Building Your Sales Analytics Strategy: Part 1 [The Importance of Data Accuracy]

This is the first of the SalesQuants 4 part series depicting the benefits of building a cohesive sales analytics and reporting strategy. The same beautiful sales data that would otherwise collect dust in daunting Excel files could very well be the defining competitive advantage that sets your sales team apart from the pack. You’ll notice a theme of accountability, reliability, and consistency in our recommendations for best-practices. Our research and experience in the field of sales analytics has made it clear that these are critical indicators in determining the extent of the benefits and latent success a sales team could derive from their sales data.

This week, our focus lies within the importance of Data Accuracy. What good is keeping a record of sales data if the the numbers are telling lies? A cooked book is a bad look, and a thorough waste of everyone’s time.

 

Standardize metrics and measuring parameters across entire organization.

Getting everyone on the same page is a crucial first step in ensuring the quality of the sales data. Mid to large sized companies typically have multiple sales teams, multiple selling processes, and/or multiple forecasting requirements.  That being said, there are certainly organizations in which each of these groups may have their own respective interpretation of various KPI’s relating to the sales cycle.  For example, a “Commit” deal for one business could imply a deal has a 90% chance to close, while a “Commit” deal to the group next door could be interpreted as having a 70% chance to close.  If everyone’s not on the same page, then company-wide reporting/analytics loses its integrity and accuracy. If these are lost, reliance on any one group’s sales data could spell trouble when it comes time to make the big decisions.

 

Discover insights that would go unrealized without intensive reporting/analytics.

Sales people are in the business of… selling.  They are not in data analysts. They make the data. They aren’t spending hours per day trying to extract key insights from the data they create.  If the price of a certain product consistently lowers each month for clients in the state of Illinois, for example, sales folks may not be likely to realize that. They shouldn’t be expected to. However, with a robust sales analytics campaign in place, these seemingly subtle changes should be easily detected. Once these type of trends make themselves known, it’s the sales leadership who will proactively take action to investigate and remedy the situation. Let the sales people worry about… selling.

 

Replace generalizations with concrete data as data is sliced to reveal trends and purchasing triggers.

Generalizations are dangerous. Generalizations leave room for assumptions and errors in understanding. There are far too many sales leaders who speak in general terms when using approximations.  For example, one sales leader claims with high confidence that 85% of Commit deals close while 40% of Best Case deals close.  The entire business universally accepted his estimations are the truth. Don’t do that.  An analytical effort was launched to uncover the true percentages.  The study revealed that 50% of Commit deals and 15% of Best Case deals actually closed.  After proving the accuracy, easily derived through analysis of well documented historical sales data, the organization can start using the realistic 50% and 15% percentages as the source of truth, and focus their efforts on improvements where they actually exist.

 

Identify easily top and bottom performing products/regions/managers/reps.

For sales organizations of any size, tracking the performance of every rep, product, and manager is undeniably overwhelming. There’s a lot of there! Keeping an accurate track of this much data for an entire company is unrealistic and unnecessary. Many key insights can get lost and can drown in the sheer quantities of data.  Through launching a robust sales analytics campaign, however, you’d then have the ability to automate this type of basic reporting. This way you can recognize those top performers and bottom performers, give them their time in the spotlight, and make decisions accordingly without needing management to exert any effort at all.

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