growth, they opened an additional East Coast office in 2022. The company’s platform facilitates transactions within a marketplace of shippers and carriers. Ultimately, Emerge is trying to match demand (shippers) with supply (unused capacity on trucks) as efficiently as possible.
Business was growing prior to its Sigma deployment, but the data analytics and BI teams didn’t have any real visibility into operational efficiency. Emerge had been using Periscope but it was only deployed in embedded customer reporting for its clients on the shipping side of the market. The company’s data team realized they’d need a more powerful analytics platform if they wanted to scale Emerge to the next level of success.
Emerge began using Sigma in early 2021. Today, a Fivetran ETL connector moves data from 600 unique sources into Snowflake. Sigma is the analytics engine of choice for that Snowflake footprint, and the company uses the platform for visualizations, reporting, data exploration and engineering, and, according to Director of Analytics Brandon Santiago of Emerge, pretty much anything data-related.
In a little more than two years, the number of daily active Sigma users expanded by 4X from 60 to 235, thanks to the platform’s easy-to-use spreadsheet interface. A subject matter expert with some understanding of business logic can now go into Sigma and do their own data wrangling and engineering without enlisting and waiting for the help of the infrastructure team, freeing up time for Santiago and his group to focus on more strategic work. Sigma plays a critical role in sales, business development, and executive communications as well: C-suite team members regularly drop screenshots of Sigma objects into powerpoint decks for board meetings. As far as other BI tools like Tableau and PowerBI are concerned, Brandon says there is no question which solution is best for Emerge.
Sigma has given Emerge rapid, cost-effective access to data for analytics, visualizations, reporting, exploration, and more.
I don’t like Tableau. You have to learn their own language, which is a huge barrier to entry, exploration is more difficult, and it just can’t render as much data as easily. I’ll never use Tableau again, and although PowerBI is cool, neither of them are capable of doing what Sigma does for our company.
—Brandon Santiago, Director of Analytics, Emerge
Brandon and his team are using Sigma for a data mining operation that distills tens of millions of rows from 17 different data sources down to the key details the end user needs—and does so in just 3 seconds. A broker looking to cover a load will be able to quickly search for the optimal carrier match, the probability of that carrier accepting the job, a starting place for negotiations, and more. Plus, Brandon thinks that with a few more tweaks, they’ll be able to get this down to 1.5 seconds.
“What we did here by deploying Sigma as our company and our datasets were growing has been essential to our success,” shares Brandon. “The ability for an analyst to take the raw data, build their own ETL pipeline out of Sigma, apply business logic along the way, and then materialize that set and make it available to end users—hundreds and thousands of times a day across all areas of our organization—is remarkable.”
When Sigma was first deployed, 60 people within the company were using the technology. Now the platform has 235 daily active users–or roughly 80% of the entire company.
One of Emerge’s core application objects was generating 150,000 records per year, while another was generating 1M records annually. Since deploying Sigma, those records have grown to 450,000 and 3.5M, respectively. That 3X to 3.5X growth would have driven similar growth in Snowflake credits, taking Emerge from around 250 credits to close to 900 monthly credits. Yet with Sigma, the company has actually reduced its usage to 160 credits per month, so Emerge is actually saving 32% per month in Snowflake compute costs.
Prior to Sigma, Brandon says Emerge wasn’t able to view or present a clear picture of just how quickly its business was growing.
Sigma allows the data, finance, and executive teams to build forecasting models, then make those models deliverable and easy to share and consume. This proved essential when Emerge went out to raise a Series B round. “The company’s leadership team used the analysis, reports, and visualizations from Sigma to present metrics to its investors that translated to the company raising $130M in Series B funding,” says Brandon.
Tasks that used to take anywhere from days to weeks have now been automated with Sigma. One job that involved exploration, engineering, and approvals has been reduced from several days to 1 minute. Another task that took the company’s comptroller and a senior financial manager 5 days every month has been automated, giving those senior team members back their time.
Ultimately, Emerge is using Sigma to break down the barriers between data and the people who need it; free up time for business and IT; reduce costs; and drive the company’s overall growth.
