With Stripe Sigma, businesses that might struggle to put proper data infrastructure in place no longer have to worry about juggling a ton of data tools. Besides giving companies the ability to generate customized reports, Stripe Sigma is also cloud-based, which means merchants can rely on Stripe to store and move all of their data.
Stripe Sigma is an in-platform data tool available to all Stripe merchants for an additional fee. Unlike the native data analytics tools packaged with other ecommerce and payment platforms, Stripe Sigma doesn’t rely on boilerplate reports. Instead, Stripe Sigma includes a SQL query editor that makes the act of parsing data simpler and more collaborative.
In this blog post, we’ll talk about Stripe Sigma and everything good it brings to the table for data analysis, while also taking time to discuss scenarios where Stripe Sigma’s approach to data falls short.
Stripe Sigma offers dynamic in-platform data analysis
There’s no denying that Stripe Sigma has many great features. Compared to other native data analytics tools, Stripe Sigma gives business teams a unique suite of features that allow for truly dynamic data analysis from inside the Stripe platform.
Pro #1: Stripe Sigma takes a SQL-first approach to analytics
Stripe Sigma doesn’t rely on boilerplate reports that are little more than glorified spreadsheets. Stripe Sigma includes a SQL query editor that offers truly customizable reports.
The beauty of this setup is that any team member with the right permissions and basic knowledge of SQL can convert any question they have about their customers into a SQL query and then use it to gain actionable insights into business performance and customer behavior.
Pro #2: You get customizable and collaborative reporting
Another feature that sets Stripe Sigma apart from other proprietary data analysis tools is the ability to share customized SQL queries across teams or departments. This is a radical departure from the way other payment and e-commerce platforms handle native data analysis.
Businesses on the Stripe platform have the opportunity to transform data analysis into an area of operations where the entire company participates, rather than one or two lonely data analysts constantly inundated with requests for data from different departments across the company.
Pro #3: You can parse business data from the merchant dashboard
While many other payment and ecommerce platforms bury their data tools behind an admin panel on the back end, Stripe Sigma places data analysis at the center of business operations because it’s integrated directly into your Stripe dashboard.
Stripe Sigma is available to all Stripe merchants (for a fee). It gives anyone in the company with the right permissions and basic knowledge of SQL the opportunity to mine and parse data to help any team or organization meet its goals.
Pro #4: ETL and data warehousing are both easier in the cloud
Finally, Stripe Sigma is entirely cloud-based, which means that at least some of your data infrastructure is already in place. Before you get too comfortable, you should know that some data tooling will be necessary. Still, Stripe Sigma does make things easier if your business needs to pull data from separate cloud platforms and other systems.
For small and medium-sized businesses just starting to get their customer data figured out, there are real benefits to Stripe Sigma’s cloud-based approach to data. It’s cheaper and more cost-effective, it’s easier to set up. It requires much less work to maintain, and there’s (almost) no need to worry about data pipelines or automated ETL applications.
Stripe Sigma is great, but has some blind spots
What’s interesting about Stripe Sigma is that so many of the things we liked about it (the SQL query editor, the collaborative tools, and the ease of cloud-based data warehousing) could also be seen as drawbacks.
The biggest problem with Stripe Sigma is that while it has some unique and powerful features, a robust data stack will perform all of the functions of Stripe Sigma and still be the better data analysis option for most smaller Stripe businesses.
Con #1: Data analysis may not be not for everyone on the team
Stripe Sigma’s collaborative elements are great, especially how they put real-time data analysis within reach of almost any member of a team or department. However, Stripe Sigma’s collaborative features might not be a good thing for some Stripe businesses. The SQL query editor is great, but it’s useless to anyone on your team who doesn’t know SQL.
The other issue is that for some Stripe businesses, handing out data analysis permissions to just anyone with a question about customer behavior isn’t the safest or most constructive policy. Plus, some less-experienced team members might struggle with the finer points of data analysis, especially the push-and-pull that comes from synthesizing numbers and real human behavior.
Con #2: A BI tool can inject business logic into data analysis
Data is messy. Stripe Sigma can help, but synthesizing raw data about human behavior into meaningful insights is one area where a BI tool has the clearest advantages over a narrow proprietary analytics tool.
The most significant advantage of a BI tool is that it can be used to ground data in current events, industry-specific metrics, and other forms of predictive analysis. The other benefit a BI tool will have over Stripe Sigma is that it allows teams to create consistent and practical metrics to track their business objectives.
Con #3: Stripe Sigma’s analysis is narrow in scope
The big problem with any proprietary data analysis tool is that the data it provides is limited in scope and shouldn’t be relied on in isolation. Stripe Sigma, unfortunately, is no exception here. If you want to deploy a robust data analysis regimen, would you rely on a tool like Stripe Sigma alone?
If you’re trying to figure out where, or how exactly, Stripe Sigma fits in with other data tools, take a moment to think about everything you could learn about your customer base if you used Stripe Sigma alongside a CRM platform like HubSpot, a BI tool, or Google Analytics.
When you consider the fact that Stripe Sigma provides only a narrow slice of data, the advantages of connecting it to a BI tool or another data source are obvious.
Con #4: A BI tool would also eliminate the need for data tooling
The other problem here is that one of Stripe Sigma’s primary selling points is that because it’s a cloud-based application, it eliminates the need for costly and time-consuming data tooling. This might be true, but for many smaller Stripe businesses, a BI tool or modern data stack already provides a more efficient workaround to expensive on-premises data infrastructure.
Seen in this light, Stripe Sigma’s cloud-based data warehousing capabilities are a wash.
Get more value from your Stripe data
If you’re a Stripe merchant and you’re trying to get a handle on your data analysis infrastructure, Stripe Sigma is a great place to start. It has some innovative features that set it apart from other proprietary and in-platform data tools. But for truly comprehensive data analysis, Stripe merchants shouldn’t rely on Stripe Sigma alone.
To leverage Stripe Sigma effectively and meet your business goals, you’ll need to connect Stripe Sigma to other data sources, like CRM platforms, BI tools, or Google Analytics. If you’re a Stripe Merchant and you’re ready to integrate Stripe Sigma with other data sources, consider a cloud-based data platform like Panoply.
Panoply provides Stripe merchants with code-free data integrations and automated data warehouse configurations. Panoply also connects to all major BI and analytical tools. If you get confused or need a little extra help with the onboarding process, our industry-leading technical support will have you parsing data like a boss in no time at all.