CRM Implementation and Opportunity Pipeline Analysis

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Case Study

CRM Implementation and Opportunity pipeline analysis

the Challenge

The client was a small UK-based company that installed and tested safety equipment used to clean and maintain buildings. For example, buildings with large glass facias require constant cleaning and maintenance, and to achieve this safely there are a number of items necessary for the personnel that perform this function. The directors of the company were essentially operating by instinct and gut feel.

In this particular case the company did not even use a CRM system. Various spreadsheets were used to keep track of leads and opportunities.

the Solution

There was a three-part solution:

  1. Assist with the implementation of a CRM solution – in this case GoldMine. This involved a number of tasks (excluding the actual installation of the software and the setting up of the infrastructure):
    1. Setup of GoldMine CRM solution in order to track leads and opportunities to facilitate information that the directors wanted
    2. Management of change to embed the new solution within the organisation
    3. Creation of data feeds to a Microsoft SQL and Microsoft Analysis Services platform
  2. Installation and setup of Microsoft SQL Server and Analysis Services (SSAS)
  3. Transformation of data to information:
    1. Databases were set up
    2. Incoming feeds were created to extract, transform and load the data
    3. Analysis Services cubes were set up in order to transform the data into effective and trusted information
    4. Methods of querying the Analysis Services cubes were implemented using Excel
    5. Automatic production of reports for Directors and Managers

the Results

For the first time it was possible to measure and articulate some critical parts of the opportunity pipeline. For example:

  • Number of leads in the system at any one time.
  • Number of opportunities in the system at any one time.
  • Conversion of leads to opportunities:
    • Conversion time
    • Conversion rate
  • Number of leads required to achieve a certain number of opportunities
  • Conversion of opportunities to sales:
    • Conversion time
    • Conversion rate – number of opportunities
    • Conversion rate – estimated revenue vs sales revenue
  • Number of opportunities required to achieve a certain number of Sales
  • Estimated revenue required to achieve a certain level of sales
  • Estimated sales at given intervals based on CRM history
  • Matrix of win/lose criteria:
    • Why were opportunities won
    • Why were opportunities lost
    • Strengths and weaknesses
  • And more..

The customer was left with the ability to measure and understand some critical aspects of the opportunity pipeline. This made it possible to change their marketing and sales strategy in order to improve closure rate and ultimately revenue. It was also possible, increasingly accurately through time, to estimate income at certain intervals (i.e. 1, 3, and six months).

 

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