The future, a realm of infinite possibilities and uncertainties, remains an enigma that continuously eludes our grasp. Technological advancements and societal shifts drive unprecedented change, businesses must grapple with the challenge of predicting and adapting to evolving customer expectations. In such a dynamic landscape, the concept of holding the “universal remote” to customer master data…
CLV and in turn, the profitability of each customer leads to measures of value that will be different for different customer groups. The identification of efficiency in the way the value is produced helps to direct an organization’s efforts. This in turn leads to the refinement of the exact kinds of customers and business partners that your organization wants to expend effort and energy on. The profitability of the customer is the revenue derived from that customer less the costs of identifying, securing, retaining, and growing them. The same approach needs to be used for campaigns. The more compelling the proposition with the greatest possible efficiency, the highest potential profit can be secured per customer.
Cloud solutions like the Pretectum CMDM applications are housed in data centers that are secured with access controls, surveillance, and other physical security measures; we make use of the some of the best in class implement network security measures, such as firewalls and data encryption to protect your customer data as it is transmitted over the internet. This data is encrypted both at rest and in transit, to protect it from unauthorized access.
Depending on the nature of your business and the relationship that you have with your customers you may have several different types of customer master data that you choose to manage and maintain. There are other types of customer data that you may need to manage too, data types that you don’t necessarily always think of as master data but which may benefit from being stored and retrieved centrally as required.
Pretectum’s CMDM is able to support you in leveraging all of these different ways of deciding what to store and what the criteria are around the values that you might store, qualitative, quantitative, declared or inferred. All types of data are supported in a highly configurable way according to your specific business needs.
If you’re wondering whether you can achieve a particular outcome in your use of the Pretectum master data management system to improve sales, support a particular initiative or simply provide your customers with a great personalized customer experience, reach out to us and we’ll tell you what you need to know about how the system can help.
Customer data plays a crucial role in customer relationship management as it provides valuable insights into customer behavior, preferences, and interactions with your organization.
Having accurate and up-to-date customer data can help your organization better understand consumers and provide personalized experiences that foster loyalty and improve satisfaction and confidence in your products or services.
Harvard Business Review contributor and business expert Barbara Bund Jackson has found this is very valuable through her research.
Customer Master Data Management (CMDM) is a process and technology used by organizations to ensure that customer data is accurate, consistent, and up-to-date across all systems and applications.
CMDM aims to provide a single source of truth for customer information by creating a centralized repository of customer data and managing the quality, governance, and integration of this data across the enterprise.
Customer Master Data Management helps organizations to improve customer experience, reduce data duplication and errors, enhance data security and privacy, and support informed business decisions by providing a comprehensive view of customer information.
Putting a price on data is a tough task to perform if your business is not “in the business” of selling data. The real question though, is does your organization recognize its arguably most valuable data asset – customer master data, as a valuable resource? The true value of that data more than likely hides in how you use it.
Customer data holds enormous economic potential if managed well and appropriately leveraged. The challenge though is that many companies struggle with proper handling and syndication of their data. Further, they don’t think about their customer data strategically. They don’t take what they have and convert the data that is in hand, into actionable information. Worse, they may not be managing their customer data in any meaningful way, they may have data all over the place in systems, spreadsheets and even email.
By implementing some data management best practices around customer data, these same businesses could be thinking more strategically especially if they are ensuring that their data is accurate and aligned with their business objectives.
Customer data management (CDM) is one of the most important aspects of customer experience management. It helps companies get to know their customers, understand their preferences and needs, and deliver personalized services and experiences that keep customers happy and loyal. A key element of CDM is data quality.
Data quality refers to how accurately your company’s information about its customers reflects reality. If you don’t have good-quality customer data, your efforts will be wasted on inaccurate information about those customers—including ones who can’t be found when they need help with a problem or question!
Customer master data management (CMDM) and customer data governance are co-dependent disciplines. Successful CMDM is not possible with at least a few key data governance elements.
While the CMDM may be understood as principally the technology, the actual data governance is the people, processes and technology.
With Pretectum’s CMDM we feel that the three are inextricably linked and so do not see it as being possible to pick up a solution like CMDM without data governance.
The reverse may be true. You may have data governance without master data management but then the effectiveness of your data governance policies and procedures have to be called into question.
Japan’s third-largest car manufacturer is Nissan and they are currently improving their operation practices as they aim for better sales output and of course brand awareness.
Nissan is considered an example of one a European car brand that is notable and successful. Founded in 1933 by Engineer Kenjiro Den, Nissan initially produced just motorcycle engines before branching out into automobile production in 1934.
For more than 80 years Nissan has built cars in Japan and in developing markets around Europe (and beyond) selling more than 4M units annually under the Nissan brand – including well-known models like the Nissan Leaf and Nissan X-Trail SUVs.
Nissan is also the owner of the premium Infiniti brand and the heritage brand Datsun which it discontinued on April 22. In addition to cars and trucks, it has in-house performance tuning products and cars labelled Nismo
It is a tough job, focusing on the environment, vehicle and product quality and customer loyalty. The approach has to be multi-pronged and is driven by data.
