For decades, the sales report has served as the bread-and-butter of sales management. Sales teams rely on sales reports to meet their sales goals, while the company’s key stakeholders and revenue leaders review sales reports monthly, quarterly, and annually in order to make informed decisions for the company’s future, including how to allocate investments and plan growth.
While the data and analysis compiled in the reports remain invaluable to the decision-making process, the reports themselves have become obsolete. Thanks to technology, there’s a new, much more efficient and effective way for sales teams to collect and review important data.
What is a sales report?
First, let’s define a traditional sales report. In a nutshell, sales reports provide an analysis of a company’s sales activities within a particular time period. Produced monthly, quarterly, and yearly, as well as ad hoc to satisfy a specific business need, sales reports contain a variety of sales metrics and data, such as:
- Total revenue
- Sales volume
- Deal size
- Number of deals in the pipeline
- Sales velocity (length of sales cycle and how long each opportunity stays in each stage)
- Number and type of new customers
- Conversion rate
- Customer acquisition costs
We'll provide some sample sales reports below.
Why is sales reporting important?
Sales data and analysis are critical to the strategic management and success of the entire sales process. By tracking sales metrics, sales managers can see where the company’s success lies and understand what drives sales in those areas, as well as identify opportunities to boost sales performance, and scale as the business grows. By analyzing such sales data, sales managers can also more easily spot at-risk deals to halt slippage, drive predictable revenue, and support more accurate sales forecasting.
Types of sales reports
The type of sales reports your revenue team uses on the sales metrics and key performance indicators that matter most to your sales process and methodology. Each report should provide actionable insights for revenue leaders, supported by the numbers. The last thing you want is your sales ops team pulling data just to have stats on a page. Sales report examples include:
Sales Key Performance Indicators (KPIs) Report: This sales report serves as an overview of the revenue team’s main goals. A KPI report might include:
- Total revenue
- Revenue by product or product line
- Net new logo revenue
- Renewal revenue
- Year-over-year growth
- Average selling price
- Rep attainment
- Deals slipped
This list can (and should) expand beyond these sales metrics However, for any report, the critical piece of the puzzle is whether or not the data is easily digestible, accurate, and actionable.
Creating a sales dashboard so the data from your report can appear side-by-side with up-to-date and accurate data gives revenue leaders the best opportunity to define their sales strategy in real time.
Sales Pipeline Coverage Report: This sales report tells sales leaders how much revenue exists in pipeline and whether there is enough coverage to hit the quarters quota:
- Total revenue in open opportunities
- Total revenue won
- Gap to quota
- Pipeline coverage
- Average length of sales cycle
- Average contract value
- Historic win rate percentage
- Sales stage conversion rate
Best-in-class revenue teams will also examine out-quarter pipeline metrics for even greater visibility into the future, and to drive still more predictable revenue. The key to useful pipeline coverage metrics is understanding historical conversion rates by segment, territory, sales stage, and more, so you can accurately predict where you’ll land based on the pipeline at hand.
Sales Performance Metrics Report: Sales activity data is every touchpoint made by your revenue team with a prospect or customer:
- Number of emails sent
- Number of meeting scheduled
- Number of files sent and opened
- Number of calls made
Sales activity data is notoriously hard to come by because it requires that sales reps manually log numbers into CRM. However, new sales automation technology eases this pain point by automatically harvesting and associating sales activity data with the proper accounts.
When leveraged correctly, activity data not only illustrates how each rep performs, but also whether the prospect or customer is engaged in the deal or not. Sales activity data is a key data point for inspecting deals and identifying which accounts could use some love and where reps should spend their time.
How to build a sales report
While the data and analysis contained in traditional sales reports is crucial for sales success, the way sales reports have typically been generated has become sorely outdated. Two of the most common ways to create a sales report is via an Excel spreadsheet or by exporting data from CRM.
That sounds pretty straightforward, right? So what’s the issue?
Static sales reports aren’t accurate. By the time they are generated, validated, formatted, and shared, the data is likely stale, meaning sales leaders are relying on old and possibly inaccurate information to assess the status of sales and make crucial decisions. And that’s assuming the data entered into CRM manually is accurate and up to date in the first place.
It’s time consuming. Pulling data day in and day out forces sales operations teams to spend more time auditing manual one-off data pulls instead of focusing on a longer-term strategic roadmap, such as process improvement, tool adoption, and scaling systems. Sales managers may make requests in a time frame that just isn’t feasible.
Audiences are changing. Sales metrics shouldn’t just be looked at by sales and revenue leaders. Their counterparts across the entire revenue operations team in marketing, client success, and demand gen should also have their finger on the pulse of all the same metrics, but sales ops is often doesn't surface insights for those departments.
The next evolution of sales reporting
Thanks to technology like automation and AI, sales reporting can now be streamlined, highly accurate, and done in real time. Further, AI allows sales teams to glean deep insights into the sales pipeline, and the sales process as a whole, for better forecasting accuracy as well as improved sales pipeline visibility for future growth and investment decisions.
Clari streamlines the data entry process by automatically capturing data from CRM and reps’ emails and calendars, ensuring all information is accurate and up to date, with no missing pieces. Then, Clari’s AI analyzes the data to produce helpful sales metrics like CRM score, opportunity scoring, sales activity, deal insights, and pipeline coverage to help sales reps and managers save time, focus on the right deals, improve forecast accuracy, and plan better for the future.
There’s no one-size-fits-all, silver-bullet sales report, which is why Clari pulls all of these metrics and analytics into a cohesive sales dashboard that is flexible and filterable by any user, from rep to sales leader.