Custom Business Analytics Without Engineers or Analysts
Build your no-code data stack in the cloud
Did you ever feel constrained by analytics capabilities of the business software you use? Tracy did.
Tracy leads sales operations at BillSpark, a billing software startup mainly serving Insurance companies. Her team uses Pipedrive, a modern CRM with nice UI. It is a great tool and the team enjoys using it (as much as you can enjoy CRM).
Over time, Tracy realized that Pipedrive reporting capabilities do not match her needs anymore. While they show basic charts like revenue over time and conversion rates, it cannot do calculations like lead cohort analysis or conversion rates by team.
Tracy was looking for a CRM with better reporting. People recommended Salesforce which has much stronger data visualization capabilities. Salesforce UI is not great: it is slow and looks like it was built in early 2000th (well, it was), not to mention time and cost of switching CRMs.
There was no good choice. Tracy did not know what to do.
While she was struggling with the tradeoff between user experience and reporting capabilities, Patrick, a sales ops leader from another startup, showed his dashboards. They had everything Tracy needed.
“Can you give me contacts of the person who built this for you? How much would it cost?” - asked Tracy.
“What person?” - replied Patrick - “I built it. Or, rather, it built itself. It’s all out-of-box cloud apps. I only built the charts I use - that’s all.”
He proceeded to show Tracy the cloud analytics stack he assembled. A week later, Tracy built all the charts she needed and more. They were connected to her Pipedrive instance in near-real-time. She never used built-in CRM analytics after that.
The cost? $350/month for software subscriptions and about 7 hours of her time. When her company grows, they may hire a full-time analyst, but for now this will do.
Cloud Analytics Stack
If you still use the same tools for doing the work and for analyzing it, welcome to 2021!
In the last few years, there was an explosion of user-friendly cloud analytics tools: Data Warehouses, ETL, and BI software. If you don’t know what some of this means - hold on - it’s simple. With these tools, anyone can build business analytics stack without being a data engineer or an analyst, and as cheaply as a couple hundred dollars per month.
The simplest version of the cloud analytics stack looks like this:
An ETL tool pulls data from the tools you work in and puts it into a Data Warehouse (just a fancy name for a database). On another side, Data Visualization Tool connects to your Data Warehouse and allows you to query data and display it as charts, dashboards, and reports.
A cool aspect of this is that each component is replaceable. You can switch your CRM while keeping ETL, Data Warehouse, and Data Visualization, you can switch ETL tool while keeping the rest, etc.
Building It Yourself
Let’s take a look at the stack that worked for Tracy. Yours will work in a similar way, even if you use other tools.
Tracy uses Pipedrive as CRM, Stitch as ETL tool, Panoply as Data Warehouse, and Chartio for data visualization. All these tools are friendly to non-technical users - a very important quality for someone who does not have engineers in the team.
Connecting them all together consists of a few well-documented steps:
The result:
You don’t have to use the same toolset. There is a wide choice of:
Take your pick (or ask me if you are not sure). Regardless of which tools you choose, you will find detailed step-by-step manuals for connecting them together.
Summary
You should not be limited by reporting capabilities of the enterprise apps you use. In most cases, you should not even try using embedded analytics - it usually sucks.
Build your cloud analytics stack. Connect an ETL, Data Warehouse, and Data Visualization tools together. You don’t need engineers or analysts to do this.
Set it up once, and use it for any applications your data sits in: CRMs, marketing automation, customer success, HR, or financial tools. Almost all of them can be connected to the stack described above without any code involved.
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