Introducing some CRM Analytics Implementation problems
INTRODUCING SOME OF THE BENEFITS OF CRM ANALYTICS
We already know that CRM is in case you have forgotten to get a copy of series one of this book. But when we talk about Analytics, we talk about the analysis of data that the organisation have about their customers.
This will help them in meeting their customers in the right place with the right product and services.
Benefits from CRM Analytics
One thing you should know is that Data Analysis in CRM is a continuous process. Organisations have to continue to review their customer’s information and use the information gathered in evolving a well informed and balanced decisions about their customers.
Customers information as an integral part of CRM is always gathered front offices which are departments that have a direct relationship with the customers. As this information is obtained, they are systems that perform data cleansing, application rules and storing of information in the data repository.
The organisation needs to do some calculations in order to know whether they are making the right decisions. While applying calculations, the organisation needs to analyse if the rules are consistent across multiple channels. This need to be done in order to ensure that customer are satisfied irrespective of the channel that they have chosen to interact with the organisation.
You should also know that the organisation must be able to have established ruled that will regulate customers interaction and know the number of systems that each rule will govern in general.
Now the benefit ………
#1 Customer Retention
A sophisticated customer-centric data warehouse must be able to mirror customer’s that have left the Organisation’s lifecycle and join competitors chain.
It must be able to portray the reasons why they have left in order to prevent future attrition. The models must also be able to identify potential defectors among the current customers and prevent their movement.
#2 Sales and Customer Service
In today’s business environment, you should know that it is an organisation that is able to provide superior customer service that rules the market space. If an organisation have adequate information about their customer, they will be able to provide valuable information to their sales and marketing people which they can use to corner sales.
You should know that if the organisation have adequate information, it is possible for them to create software that will predict products that can be introduced to customers and prospects alike.
There are programs such as market basket analysis which analyses transactional databases to find a set of items that appear frequently together in a single purchase. This helps in increasing cross-selling ratio, product placement improvements and better layout of catalogues and web pages among others.
Business people know that marketing cannot thrive without adequate information about the prospects. When the markers have adequate information about the prospects, they will be able to execute retention campaigns, lifetime value analysis, trending, targeted promotion among others.
Indeed only by having a complete customer profile can promotion be targeted, and targeting dramatically increases response rates and that decreases campaign cost.
Direct mail costs are directly proportional to the completeness and accuracy of customer data.
#4 Risk assessment and Fraud Detection
An accessible customer base reduces the risk of entering into undoing risk. When an organisation have a database of their customers, they will be able to know the relationships between their various customers, they will also be able to identify customer’s carrying out fraudulent activities or using different names. An insurance company will also be able to identify customers with different types of policies more than expected.
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:
- Data lag
- Knowledge gap
- Incongruent data models:
- Business process stagnation
- Architectural misfits.
- 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.
- 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 affect changes in their contact address. This is likely to affect customers relationship.
- 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.
- 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.
- 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.
SUMMARY ON CRM ANALYTICS IMPLEMENTATION PROBLEM
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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