The Basics You Need to Develop a Sales Analytics Solution That Benefits the Whole Business

Why Is Sales Analytics Important?

Whether in a B2B or B2C environment, sales metrics are viewed as the leading indicator of organizational health. Especially in times of economic uncertainty, the ability to get a good pulse on sales is critical; you need to know how sales are trending and what can be done to maximize profitability.

Companies that have their sales data in order with the ability to perform sales analytics have a leg up over their competition. They can better understand their customers, gain a more accurate view of the sales pipeline, know where to focus to maximize ROI, and identify cross-selling and upselling opportunities.

Start With a Sales Analytics Strategy

Building out your sales analytics solution should be done intentionally with company goals and end user needs in mind. It is not enough to tack on sales metrics to your monthly reports. Sales activities should be looked at holistically which is best done through a sales analytics platform.

To ensure a sales analytics solution that is useful and widely adopted, keep these tips in mind.

1. Know Your Audience
   
   It’s critical to understand the users of your sales reports, all the way from field sales to corporate sales analysts to field sales management to executives. Each of these user groups will have distinct and overlapping needs from a sales reporting tool. With knowledge from these audiences—the questions they’re asking, the data that represent answers, and what would help them—a comprehensive solution can be built. Get their involvement up front and avoid the mistake of having one representative speak for a different group.

2. Stop Using Excel
   
   Too many organizations try to do too much in Excel, and it creates a significant risk for the organization. The potential problems are numerous, including:

• The possibility of changing the data—whether accidentally or intentionally
• Having multiple versions with different data
• Instability and slow performance of the tool, especially when working with large data sets. Analytics8 recommends modern BI tools such as Power BI, Qlik Sense, Tableau, and Looker which provide mature capabilities in presenting and visualizing data and empower end-users to do their own analysis.

3. Create a Central Hub
   
   Sales reporting should be centralized in a hub that’s accessible from anywhere—the corporate office, the field, or home. The hub may be within the tool itself (like a CRM) or within a company hosted portal or intranet, such as SharePoint. This central access reduces complexity and allows easy access to view and share data. It also serves as the single source of data which will eliminate frustrations around different data being used in different regions or departments. For sales teams, the central hub streamlines rep evaluation and makes it easy to compare reps across regions.

4. Lead Your Users to Action
   
   Seeing historical sales performance is obviously important. But a more mature level of reporting surpasses presenting information about the past (descriptive analytics) and helps the end-user determine what action to take in the future. This requires more than a single KPI or dashboard; you need a series of data points that the end-user can drill down into, manipulate, and ask a series of questions from. A modern analytics tool will streamline the journey to advanced analytics, providing the ability to generate insights based simply on the dataset.

How to Do Sales Analysis

With your sales analytics solution in place, here’s a starting point for where and how you should focus your analysis.

1. Start With the Basic Sales Data Points
   
   No matter the type of business we’re working with, there are a common set of data points that belong front and center in a sales analytics solution:

• Product/Service data: data on the product being sold, the quantities of that product, and its price
• Sales channel and customer information data: often used along with the cost of the product
• Organizational data: such as the sales rep, their placement within the sales organization, along with the organization or hierarchy of the product

2. Pivot Your Data
   
   Sales data should be “sliced and diced” from multiple angles, or “dimensions” as we refer to them in the analytics world. Common examples of sales dimensions include product, profitability, geography, date range, and sales rep.

• Instead of looking at just the quantity of product sold, you could look at product mixes and which products sell best alongside other products. You would also want to look at profitability against quantity and see how different geographies compare in sales. If sales are lower in one region, you can compare the sales against the same time period in previous years to understand if sales are actually poor based on historical trends.
• For a sales team, you can compare overall sales performance by sales representatives, but it would be more beneficial to understand individual trends—is one rep performing better this quarter? If so, add the product/services dimension to understand if certain products make the company more money per sale. Add a geography dimension to know if certain markets are hotter than others and perhaps realign sales territories.

3. Look for Trends
   
   Analyzing sales data for a point in time is rarely informative. However, seeing how sales data are changing over the course of time may bring new insights. Increasing sales are good but understanding factors behind trends (and outliers) is where your organization can benefit.

4. Pay Attention to Top and Bottom Performers
   
   One of the most common requirements in sales reporting is seeing top performers by sales quantity, such as the number of units sold, or by profitability. This can be applied to a company’s products, sales reps, and geographies. A corollary to this is seeing the bottom performers to get an understanding of which products, reps, and geographies are actually costing the company.

5. Measure Performance Against Plan
   
   Encourage accountability from sales and leadership by comparing sales performance against organizational goals. Knowing whether sales goals are on target impacts so many other organizational goals, such as hiring, staff raises, and other investments. This should be a primary KPI.

Sales Analytics Drives All Around Better Decision Making

Having visibility to sales performance and profitability allows a business to respond to a quickly changing economic climate. But, aiming to provide the insights that help the sales team actually sell better is icing on the cake. When sales teams succeed, the whole organization becomes stronger.