Benchmarking the Average Sale Value

Problem: Are deals and sales growing in a healthy manner?
For many Sales Leaders, some leading indicators of the efficacy of their team’s sales activities are the number of deals and the total amount of sales. But these figures can be deceiving.
If sales amounts hold rather steady, but the number of deals is rising, then it is taking more work just to run in place. Or if the amount is rising but the number of deals is declining, that may mean additional opportunities are being unrealized in favor of a few big deals. And big deals are great, but depending on a few big deals to meet the numbers can be risky.
A useful metric to track is the average deal size. That's why we built Sales Performance Intelligence, Account Performance Intelligence, and Territory & Segmentation Intelligence analytic packs for the Data Analysis Helper app.
Solution: Providing context to basic sales information
Data Analysis Helper’s premium add-on packs automatically measure this important information at the rep and organizational levels, for individual accounts, and across various territories and business segments. This average deal amount is calculated in real-time for both current and historical performance periods. This means it provides context when sudden changes occur as well as for the overall trend line.
Do individual reps or accounts need extra attention if falling behind the average? Or do higher performers have lessons that could be transferred to optimizing other situations? The same can be measured with certain territories or industry segments.
Having this more granular information brings fuller meaning to the top-line numbers of deals and sales. Specific opportunities and trends can be identified early on and addressed. Moreover, longer term benchmarks tell a story that could inform strategic decision making at all levels of the organization.
Want to see how Data Analysis Helper analytic packs can help your sales team?
Sales Leaders: Analyzing Historic Sales Performance for Forecasting | Data Analysis Helper Use Case Library | Recognizing At-Risk Accounts and Reducing Churn |