How Spacious Saved Time, Resources & Boosted Revenue with Panoply

The Company

Spacious calls their business a “future of work” company. The innovative company developed a network of working spaces. Their concept involves making available real-estate properties such as restaurants (that are otherwise vacant during the day) available for working during regular business hours.

The Challenge

Like most modern startups, Spacious has many systems for their customer data. Their data comes from many sources including Stripe, Intercom, Google Analytics, Facebook ads and their own MongoDB instance where they track user engagement. 

Before Spacious implemented Panoply, their multiple stores of data were living everywhere across their organization. Most problematically, this data existed in little separate silos. The business shared that it was "incredibly frustrating" to run any type of analysis. 

Prior to implementing their cloud data warehouse, Spacious was manually exporting data and looking at everything individually in spreadsheets. No dataset could talk to or be compared to one another.


The Solution

The CTO of Spacious knew early on that they needed a rock-solid data pipeline to power insights for their business. They chose Panoply as their data stack's foundation. They set up Panoply in a way that allowed them to combine all their data sources like Stripe, Intercom, Google Analytics, Facebook Ads and their MongoDB instance. In sum, they track user engagement, subscription data and accounting data.

Panoply powers their main analyses which focus on the customer side and the supply/space side. For customers, the key metric they monitor with Panoply is customer acquisition cost (CAC) vs LTV (lifetime value of a customer). Spacious' business depends on keeping that ratio in check, because it tells them their profit generated per member versus the cost we incurred in acquiring that customer. 

Startups or any small business doesn’t have the time, cash or resources to spend on a data engineer or data team. We love having a solution that means we can get our data all in one place without having to involve engineering. Also, it lets me move with the speed I need to, which is key to my success in this job.

The Results

Spacious has a complex way of allocating revenue to different partners across our network and before Panoply, they had many many hours of data exports, manual file checking by every team within Spacious. Now with Panoply, each person uploads their data into Panoply easily, and with a little SQL, their data analysts can generate revenue numbers in a matter of minutes, where it used to take hours. 

Panoply has changed the game by eliminating time consuming manual processing. Justin Mulvaney, their data analyst reports that before Panoply, manual work "Sucked a week of our CEOs and Head of Operations’ time. It literally took up 25% of our executives’ time. As a data analyst, I was able to prescribe a much easier way with Panoply at the center."


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Industry Ecommerce, discount vouchers Team Data science and analytics Location New York, NY
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