Delivering superior sales performance with predictive analytics

[david_jonker]

Can analytics be used to improve sales performance? The answer from Greg Petraetis, head of analytics, SAP North America, is a resounding "Yes".


When Greg first took over his team, which is charged with driving SAP’s leadership position in analytics, he had a theory that better intelligence about customers could help shorten sales cycles, increase pipeline, increase revenue, and grow SAP’s market share in analytics. In just six months that theory has proved to be true.

 

Laser-focused target lists

The starting point was focusing on the desired outcome. Greg wanted to give his team laser-focused, targeted lists to help them sell more efficiently. SAP data scientists had delivered similar lists before, but building the models to create them was time consuming. They needed to be able to work faster.

 

SAP Predictive Analytics software provided the answer, allowing them to shorten the time needed to build models from two weeks down to a single day. One of the models they built focused on customers’ propensity to buy business intelligence software.

 

Easily accessible information

The next step was making the propensity models accessible to sales. Greg knew that if they weren’t delivered in an easily accessible form, they wouldn’t be used.  To achieve this SAP Lumira was chosen to provide an agile data discovery tool designed to expedite data preparation and enable data to be presented in a visual, easily digestible form.

 

Today, sales people can easily select their accounts, see the high priority targets, and get a summary of the customers’ current business intelligence usage. Armed with a better understanding of customers’ environments, sales professionals and field support teams can have more relevant conversations about how analytics can help their business.

 

And, with SAP Lumira reports accessible from a laptop, tablet, or mobile phone, the adoption rate by the analytics team has been 100%, making it the most widely used propensity model to date.    

 

The results Greg and his team have achieved have been nothing short of remarkable. In just six months they have dramatically improved prospecting accuracy, business development focus, campaign management, and sales efficiency. Specific results include:

• A direct increase in sales and revenue


• An increase in qualified pipeline coverage greater than 3x 


• A 20% increase in average deal size


• More salespeople meeting or exceeding quota

 

Greg’s top tips for using analytics to increase sales performance include:

1. Don’t worry if data isn’t 100% accurate to begin with. As long as it’s directionally correct it will stimulate the right discussions. Data quality will improve naturally with use, feedback, updating, and iterative cleansing.


2. Drive excitement and adoption by making the application simple and engaging for the field, with easy-to-understand, interactive visualizations.


3. Integrate predictive analytics into the visualization and discovery process on a self-service basis so that new insights are intuitively delivered as the underlying data and attributes change. This will keep the insights from the application relevant.


4. Use iterative techniques to design and deliver a working app quickly and then adapt it based on user feedback.


5. Partner with IT through this process so that the users receive the desired self-service and flexibility while leveraging the business intelligence platform to maintain data governance, security, and control.

 

Learn more about how Greg improved sales performance and discover how other SAP executives are using analytics solutions to accelerate insight, anticipate tomorrow, and shape the future.