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Analytic CRM –
Customer Relationship Management meets Business Intelligence 9th April 2009 | Category: CRM meets BI
..."I know what I discussed and agreed with which customer, and when!" ...
... "Of course I know my best customers!" ...
... "Mr. Zürcher from Bern AG is one of our "A" customers; he phones us regularly, and is always ordering goods" …  You will surely have heard answers like these when talking to your colleagues and employees from the sales or service departments about the value of their customers.
- Are you sure that these statements, often prompted by a “gut feeling”, are true?
- Presumably, you are familiar with your customer processes and with the customer’s management. What about the "hard" facts and figures?
- Can you evaluate these across companies without mixing media, and integrated in and harmonised with your financial or logistics figures?
- Can you make them available to the recipients in the company, organised by target group?
In the present difficult economic environment, it is particularly important to know which of one’s customers make the highest-value contribution. Which customers deserve particular attention? With which customers can I save time and money that I can use elsewhere with better prospects of success?
In Customer Relationship Management (CRM), companies aim to exert a positive influence on the relationship to their customers and to intensify it, so as to assure a sustainable, stable partnership. Companies can master this task only if they align their processes on the customer and the products and services that are actually needed. The CRM approach strives consistently for orientation towards the benefits for the customer, and also the benefits for the company (customer value). The following tasks ate particularly typical: - Embedding in the company strategy,
- Establishment of a customer-oriented company structure,
- Alignment of products, services and business processes on the market and the customers,
- Systematic harmonisation and coordination of all activities, and
- Design and introduction of IT support.
Independent of the CRM tasks that are current in the company at the moment, there arises a conflict of goals between optimal benefit for the customer and at the same time a high customer value for the company. This conflict is resolved by efficient customer information and IT applications. Measurability and transparency in this area are achieved through analytical CRM.
The analytical part of the Customer Relationship Management concept must be seen as spanning the various CRM processes in the company. Control instruments in the form of reporting and analysis tools are made available to the respective levels of management. This is precisely the point at which analytical CRM goes to work. Its task consists in converting the CRM-relevant data available in the company to information, and making it available as a basis for action and decision-making. This basis for actions and decisions affects functions and processes that, based on Business Intelligence approaches, provide information about the customer, such as customer value, customer needs, customer behaviour, ABC analyses and forecasts.
In addition, the analyses, information and data needed for sales and marketing processes are provided in analytical CRM. These include the following in particular: - Customer analyses (e.g. customer value, ABC analysis)
- Product analyses (e.g. profit contribution by sales channel and product)
- Marketing analyses (e.g. campaign turnover/costs per product)
- sales analyses (e.g. orders received/turnover by customer or sales channel)
- Service analyses (e.g. monthly deviations in earnings, turnover, costs per product)
- Contact analyses (e.g. racer/bum analyses)
A specific application in information gathering is data mining. To put it briefly, data mining means using the existing data and information, but combining it differently with the aim of recognising a usable pattern. Examples of this are cluster analysis and association analysis. This results in applications for: When we talk of Business Intelligence in the context of CRM, we mean that the basic components and concepts of Business Intelligence serve as a basis for analytical CRM. >> BI-Driven – Analytic CRM <<
The components of a Business Intelligence solution make it possible to make the essence of existing (CRM) data available as knowledge to the company in an efficient manner.
Analogue to the concept of logistics, in which the primary aim is to “deliver the right material in the right quantity to the right place at the time required,” the task of BI driven analytic CRM can be expressed as follows:
The right information, at the time need, in the right aggregation (density) and granularity (fineness), for the right recipient". Viewing analytical CRM in the sense of Business Intelligence has certain consequences. The CRM strategy must be brought together with a BI strategy and harmonised with it, so that a meaningful meshing of the strategies takes place. That means that the requirements of the analytical CRM must be taken account of in the BI strategy and tied into it. The CRM analyses are put in a wider context, and the expensive, interface-intensive, insular system solutions that are so common in actual practice can be done away with or at least reduced.
The Business Intelligence concept that results from a BI strategy, in consequence, brings the CRM data together with all the other company information. Only then is an integrated approach possible that ensures control not only of the cross-department CRM processes, but also across logistics or finance processes.
This integrative approach demands that those responsible tear down the boundaries between the company’s departments and responsibilities, and look for synergies. Here, the IT department, and in particular the BI Competence Centre, together with the board of the company, can serve as a bridgehead, identifying the synergies across the boundaries of IT processes.
The following practical example, taken from a leading Swiss logistics and postal service concern, demonstrates a solution that follows the integrative approach, making management statistics from different departments available for marketing and sales. A heterogeneous system landscape was simplified, existing reports were made uniform and integrated, and new applications and reporting requirements were implemented.
It was thus possible to create an information cockpit for different target groups.
The feedback from the end users, such as postmasters, sales managers and the board of management is very heartening. The simple operation in particular is praised by all.
Further potential for optimisation was identified in the course of a project. For example, there are still software applications, databases and CRM systems that are interconnected via high-maintenance interfaces, or that are operating parallel and sometimes independently of each other. In the next months, as part of a BI strategy, the next steps towards optimisation of the information flow will be initiated. The aim is to satisfy the different wishes and requirements of the internal post customers (departments and organisational units) optimally with solutions from the service layer of the IT-PV. And to meet future requirements and challenges like this:
>>It is not enough to know, one must also apply; it is not enough to want, one must also do.<<
Johann Wolfgang von Goethe
Ralph Riede, Partner |
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