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predictive dialers and crm software
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predictive dialers and crm software
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predictive dialers and crm software


DSC Tech Library

Customer Relationship Management

CRM Customer Relationship Management This section of our technical library presents information and documentation relating to CRM Vendors and Customer relationship management software and products. Providing timely customer contact information is vital to maintaining successful business environment. Accurate information provided in an organized and thoughtful manner is the key to any business success. TELEMATION, our CRM and contact center software, was built on this foundation. The ability to modify your Customer Relationship Management software is just as important in this ever changing business environment. Our customer contact management and CRM call center software was developed initially with this concept. Our Telemation Customer Relationship Management solution and contact center software is ideally suited for call centers throughout the world.


Why CRM Is So Hard and What To Do About It

Data is key to making CRM work

By Barry Briggs


Introduction

Over the next five years, companies will spend $150 billion to reinvent sales, marketing and service. Customer relationship management (CRM) is the hub of this turning wheel, and data is the axle. It's why Gartner calls managing customer-related data the number one obstacle to getting a return on CRM investments.

To fully exploit the power of CRM, and to realize its much-hyped promise, organizations must first recognize that customer-related data often resides in dozens, sometimes hundreds of separate databases, files and data feeds; they must then understand how to utilize all these information sources in a consistent way. Complicating this integration is the thorny fact that frequently business definitions differ from system to system: what is a "customer" in one system may be a "household" in another. Or, worse, what makes up the customer record in one system may be completely different - or even conflict with - what constitutes a customer record in another system. Despite spending millions on CRM systems for call center scripting, campaign management software and the like, companies can't accommodate a marketing department's simple request to link direct mailing or call center results to Web site hits for a given campaign.

Thus, data integration can't happen without consistent data and comprehensive customer-related business definitions across the CRM infrastructure - e-mail, Web system, call center, direct mail, data mart, campaign management and so on. Most organizations have sharply delineated business units around products versus the customer, resulting in wide rifts between sales, service, marketing and product lifecycle management. Why, for instance, should channel sales share leads with direct sales? Information technology (IT) departments bear the brunt of this departmentalization. Corporate executives, moreover, are frustrated by their inability to use the data contained in separate business units, which has been gathered over the years as a result of concerted marketing and CRM initiatives. The high cost of these siloed CRM projects only adds to the pain.

Marketing Now Drives CRM

The companies struggling to make CRM work today originally focused on solving specific operational problems, which point CRM systems did very well. Unfortunately, in the process they left widening gaps between their data pools and CRM systems, as business units added new CRM modules and services to the mix. The various systems that make up the middle layer of CRM - the operational side, such as sales force automation and call center personalization systems, and the analytic applications such as data mining and targeted marketing campaigns, for example - work very well inside their boxes. But nothing has coordinated the customer touch points, or bridged the gaps between the siloed systems that support them.

These problems are more painfully apparent now that the two-year vacation from capitalism is over. Companies need to maximize the huge investments they've made and concentrate on getting things to work the way they wished they would have in the first place. Meanwhile, operational efficiency is no longer the main goal of CRM; further, marketing has become a primary CRM driver.

For example, as reported in a recent special report on CRM published in Computerworld magazine, Mazda USA wanted to tie together profiles on car owners, segment them by value tiers and build lifetime value indices and loyalty indices - but its customer database was sorted by customer name, while the vehicle database was sorted by vehicle identification number. The marketing database had 10 years of customer contacts, but no query tools or analytics. It was also full of errors and duplicates. Mazda had to tie together four major - and separate - databases: marketing, vehicle, service and warranty and call center. With its data integration nightmare under control, Mazda is getting a more comprehensive view of its customers. Mazda's problems typify those many Fortune 1000 companies today. Ideally, an enterprise would like to see its numerous CRM systems working together in concert to provide a consistent experience to the end user, and to maximize marketing opportunities. In reality, this does not happen and in fact may not be possible.

Part of the reason it's so difficult to properly coordinate CRM across the enterprise is that the infrastructure bypasses so many customer-related systems. How many systems in a given organization hold some amount of customer information? In fact, every one of them should be, to some extent, a functioning part of the CRM infrastructure. But in order to make all of these systems function together harmoniously, CRM systems must learn to speak a common language, to develop a data "Esperanto" of common definitions. They must all agree upon what constitutes a customer, what constitutes a transaction, a product, a household and so on. This doesn't mean that all the database schemas must be reengineered; only that the in communicating, systems should use this lingua franca.

Metadata is the underlying definition or description of the actual data, "the data about the data." From metadata we can assemble a common view of key business definitions, such as "customer," "product," "account" or "promotion." The classification "customer," may, at first glance, appear to be self-evident - these are the people that buy a company's product or services. But, as we've seen, the data definition of "customer" may vary widely, depending on the nature of a promotion, the channel used and/or the circumstances of the sale. The solution is standardized, reusable metadata definitions available to all systems and business units. By sharing common definitions and data about customers, a company has a greater ability to identify valuable up-sell and cross-sell opportunities across products and business units, ensure consistency of the offers and messages, and enhance the likelihood of top-line revenue growth. Having reconciled disparate system definitions, it's now possible to begin identifying the larger issues. Our systems can speak to each other: what should they say?

Establish Interaction Policies

What every marketer wants is the ability to create "interaction policies." These are codified rules for dealing with customers: across all channels and touchpoints, in real time. Here are some examples of simple interaction policies:

"If a platinum customer withdraws more than ten thousand dollars, have a sales rep call." "If a customer reports a change of address to the call center, offer a mortgage on his or her personalized Web page."

With the ability to create actionable business rules like these, marketing teams will be able to roll out tactical plans for how the organization will meet customer needs and demands while providing a consistent experience across various lines of business and marketing channels. In tandem, the IT team can leverage the new infrastructure to ensure it delivers the policies' requirements. With the customer interaction policies, business rules and supporting infrastructure clearly defined and deployed, any CRM initiative, whether a prototype or a full-scale rollout, has a far greater chance of success.

Ultimately, executing a customer interaction policy relies on the IT infrastructure and the ability to create a common view of key enterprise definitions across the enterprise. To summarize, making a CRM investment work is a two-step process that begins with unifying disparate systems by creating and managing standardized, reusable business definitions mapped to the different CRM system schemas throughout the organization. These maps, which direct CRM data movement across systems, are accessible to third-party tools via SOAP and Java APIs that make it possible to map common CRM, customer and business definitions across transactional and legacy systems.

Having accomplished the definition phase, enterprises can then deploy "interaction policies," which use the common language of metadata to allow disparate systems to coordinate with each other in real time. The end result is that cross-sell and up-sell opportunities are presented in real time; customers have pleasing, consistent relationships with the enterprise, no matter what channel they use; and the organization as a whole functions more efficiently and cost-effectively. This is the future of CRM: whoever builds this framework can rightfully claim credit for laying its foundation.

About the Author

Barry Briggs is Chief Technology Officer and Vice President of Engineering at Wheelhouse Corp., a developer of CRM integration software that makes CRM work, where he is responsible for charting the company's technology course and managing its development. Earlier in his career, he was the chief architect and lead developer of Lotus 1-2-3, the most popular software application of its time.

For more information go to www.wheelhouse.com.