Some CRM Analytics implementation Problems

crm analytics implementation problems

Introducing some CRM Analytics Implementation problems


At the end of this lesson, readers should be able to identify some common CRM Analytics Implementation problems.


There are some problems that are an association with implementation of CRM in any organisation but the organisation must deal with these problems and overcome them if they want to succeed.   Some of these problems include:

  1. Data lag
  2. Knowledge gap
  3. Incongruent data models:
  4. Business process stagnation
  5. Architectural misfits.
  6. Data lag: In data analytics, the organisation has to extract data from operational CRM, transform it and load it into the analytical database.  This always creates a data gap as it affects the availability of relevant data.  This in a way can affect market plans and future actions of the organisation.  It will also affect day to day operation organisation.  It will also affect the day to day operation of the organisation as users have to search multiple data sources before they can understand customers better.

analytics implementation problems

  1. Knowledge Gap as part of CRM analytics implementation problems: At times when the organisation have the required data about customers and what they need to know about them, they always keep the information away from employees that relate directly with customers.  In such organisations, customers will have to call up to five numbers before they can effect changes in their contact address.  This is likely to affect customers relationship.


  1. Incongruent data Models as part of CRM analytics implementation problems: At times most analytics lack a central database where different data can be harmonized.  This at times can create a confused and inaccurate representation of customer analysis.


  1. Business Process Stagnation as part of CRM analytics implementation problems: Most analytics in CRM systems are designed to automate the best practices available to the software designer.  Revising the business processes and metrics underlying those systems is sometimes impossible often costly and difficult. The result of this is a CRM system that does not give the organisation option as far as customer view’s concerned.  Their interaction with them is also limited.
  1. Architectural Misfit: With the way some data structure of most CRM software is built, they are not that useful in Online Analytical Processing (OLAP), this does not allow the customer-facing employees to aggregate and analyse historical information.  Organisation solves this problem by creating data that enables the visibility of the effect of time.  Few CRM systems today are designed to effectively leverage data marts.

Note:  A CRM analytics program that meets expectation must deliver a unified platform for CRM and analysis.



At the end of this chapter, we have been able to discover that some of the implementation challenges include:

  • Data lag
  • Knowledge gap
  • Incongruent data models
  • Business process stagnation
  • Architectural misfit.


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