When it comes to sales data, there’s not much room for error. Sales data is the drumbeat of an organization and arguably among the most important to get right in order to understand its future.
Let’s dig deeper into what sales analytics looks like, some of the common metrics that organizations use, and the major benefits and challenges of this analytic practice.
Broadly speaking, sales analytics is the practice of generating insights from sales data. The techniques and tools associated with sales analytics may vary—it can include everything from advanced predictive modeling techniques to simple spreadsheets—but the outcome is always a clearer understanding of the data, which should be used to set goals, metrics, and a larger strategy for the sales team.
Sales analytics seeks to answer questions like, “What are the trends we’re seeing in our sales data?” or “What is leading to upselling/cross-selling opportunities?” or “How are our sales reps performing in each region?”
At any given moment, sales teams might perform different sales analytics that relate to different goals. For example, meeting the current quarter’s target may require a sales pipeline analysis to determine which customers are most likely to close. Or, in order to set targets for the upcoming year, sales teams might conduct a bigger-picture revenue analysis at year’s end.
There are several baseline analytics that sales teams need to perform in order to operate effectively. However, many of today’s sales teams are bolstering their sales analysis with more advanced initiatives that drill deeper into sales data. Some of those analytics efforts include:
Performing a sales data analysis just for the sake of it isn’t a worthwhile exercise. Sales analysts need to ensure that the purpose of their sales analysis—and the sales metrics they want to produce from them—are top of mind.
Sales metrics serve as a guiding light for sales reps, indicating exactly where goals are being met or falling short, and can help activate sales reps’ performance. Sales dashboards (which can be created manually, but more often are built through the help of sales analytics platforms) make these metrics visible to the entire team, and beyond.
Here are some sales metrics that many sales teams consistently track.
There’s no doubt that getting sales analytics right is important. Inaccurate metrics like customer growth rates or quarterly revenue may not impact the organization in the short term, but their long-term effects can cause organizations to overspend or invest in the wrong markets or verticals.
However, performing sales data analysis is not without its challenges. Some of the common challenges that organizations encounter when performing sales analytics include:
Successful sales analytics is an orchestration between sales analysts, sales reps, customers, business stakeholders, and many different systems and analytic tools. But at the heart of it is data. And without data that has been successfully cleansed and prepared for analytics, any analytic outcome won’t be trustworthy.
Data preparation for sales data analysis used to take hours, if not days, under traditional spreadsheet tools. But now, sales analysts are seeking out more modern options to prepare data for analytics: data preparation platforms, which can accelerate the overall data preparation process by up to 90%.
Trifacta has been routinely named the leading data preparation platform. Its machine-learning powered platform acts as an invisible hand during the data preparation process, guiding users towards the best possible transformation. Its visual interface automatically surfaces errors, outliers, and missing data, and it allows users to quickly edit or redo any transformation. Finally, it integrates with essential sales applications and can pull in data from anywhere within the organization.
Learn why organizations are incorporating Trifacta as a key part of their sales analytics today. Schedule a free demo from our team or get started right away with Trifacta on the platform of your choice.
