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Sales Analytics Strategic Planning

An strategy first looks at the current state, defines the ideal state, then outlines the strategic steps that must be taken to build a pathway between the current and ideal.


Current State Analysis

The current state analysis includes:

  • Sales Team
  • Sales Tools
  • Corporate Objectives
  • Sales Objectives
  • Reporting Cycles
  • KPI's

Most sales teams start out using a combination of some type of CRM program and MS Excel reporting to manage key information such as sales forecast, lead volumes, and customer interaction.

Adopting a systematic approach to transform from using these basic tools to analytics tools that deliver real time insight and competitive advantage is generally gained over three steps.

Step One - Trusted Data

Uses Excel spreadsheets and standard CRM reports to provide core information to executives and managers, to understand the complete view of the current state of the business. Gaining a 'complete' view is the pivotal progress from a set of disparate reports, each from separate systems.

At this first stage, individuals now have information based on data they trust, that is timely and is available on demand.

This data can be presented in a combination of graphical dashboards and tabular detail reports. They can be defined by sales channels, roles, products or any other perspective.

This helps managers and executives develop a greater appreciation for and desire to support data integration and quality programs to ensure their information can be relied upon iwth confidence.

Stage Two - Evidence Based Decision Making

Now that users trust the data, they can align everyday and strategic decisions around the insights gained from the data.

The outcome is that decision accuracy improves as the availability of relevant data improves. This is an important step to driving the use of business intelligence within the various business contexts. It also supports increasing need and capability for ad hoc data analysis.

No longer are decisions made on the perspectives of multiple individuals, but on real evidence. Analysts have access to robust Ad Hoc tools that allow them to answer questions without the need to write code or request IT to create a new report.

By framing up analytics data sets to be context sensitive and relate to the actual decisions that must be made by managers, BI becomes the decision platform of choice very quickly.

Step Three - Presightful BI

Leveraging upon the learnings of stages one and two, the business can establish key performance indicators to manage their key result areas, and actively mine historical data to predict future outcomes. This transcends the ability to gain insight from historical data, to use that data to project future presight.

Predictive analytics is used in sales for:

  • Demand Planning - based on market drivers to ensure sufficient but not surplus stock is on hand in sales channels
  • Portfolio Management - determine the most profitable entry and exit points and optimize product pricing throughout the product lifecycle
  • Sales Forecasting - based on historical win rates
  • Customer Lifetime Value - from mining data to prioritize accounts
  • Campaign Mangement and Optimization - mining the results of campaigns to continually adjust investments to generate the greatest return.

The key development in sales solutions today is in combining:

  1. Customer Relationship Management [CRM]
  2. Sales Analytics
  3. Social Interaction

into one integrated solution that provides for managers to analyse performance and made decisions about future activity within a single environment.

Next: Using Sales Analytics Tools

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