Amuse Cuts Cost Per Delivery by 30% and Enables Self-serve Analytics with Sigma

Amuse is an e-commerce cannabis delivery business that is reinventing the way consumers order and consume cannabis. Made up of experienced e-commerce operators from companies including Amazon, Uber, Bird, Eaze, Nike, MedMen, Target, Weedmaps and more, Amuse’s mission is to deliver high-quality cannabis products safely and conveniently right to your doorstep.

The Challenge

Building a Data Stack That Improves Operational Efficiency By Enabling Self-service

Starting a successful service in a field full of well-funded incumbents requires swiftly identifying and overcoming operational challenges. But starting one in the middle of a global pandemic requires the highest levels of visibility, efficiency, and adaptability. And that’s exactly where the team at Amuse found themselves as they prepared for launch in 2020.

“Our top goal is always to reduce our cost per delivery (CPD),” says George Durzi, Chief Technology Officer at Amuse. “This requires running our organization on data. That’s why, since day one, we’ve been tracking every key metric in an effort to lower CPD. We knew that getting our data stack off the ground was absolutely critical.”

Alex Becker, CRO at Amuse, emphasizes the importance of the CPD metric for the company:“If we can get really efficient on the cost per delivery side, we’re a rocket ship of a business.” But measuring CPD and identifying opportunities to improve it are much more complicated than it may seem.

“There’s at least 18 different variables that go into cost per delivery,” says Becker. “We have direct costs like driver payroll, benefits, mileage reimbursement, etc. But there are also indirect costs like the packers that pick the items and pack them for each delivery And then there’s operational expenses like rent, electricity, and the bags that we use. All of these factors make it challenging to determine our true CPD.”

Calculating CPD costs prior to the implementation of their data stack was an intern’s worst nightmare. Durzi summarized the process: “We would do an export of our sales data. Then an export of our logistics data. We would then have a manual list of order failures and the reasons why they failed. An intern would crunch those in Excel and send the recap the previous day to the execs.”

The freedom to implement a cloud-native stack from the get go was quickly seen by company leadership as a unique advantage and mission critical investment if they were to compete in the fast moving cannabis delivery industry.

The Solution

Connect to the Cloud, Integrate Data Sources, and Automate Reporting with Sigma

With data flowing in through Fivetran pipelines into the Snowflake Data, Durzi and his team set out to find an analytics solution that would enable nontechnical folks from across the organization to self-serve.

“Most of our choices were based on not repeating mistakes we had made in the past at other companies,” says Durzi. Durzi had initially discovered Sigma while he was at MedMen, and decided to evaluate it for Amuse’s needs. Within minutes of the first demo with Sigma’s sales team, Durzi knew he had found exactly what he was looking for: an iterative, ad-hoc data analytics tool that anyone at the company could learn how to use.

The seamless integration with Snowflake was the most value I’ve gotten out of a proof of concept ever. I connected my data and was immediately up and running. From the start I could already see value.
‍_{— George Durzi, CTO, Amuse}

The possibilities that Sigma’s powerful, spreadsheet-like interface opened up for the team were immediately apparent to everyone that saw the demo. “When I showed the first analyst,” recalls Durzi, “I blew their mind when I brought in our sales data, logistics data, and easily joined them on the ticket in Sigma. He could never do that before.”

With their data stack now complete, the first order of business was getting a 360 degree view into their delivery costs and identifying areas for improvement. “Scheduled deliveries are really what sets us apart,” explains Durzi, “Since implementing Sigma, we have been able to quickly get insights into how a delivery day went and tweak our labor planning, increase capacity in different areas, identify optimal delivery windows, and better allocate resources.”

But it isn’t just company leadership that is benefiting from this data. Across the organization, teams are using Sigma to make data driven decisions that improve efficiency. Durzi explains: “We have a worksheet of every delivery, every window, and every area, and they are all open in every depot. The best part? None of it requires any dev work. Our operations team is in it every day.”

“Every team at Amuse is analyzing data in Sigma,” says Becker. “Finance, operations, marketing, analytics, central ops — it’s a lot of people.”

The Results

A Complete and Accurate Window Into Operational Costs Reduces Costs Per Delivery by 30%

With a complete and accurate window into their operational costs, the team at Amuse was able to reduce that critical metric, cost per delivery, by a whopping 30%. “Having a mature and cloud-native data tool like Sigma to give our employees access to real-time data has been a game changer for us,” says Durzi.

“The ability to get just a quick recap of the previous day like total deliveries, completed deliveries, delayed deliveries, and successful deliveries within its promised window used to be a very manual process. Now I get an email every morning that says ‘Yesterday’s Recap,’ and it’s a dashboard in Sigma. And if I see something I want to know more about, I can easily click into the underlying data, do some calculations on the fly, and find the answer right then and there.”

In addition to reducing operating costs, Sigma is helping teams across the organization achieve significant business outcomes. Becker’s sales and marketing teams are using Sigma for cohort analysis, scenario modeling, and building sophisticated customer 360’s that are improving conversion rates and reducing acquisition costs.

“On the revenue side, we’re dialing deeper into channel specific CAC (customer acquisition cost), cost per repeat order, cost per order, and other customer retention metrics. We’re building views of which channels customers are coming in through, which promos are acquiring them, which the offers were, and more. And we’re using Sigma to do that.” The results are already impressive: CAC has been reduced by 20% so far.

At the end of the day, what really sets Amuse apart from the competition is that they are a people-focused company. On their Linkedin page, Amuse highlights some of their key values – trust, reliability, and customer obsession. Those values are shared by the team here at Sigma.

Reflecting on their journey with Sigma, Durzi summarizes the relationship this way:

“We truly enjoy working with you. Sigma has been a great partner. I feel like we are listened to and heard and it’s great.”