Enabling a 360-degree view of your customer
Improve your MDM strategy to reduce costs, increase sales, promote marketing effectiveness
As companies across the board struggle with the impact the economic downturn has had on their bottom lines, some forward-thinking organizations are focusing on how to better define and manage customer data through Master Data Management (MDM). Decision makers at these companies know that even modest improvements to their MDM strategy can make a big difference in enhancing overall data quality. Improved data quality can then lead to increased business efficiency and sales and marketing effectiveness, lower customer management costs and ultimately, improve customer service and satisfaction. In fact, successfully defining and managing customer data is fundamental to the success of any program that relies on it – especially during an economic downturn, when organizations must do more with existing resources.
Apples to oranges
There are a couple of significant challenges that companies commonly confront when developing a plan for MDM. One is that various divisions within an organization have their own definitions of a customer and their own customer hierarchy, and each division requires different types of customer information. Another challenge is that many organizations spend insufficient time distilling their data requirements before defining their customer data model, and then do not sufficiently cleanse existing data or prioritize ongoing data quality. This can lead to complex data models, increased costs, and eventually, customer dissatisfaction, decreased efficiency in sales, marketing, service, and IT.
Assessing the situation
To address these costly situations and better utilize their customer data, companies need to develop an understanding of the customer data life cycle and how different parts of the organization use customer data. There must be consensus across the organization as to how customer data will be modeled. The correct technology (as well as gaps between business needs and available technology) must be identified. Defining who owns, manages, and can modify customer data is also critical. Finally, a plan must be developed to ensure ongoing data quality. Once this assessment has been completed, companies should adopt a phased approach to improving their customer data management and modeling, as well as enhancing the enabling technology. This will help simplify their customer data model, enhance their customer view via thirdparty data feeds, reduce IT costs, improve customer segmentation and sales efficiency, and maintain a single, complete view of every customer. As a result, users across different divisions will be talking about the same customer and can link all relevant company-wide activity correctly to this customer.
Example
We recently worked with a global high-technology company that wanted to improve the quality and reliability of its customer data. This firm needed to increase the efficiency of its sales force during a hiring freeze, ro-actively track lucrative support contract renewals, increase levels of customer satisfaction and ultimately, maintain a ingle, 360-degree view of each customer. We realized that while the company’s sales and service departments had different needs, the majority of their requirements overlapped and could be achieved by a single CRM system – provided that customer data was properly modeled from the start. It also became clear that by spending time creating a more refined customer data model that minimized exceptions, the company could simplify many business practices, streamline the existing infrastructure and reduce long-term costs. Using a phased approach, we were able to help this company identify how different business groups use customer data and then determine and build consensus around how customer data should be defined and owned – and who could make changes to it. In addition, we worked with the company to cleanse its existing data and consolidate duplicate records, link all child records correctly, integrate third-party customer data feeds and then train a new data quality group that was dedicated to distilling sales data into business intelligence. Since implementing this new customer data model and the MDM business process changes, the company has improved its account coordination at both the national and regional levels and has gained a more in-depth understanding of its customers.
Because of its refined MDM strategy – and resulting improved data quality levels – the company is also able to more quickly identify and sell to decision makers, generate more accurate sales projections and rapidly solve customer problems to ensure high levels of customer satisfaction and loyalty. Simply put, improving customer data modeling and effective MDM business processes enable a 360-degree view of customers. Reduced data management costs, increased sales and marketing effectiveness, superior sales forecast accuracy, and enhanced opportunities for cross- and up- selling are all beneficial byproducts. Companies will also find that this valuable effort provides a solid foundation upon which to support customer data-centric projects— both today, during difficult economic times— and tomorrow, when the economy rebounds.
Author: Bernard Drost is the chief technology officerat Innoveer Solutions, a CRM consulting firm with offices throughout the US, Western Europe and in New Mumbai, India.