Management Information Systems How Customer Essay

Length: 10 pages Sources: 8 Subject: Business Type: Essay Paper: #94298950 Related Topics: Management Information Systems, Management Control Systems, Ajax, Customer Relationship Management
Excerpt from Essay :



Advanced data analysis and business intelligence are also reflecting the change in the perception of time on the part of customers using social networks. In previous CRM systems rarely was the time-to-respond or any other metric used for evaluating how quickly and thoroughly a company responded. No longer, as the combining of insights gained from analyzing customers' comments on social networking sites is showing many companies that they have a wide gap between how they perceive time vs. their customers (Whiting, Donthu, 2009). Time and trust also are driving the next layer of the structure of CRM systems as defined by Gartner which is the definition of CRM technologies.

Applications, architectures and infrastructure of CRM systems are seeing the greatest impact from social networking. From the widespread adoption of Salesforce.com, a series of CRM applications-based entirely on the Software-as-a-Service (SaaS) model to the integration to Facebook, Friendfeed, Twitter and in some cases, MySpace, CRM systems are looking to capitalize on the exceptional popularity of social networks. The SaaS delivery model lends itself well to integration with social networks as the Application Programming Interfaces (API) and methods of application scalability on hosted platforms are comparable to each other (Toor, 2009). Integrating social networking-based content into traditional CRM systems that are based on licensed models however is more of a challenge as these systems has been specifically designed to support integration in a precise data interchange format. The exceptional growth and popularity of social networks and the SaaS platform for delivering CRM applications however have both benefited from the en masse adoption of Extensible Markup Language (XML) protocols as the primary means of systems integration (Choi, Wong, 2009). XML is revolutionizing CRM in that it makes it possible to integrate with a far greater number of potential databases, application and website that can be accessed using this integration standard. XML is also being used as the foundation for asynchronous JavaScript and XML (AJAX) programming of CRM applications. AJAX has many benefits relative to HTML or DHTML programming for CRM applications, the foremost being speed and accuracy. AJAX is a programming technology that only refreshes the part of the application that has changed. Estimates place the speed increases in application performance as high as 60% over pure HTML pages for CRM and database-intensive applications (Choi, Wong, 2009). With time and trust being the primary differentiators in CRM applications, the rapid adoption of AJAX as a programming standard for social network applications is consistent with the preferences of customers today. Instead of thorough responses to their requests for information or support, customers instead want to have a company get back to them quickly, accurately, and succinctly (Greenberg, 2008). Gone are the days of reciting back via the Internet and Web-based applications just how much a company knows about a given subject. Today the focus in CRM as a result of XML integration technologies, AJAX programming languages and integration to customer data is more about helping customers get to their goals and solve their problems as quickly as possible. When a CRM system can deliver that finely tuned of results in conjunction with being as efficient and accurate as possible, they will have met the expectations of the 21st century consumer and customer (Greenberg, 2008). The fact that so many CRM systems however are not embracing this approach to speed, trust and time being the critical differentiators means that will be a widening gulf between companies and their ability to respond to customers.

The final layer of the CRM building blocks as defined by Gartner is CRM Metrics. As was mentioned in the section on CRM Information, this area is going through rapid change as marketers attempt to keep pace with the massive volumes of data produced on social networks. Second, this area of value, retention and customer loyalty has also become even more critically important from the context of fighting back a global economic recession. Through the use of business analytics and business intelligence applications, CRM systems are capable of predicting customer behavior over time and developing strategies to better align to customer preferences. As with each layer of the Gartner CRM definition, this area is also seeing an exponential level of content being generated both through social networks and through the XML integration links with existing customer databases, order capture and order management systems throughout companies. An area that is also fascinating is how forward-thinking companies who are attempting to define the Return on Investment...

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This is occurring at the CRM Metrics level of the Gartner Model as companies integrate their financial information into the CRM systems to determine ROI of these investments. Second, there is the ability now to track the profitability of each marketing strategy or program over the long-term. Using social networking sites as a sounding board and a means of listening more proactively to customers, companies are able to better ascertain how their investments are paying off or not by the strategy level.

Conclusion

Social networking applications, their rapidly gaining popularity, and the catalyst of all these innovations, Web 2.0, is also drastically re-ordering the CRM landscape as well. In many respect social networking is bringing the voice of the customer louder and more clearly into companies than has ever been the case in the past (Greenberg, 2008). Others argue that social networking is also redefining the concepts of trust, transparency and even changing how people value and see time in the context of how they buy and consumer products and services (Whiting, Donthu, 2009). Underscoring all of these factors however is the fact that expectations continue to increase on the part of consumers for accurate, timely and useful information delivered how and when they need it. The role of CRM as enabler of customers' goals instead of a means to push more products at them and sell more is a critical one. No longer are customers content to just hear what companies want to say; customers are now redefining the value propositions of companies an in so doing, redefining their brands (Bernoff, Li, 2008). The customer being in control due to social networking is readily apparent from reviewing the applications in Appendix B. Far more intriguing that this dynamic however is how companies will cope with the massive challenge of serving customers whose expectations of service, responsiveness and truthful service are escalating over time, changing the nature of customer relationships.

References

Colin Beasty. 2006. RE: TOOLING. Customer Relationship Management, September 1, 46.

Bernoff, J., and C. Li. 2008. Harnessing the Power of the Oh-So-Social Web. MIT Sloan Management Review 49, no. 3, (April 1): 36-42.

Boiy, E., and M. Moens. 2009. A machine learning approach to sentiment analysis in multilingual Web texts. Information Retrieval 12, no. 5, (October 1): 526-558.

Choi, R., and R. Wong. 2009. Efficient Filtering of Branch Queries for High-Performance XML Data Services. Journal of Database Management 20, no. 2, (April 1): 58-83.

Jim Dickie. 2005. Is Social Networking an Overhyped Fad or a Useful Tool? Customer Relationship Management, February 1, 20.

Jill Dych. 2009. The New World of CRM: Three game-changers and how to make the most of them to benefit your customers. Information Management 19, no. 5, (June 1): 53.

Julian Johnson. 2004. Making CRM technology work. The British Journal of Administrative Management (January 1): 22-23.

Kim, H., and Y. Kim. 2009. A CRM performance measurement framework: Its development process and application. Industrial Marketing Management 38, no. 4, (May 1): 477

Greenberg, P. 2008. Everything Is Social. Customer Relationship Management, March 1, 48.

Chor-Beng Anthony Liew. 2008. Strategic integration of knowledge management and customer relationship management. Journal of Knowledge Management 12, no. 4, (July 1): 131-146.

McKay, L.. 2009. Making Relationships Matter. Customer Relationship Management, March 1, 18.

Tim O'Reilly. 2006. Web 2.0: Stuck on a Name or Hooked on Value? Dr. Dobb's Journal, July 1, 10.

Ratnasingam, P.. 2008. The Impact of E-Commerce Customer Relationship Management in Business-to-Consumer E-Commerce. Journal of Electronic Commerce in Organizations 6, no. 4, (October 1): 30-46.

Richards, K., and E. Jones. 2008. Customer relationship management: Finding value drivers. Industrial Marketing Management 37, no. 2, (April 1): 120.

Rishel, T., L. Perkins, S. Yenduri, and F. Zand. 2007. Determining the context of text using augmented latent semantic indexing. Journal of the American Society for Information Science and Technology 58, no. 14, (December 1): 2197.

Singh, T., L. Veron-Jackson, and J. Cullinane. 2008. Blogging: A new play in your marketing game plan. Business Horizons 51, no. 4, (July 1): 281.

Tajinder Pal Singh Toor. 2009. Creating competitive edge through improved customer relationship management. Business Strategy Series 10, no. 1,

(January 1): 55-60.

Ping Wang and E. Burton Swanson. 2008. Customer relationship management as advertised: Exploiting and sustaining technological momentum. Information Technology & People 21, no. 4, (October 1): 323-349.

Anita Whiting, and Naveen Donthu. 2009. Closing the gap between perceived and actual waiting times in a call center: results…

Sources Used in Documents:

References

Colin Beasty. 2006. RE: TOOLING. Customer Relationship Management, September 1, 46.

Bernoff, J., and C. Li. 2008. Harnessing the Power of the Oh-So-Social Web. MIT Sloan Management Review 49, no. 3, (April 1): 36-42.

Boiy, E., and M. Moens. 2009. A machine learning approach to sentiment analysis in multilingual Web texts. Information Retrieval 12, no. 5, (October 1): 526-558.

Choi, R., and R. Wong. 2009. Efficient Filtering of Branch Queries for High-Performance XML Data Services. Journal of Database Management 20, no. 2, (April 1): 58-83.


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