Big Data Sales Analysis in Less Than 10 Minutes
While scouring an enormous amount of your company’s sales data is likely not at the top of your to-do list, it should be. Simply put, what is not measured can’t be improved and this goes for your sales performance.
What is a sales analysis?
A sales analysis is an empirical examination of your business' performance that provides insights into the past, present, and future of your business.
Why is a sales analysis important for my business?
An effective sales analysis is a powerful tool that can help you forecast trends, identify weaknesses and opportunities for growth, and gauge your sales team’s performance.
How do I perform an effective sales analysis?
Collect the right data - Each time you process and record a transaction with a customer, the data collected from your customer is incredibly valuable. The more accurate, historical customer sales data you have at your fingertips, the better. Having sufficient quality and quantity of data is key to making informed decisions.
Ask the right questions - When working with large, complex data sets, losing sight of your initial goal is easy to do. To avoid this, ask the right questions and clearly define the goal of your analysis upfront. Asking yourself the right questions could look like this:
How effective are my sales representatives?
What are the primary characteristics of my repeat customers?
What are your best-selling products?
What is my rate of monthly sales growth? ((Current month’s performance - previous month’s performance)/100)
What is my lead conversion rate? (Number of leads that converted into opportunity in a given period)/(Number of leads created in this period)
Get started - If your data is contained in a CSV or spreadsheet with millions of rows, you will likely be unable to work with it effectively in Excel. Have no fear; this is where Gigasheet comes in!
Follow along as we dig into 1.8 million rows of sales data using Gigasheet
First, I will upload my file, a 329.5 MB CSV with 1.8 million rows of a toy company’s sales data.
Choose My Device, and then select the file:
Next, I will get a feel for my data using aggregations. I am specifically interested in determining how many unique values there are in the Account Owners, Territory, and Purchaser columns.
Despite my very large data set, I can quickly see that my data contains 755 unique account owners, representing 275 territories and 5 separate purchasers. Additionally, by sorting the Close Date column, I determined that the the range of close dates is 47 months (~ 4 years of data). Using the Percent Unique aggregation on the Next Steps column, I can tell that approximately 2% of rows don’t include next steps.
The 2% of rows that don’t include next steps makes me interested in analyzing this further to identify which sales representatives are driving this. Let's do so using groupings. First let’s group by the Forecast Category column, which shows me that approximately 6% of my 40,422 committed deals (with a value of $100,104,710) don’t have next steps.
Let’s continue to group by quarter and account owner and sort by % empty in next steps. That way, we can identify our account owner problem children who are driving the 6% of committed deals without next steps.
We can see that 33% of Devin Y. and Dominic E.’s committed deals don’t include next steps. Sales management is going to have to take action!
Now that we’ve identified our problem children let’s identify our stars. Let’s add a territories grouping, showing that New York, Los Angeles, and Dallas were the top three territories during Q2 2022 with $1.4 million, $1.0 million, and $0.6 million in committed deals, respectively.
We can further drill down and see that Nicholas R., Taylor E., and Jack L. were the top three account owners in Q2 2022 in the New York territory. President's Club, here they come!
In under 10 minutes without writing any code or queries, we’ve effectively performed multiple sales analyses on an enormous data set!
Want to continue analyzing this data set? Click here for the data grouped by account owner and here for the data grouped by territory. Or better yet, upload your own sales data and start analyzing it today!