Saving Goldbelly 19%: "One of the highest ROI cost saving initiatives we've had"

Case study

Published on

Espresso saved Goldbelly 19% on their Snowflake bill

“Espresso AI has been super easy to integrate and got us immediate, measurable cost savings on our Snowflake spend."

"Plus, the support team has been very helpful and responsive throughout the process of setting it up!”

Goldbelly is a curated online marketplace for gourmet food and food gifts from across the US. Founder Joe Ariel and his team of ‘Food Explorers’ search the country for the nation’s best regional, small batch foods, from the county’s top chefs and most iconic restaurants, to the most renowned bakeries, pizzerias, pitmasters and artisan shops. With an ever-expanding, curated selection of over 10,000 restaurants and food makers, Goldbelly offers a platform for small local businesses to reach new customers outside of their local area.

Headquarters

New York

Employees

120

Funding

Industry

Food marketplace

CRM

Espresso has been super easy to integrate and got us immediate, measurable cost savings on our Snowflake spend. It is definitely one of the highest ROI cost saving initiatives we’ve had.

Tim Hsu

Engineering Manager

If you have a craving for authentic brisket, a Boston lobster roll, or an apple pie from where you grew up, Goldbelly may just be the best way to get it. Many people first heard of them in the dark days of the pandemic, when they were the only thing standing between you and boiling an egg for lunch. Now, they're between you and over 10,000 restaurants and niche food makers across the country.

‍

Goldbelly's Snowflake Usage

Goldbelly uses Snowflake as its primary data warehouse, aggregating data from various sources including its core customer-facing application.

As Goldbelly's growth skyrocketed, so did its Snowflake costs.

The data team sought to improve the efficiency of their Snowflake environment and reduce operational costs, but were cautious about disrupting critical or customer-facing workloads.

‍

Espresso AI’s 19% Savings Estimate

To understand the optimization opportunity, Espresso AI followed a three-step process:

Establishing a baseline: Analyzed the customer’s metadata in a proprietary simulation environment to replicate daily workloads and pinpoint inefficiencies.
Modeling agent impact: Simulated how Espresso’s autoscaling and scheduling agents would optimize usage by reducing idle time and improving warehouse efficiency.
Synthesizing the data: Delivered a detailed per-warehouse breakdown of potential savings from these optimizations.

Espresso’s autoscaler was projected to reduce Goldbelly’s six figure Snowflake bill by 19%.

‍

Implementation was fast and seamless

Espresso AI’s onboarding process was fast, secure, and required minimal effort from Goldbelly:

User setup: Goldbelly ran a script to create an Espresso AI user with restricted Snowflake permissions.
Risk-free trial: A two-week trial with a money-back guarantee demonstrated savings in a live environment.
Full control: Goldbelly retained complete control, with logs of all actions and a guarantee that no queries would be altered.

To support monitoring and validation:

Espresso AI provided daily comparisons of credit usage before and after optimization.
All automated changes, such as cluster scaling, were fully transparent and reversible.

Espresso's 19% Savings Projection Validated in Production

During the trial, Goldbelly saw immediate value from Espresso AI:

Cost savings: The projected 19% reduction was validated in production
Efficiency gains: Dynamic workload management reduced idle time and optimized resource usage. The time saved optimizing Snowflake was able to be reallocated to higher value work.
Full transparency: Goldbelly’s data team verified savings via detailed logs and dashboards, including controlled tests comparing optimized and non-optimized warehouses.

Following the successful trial, Goldbelly expanded Espresso AI’s solution to more Snowflake warehouses.