Analysing Major Analytical CRM Implementation Problems
There are some problems that are associated with the implementation of CRM in any organisation but an organisation must deal with these problems and overcome them if they want to succeed. In this article, I want to look at some of the major analytical CRM Implementation problems. Follow me as we look at that together in this article.
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 an 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: 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 form employees that relate directly to 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: 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: 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.
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.
Analytical CRM has much to do with capturing, analyzing and applying the knowledge about customers and ways to approach them, typically using databases, statistical tools, data mining, machine learning, business intelligence and reporting methodologies.
Customer knowledge consists of basic personal data such as Customer name, company name, business unit, business department, address, e-mail, phone, fax, gender, nationality e.t.c.
It also consists of sophisticated client knowledge such as client value, (annual revenue profitability), transactions (product description, revenue, profit, payment method, payment behaviour).
We also have internet communication (IP address, entry page, clickstream, visit length). Telephone communications (call centre, report data, sales calls). This client information can be captured from the processes (sales, services, finance, and marketing) and channels of the organization. Certain data can also be acquired from external sources such as market research data or address databases. It is often advisable to store all client data centrally for the organization to avoid multiple versions of the truth. Client data should be actual, complete, correct, unique and accessible for those who need it when they need it.
USAGE OF ANALYTICAL CRM
- Optimize marketing effectiveness.
- Customer acquisition, cross-selling, up-selling, retention e.t.c.
- Analysis of customer behaviour to aid product and service decision making e.g. product pricing, new product development.
- Management decisions e.g. financial forecasting, and customer profitability analysis.
- Prediction of the profitability of customer detection.
STRENGHT OF ANALYTICAL CRM
- Can help to find and explore useful knowledge in large customer databases.
- Classify customers, predict customers behaviour select market approach and channel.
LIMITATIONS OF ANALYTICAL CRM
- Certain Analytical CRM techniques can be complex to understand.
- It is still in an early stage of usage.
At the end of this section, we have discovered that:
- Analytical CRM has to do with capturing, analyzing and usage of the customers knowledge.
- Some of the knowledge includes Basic personal data, sophisticated client knowledge, internet communication and telephone communication.
- Analytical CRM is used to: Optimize marketing effectiveness, analyze customers’ behaviour, manage decisions and predict the profitability of customers.
- Some of its limitations include complexity and non-popularity of the applications.
ANALYTICAL CYCLE FOR CRM
Analytical CRM plays an important role in CRM. They are used segmenting and targeting customers. Most importantly, analytical CRM is used in justifying, planning and measuring CRM initiatives. In this chapter, we are going to look at how analytical CRM is been used to achieve these objectives.
Analytical CRM can be used to justify the introduction of an initiative or to drum support for an initiative by the executives. In formulating a CRM initiative, you should be able to determine by which you will be able to determine your success. One a particular initiative meet up with the standard that you have set for your Program, you can gather support for such initiative.
Such metrics that you can use include assessing customer satisfaction, customer profitability, customer retention, and sales and service delivery efficiency and effectiveness. You must also think of the benefits that is accrued to such programs. This must be presented to the executive management for approval.
CRM initiatives should be prioritized based on an evaluation of the organization’s biggest problem and greatest opportunities. You must be able to analyze your profitability based on product, channel and customers which is an essential part of the planning process. This will help you in making decisions as regard resource allocation, product development and identifying your opportunities too.
Planning must also take budgetary provision into consideration. This will give room for a trade-off. For instance, you can satisfy a product that is not moving well in the market for the ones that are well accepted by the people. It will also help the organization to establish priorities and allocate resources appropriately for specific initiatives.
Analytics drive CRM initiatives as it allows the organization to have a better insight into their customer’s life. This knowledge helps the organization to segment their customers. The segmentation is done based on certain characteristics such as life stage, profitability, products, demographics and information customer behaviour gathered from each segment can be analyzed as this will allow the organization to come up with a model and predict customer behaviour.
Predictive modelling is essential to effectively target customers. Many campaign management vendors are combining segmentation and predictive modelling into a single solution, which Gartner has termed as “Relationship optimization”. You should know that profitability information from profitability systems can also be placed into the marketing system so that it becomes a dimension for segmentation and analysis. As the marketing of CRM executive, you have to continue to carry out analysis of your customers in real-time and this must be compared with customers profile in order to be sure of its authenticity.
CRM initiatives must be measured on a regular basis in order to refine initiatives and to justify is adoption organizations have to measure it in line with what was agreed upon in the beginning in order to be sure that the initiative is still relevant.
Such measurement will enable decision managers to make business decisions that will enable them to understand customer behaviour, guide business strategy, better manage resources, optimize channels, improve product and maximize customer profitability. In order to do this effectively, it will require query, reporting and group comparison capabilities.
At the end of this lesson, we have been able to discover that:
- Analytical CRM is used in segmenting and targeting customers.
- Analytical CRM is also used in justifying an initiative in order to drum support for it. This is done through the use of metrics which are been used in order to determine customer satisfaction, profitability, retention, sales efficiency among others.
- Analytical CRM helps an organization to plan about how to allocate resources, product development and identification of organizational potentials.
- Analytical CRM also allows the organization to have a better insight into the customers’ behaviour. It will allow them to know what the customers want so that they can come up with products and services that will satisfy their interest.
- CRM initiatives must be measured on a regular base in order to refine it and justify its adoption.
Now your take on this article…
I know you might agree with some of the points that I have raised in this article. You might not agree with some of the issues raised. Let me know your views about the topic discussed. We will appreciate it if you can drop your comment. Thanks in anticipation.
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