Sales Analytics: Focusing on Business Needs Ahead of Data Requirements

Author: Mark Ippolito
5 / 10 / 2012

Among sales and marketing leaders we meet, one of the hot button topics we hear about most often is the subject of sales analytics. Often the symptoms are heard ahead of the root cause:

  • “My analyst team keeps generating reports, but few of them are actionable.”
  • “There are too many spreadsheets with conflicting numbers and we wind up with multiple versions of the truth.”
  • “My instincts are telling me this is the right decision, but I can’t get my hands on the right data to support the decision.”

A recent client engagement presented us with these very real questions to resolve. A software company with a sales force selling multiple products experienced rapid growth and quickly outgrew its “start-up” ways of management.  The leadership team needed to understand how they could efficiently scale the business without a parallel increase to the cost of sales.

Rather than starting with a deep dive into the pain points (data integrity, report accuracy/relevance, analytics process, etc.) our approach was to first identify and understand the key business questions we were trying to answer in context of the company’s overall objectives. Only once we have a firm grasp of these objectives could we then move forward and develop a roadmap for delivering improved business intelligence.

Our investigation centered in identifying the specific questions our client needed to answer in order to affect performance. By category, they were: marketing lead performance, sales forecasting and establishing performance benchmarks for individual performers and territories.

To isolate the relevant data to address these questions, we focused on the client’s sales process, along with the key actions taken at each step, to determine whether or not key information was being captured.  To do this we isolated the business drivers, actions required and related business process. A flow diagram was developed as follows:

Once the business drivers were defined, we were then able to initiate the data assessment to determine whether data mapping to each driver was available. To our delight (not to mention the client’s!) the data was already there; but we recommended a few process changes to enhance data quality and designed a data infrastructure to support ongoing reporting and analysis.

After creating the data infrastructure, we used data visualization software fromTableau Software to construct dashboards for each of the four quadrants of business processes identified: Marketing Leads, Sales Activities, Sales Pipeline Management and Revenue Performance:

In Tableau each quadrant has the capability to quickly do a deep dive to answer questions specific to each business process. For example, in isolating Market Lead effectiveness, we can quickly expand the dashboard to reveal Lead Status, Lead Dis-Qualification, Leads by Product Type, Marketing Source and Geo:

Key Takeaways: When faced with the challenge of providing information to your organization that delivers key insights and empowers informed decision making, follow these guidelines:

  • Invest time up front to consider your analytical needs in the context of your overall objectives before investigating data integrity, systems, tools, etc. Your aim is to deliver information that will have the greatest impact on your business, which requires a clear understanding of your business goals.
  • Identify the key business questions you want to answer.  Hint: The more specific each question, the better. For example:
    • Good: How are our marketing leads performing?
    • Better: How are our marketing leads for Product Y performing in this territory?
    • Best: How are our marketing leads performing for Product Y, by each sales rep (or partner), in this specific territory, over time?
  • Map your business questions to the business process(es) that will impact the outcome for each. Since your goal is to provide insights that will have the greatest impact on your business, do not be afraid to de-prioritize those questions that will not drive specific, high value actions.
  • Evaluate the data being captured and data design structure to ensure that the information needed is accurate and complete. Where data is missing or incomplete, flag requirements for improvement.
  • Develop the reporting solution, conduct QA/testing and prepare users for adoption.

The path to effective sales analytics starts with asking the right questions.

This post contributed by Mark Ippolito, Sr. Manager and Practice Leader, Sales Optimization

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