Coffee House in the UK - Customer Relationship Management - Case Study Example

Table of Contents Introduction……………………………………………………………………………………..2 Decision Support System………………………………………………………………………..3 Customer Relationship Management (CRM)…………………………………………………5 Conclusion………………………………………………………………………………………10 References……………………………………………………………………………………….11 Case Study Introduction Coffee house is one of the leading restaurants with various outlets in the U.K across 4 cities and it is also planning to expand into the Hampshire area in the U.K. The company needs a decision support system to aid them in some key decision pertaining to strategic and operational areas of their businesses. With the immense information that the company posses in relation to its operations, the company is seeking to have the data which include sales revenue, cost of products sold and the expenditure to be analyzed by using a modern decision support system while at the same time providing monthly profit and loss analysis per outlet including any new partner (Franchise) whom they are likely to associate with In addition to this, the company possesses data regarding the demographical breakdown of the entire U.K population in the Hampshire area and coffee house restaurant expects the Decision Support system to assist them in regards to this particular issue. The company also has some information pertaining to new companies which are seeking to collaborate with coffee house on franchise partnership for their new expansion venture, this calls for a DSS system that will aid coffee house to assess the risk associated with engaging a new company and it should also help in determining the credit score of the envisaged partnering company. Because coffee house is thinking of joining more franchises and it is already operational in 4 cities of Hampshire, it should embrace a system that is open and possibly can be easily controlled via the World Wide Web to enable easier administration of its resources. Decision Support System Coffee house management will be seeking access to strategic companies information in order to help them best strategize on their operations, management and evaluation of their restaurants. This calls for real time data that is customer centric and that which permits them to make comparisons on customer to customer basis while at the same time enabling them to compare the financial aspects of their company on an outlet and seasonal basis. This calls for data that is useful, accurate, organized and readily accessible about the operation and management of the company inclusive of its franchise holders. With data driven decision making becoming absolutely critical in any organization, it means, sales report, profit & loss Analysis per, consumer demographics, score card and even real time weather data have to be informed by accurate & relevant information which is readily available in order to influence the aspects of decision making. However, in order to do this, raw data from disparate sources have to be accessed, integrated, compiled and finally be distilled into some useful information in a timely manner and this task may be accomplished by a technology known as a Decision Support System (DSS). A modern DSS consists of the user interface which acts as the main gateway to the database management system (DBMS) of the restaurant together with the model based management system (MBMS) in which the restaurant DBMS can be independently managed or integrated within a Decision Support System generator in order to allow users to create a D-Base file that will be used as an input to the Decision Support System hence to be shared by the different networks which operate independently but need data for the managements decision. The created models together with the D-Bases are stored are kept in the model base and D-base in direct storage devices which may also be kept in remote locations (Carter et. Al. 1992:19). NB: All the restaurants data has to be stored in a central repository regardless of the location to aid the executives in proper decision making. Due to advancements in technology, DSS can focus on teams, workgroups and distributed, decentralized structure of the company (King, 1993). However, in a user’s viewpoint, it is only the user interface of the DSS components which they have to deal with on a one by one basis. Therefore the system must have a friendly user interface in which issues to be considered include: The choice of input and output devices used The screen design Colours used in the interface The presentation format of the data and information available on the system Various interface styles among others. The DSS generator should provide its users with various interface modes such as menu based interaction mode, command language interface, Questions & Answers, interactive forms, language processing dialogue. With the user interface, the users are able to access: The data sub-system which consists of the main database of the restaurant software which should also be shared externally in order to be accessed by the franchise database and at the same time the DSS should be able to seamlessly access the database from the new franchise. The model sub-system which consist of the model base and the model base management software And a perfect example of a modern DSS is a Customer Relationship Management System (CRM). Customer Relationship Management (CRM). This may be described as an integrated information system that collects information about a particular client. It can also be used to plan, schedule and control all the pre and post sales activities within an organization and in this regard the restaurant and it embraces all the aspects that deals with both prospects and customers including sales force, marketing, call center, field service and technical support. However, in today’s competitive business landscape, better and reliable information is only half the battle won and finding the particular information faster is the most challenging task whereby in order to alleviate these concerns, Coffee House restaurant sales & marketing departments are embracing solutions that integrate data from credible information providers (Brad Haigis) This systems primary goal is to improve on long term growth and profitability of the restaurant by better understanding the customer habits. It should also provide more effective feedback with improved integration in order to better gauge the return on investment recorded in these particular areas. With these benefits in mind, the restaurant should try its best to implement a modern CRM which will help them in making some of their strategic decision pertaining to operations of the restaurant together with both the old and new franchises. This requires functionality such as data mining from the system in order to properly evaluate clients on regions, age, social status, spending habit, income, purchasing power, religion e.t.c When the restaurant accesses some of these key information, they may be useful to the marketing department which will also aid the restaurants management into making some key decisions pertaining to the overall operation and decision making and once coffee house restaurant begins to use its customer information to make timely decisions, then, they may begin to develop sophisticated means of using the customers data (CRM TODAY, 2010). With customers information being the foundation of the CRM system, there should be properly piercing of customers information from multiple systems for the analysis and marketing campaigns in which the information also have to be centrally stored while providing a comprehensive view of the customers information in order to reduce the demand on information technology while improving on efficiency of marketing and customer communication processes, this calls for the information being consistent, reliable and in a usable format (CRM TODAY). With a modern CRM system in place, coffee house may be able to perform accurate descriptive analysis which is likely to give them the required competitive advantage over their rivals; this is because customer segmentation will be easily performed to drive marketing initiatives. Market basket analysis will also be possible to be performed which will link products together based on the rationales of a customer buying habits. A CRM system will also aid in predictive modeling which mainly embraces statistical methods to compare and contrast clients on various factors and they uses a certain score card mainly applied to business customers and in this regard coffee house customers in order to predict their likely behavior. For instance, there is the CHART analysis possible by a CRM system which creates decision trees of some predictive attribute combination by testing factors against each other and with each attribute adding a branch to a tree in which branches predicting certain product consumption which might be a fruit drink or take away pizza and may include age group of under 20, 20-50, 50 and older, this requires each age branch to have a percentage associated with it which might be the under 20 node that has a 70% likelihood of consuming certain foods. By coffee house deploying modern CRM system, they are also able to predict response to some targeted offers, this calls for the customers to be scored on their likelihood of responding to a certain offer which might be lets say “Happy Tuesday, Buy one Pizza get one free”, coffee house is really able to run an economic or what if scenario and really even predict their response to their new offer (CRM TODAY, 2010). Modern CRM systems have also been infused with a plethora of business information in regards to their prospective and existing customers, these information may include the coffee house customers financial information such as credit history, income, spending habits, it may also include the corporate structure, industry reports e.t.c It is this teaming up with specific industry information providers that mainly focuses on analyst reports, in depth financial data and business intelligence that the CRM providers will easily enhance their offerings in order to integrate timely & relevant information from reputable sources with the result being a richer CRM environment that will aid the coffee house representatives in making stronger connections with each and every of its customers available hence providing sales representatives with the required knowledge in closing sales quickly and effectively(Brad Haigis) Fig 1.0 Diagram depicting a CRM system Some CRM systems come with lead generation technology which can make it easier for coffee house to easily identify new customer, this may happen by searching “Google local” for some key words which may be limited on cities, regions or countries, you then proceed on and choose the right prospect and transfer the data into the CRM system with just a mouse click including his contact details (Fellow Consulting, 2009). It is also possible to search for a new franchise holder, know about your competitors location or even get to know the best location for coffee house billboard advertisement, you only need to search for a certain unique keyword (e.g. coffee shops Hampshire) and place your icon on the results, you immediately witness the top results next to the icon in which it is also possible to view detailed information and eventually import that particular data into the proposed coffee house CRM system (Fellow Consulting, 2009). Coffee house has also to build on its customer loyalty in order to remain competitive and in order to do this, it has to identify loyalty drivers in which coffee house adopts a satisfaction measurement system that is empirical, integrated and customizable and the system should also avail real time feedback to enable corrective action from the management (Oracle, 2006). Customer loyalty has to be build by coffee house because, most customers tend to be evangelistic about their relationships over time hence likely to help coffee house expand its market presence by personal referrals only. For instance, in a certain study of retail profitability which is somehow related to restaurants, it was found by Bain & company that after a single satisfying purchase the average customer referred three friends or colleagues, but after some ten such like purchases the number of positive referrals was up to seven hence customer loyalty doubled more than doubled new business leads (Bain & Company, 2000). Conclusion Implementing a modern decision support system is a proactive way of using data to manage, operate, and evaluate coffee house restaurant together with its associated franchises. Depending on the available and quality of the underlying data, a DSS system may be used to address multiple issues pertaining to strategy, sales & marketing, competitive positioning, customer retention and loyalty. Acquiring a DSS and in particular a CRM system is a major undertaking by coffee house restaurant and they will need to plan appropriately, this is because combining customers information while at the same time performing data mining is likely to enable coffee house to better understand its clientele base and at the same time communicating with them more effectively. Once coffee house start using its client related information to make decisions about how, when and what to market to their customers, they are then likely to increase their volume of targeted customers. References CRM TODAY (2010). Data Mining and Customer Relationship Management. Retrieved May 2010 from http://www.crm2day.com/content/t6_librarynews_1.php?id=EpFEAkAFpuEZkNWvTr Brad Haigis. The future of CRM: Intelligent systems empowering sales. Retrieved May 2010 from http://www.realmarket.com/required/onesource3.pdf CRM TODAY (2010). CRM depends on the data warehouse. Retrieved May 2010 from http://www.crm2day.com/content/t6_librarynews_1.php?id=EpFEyVlllZAZeqqfHq Fellow Consulting (2009). Customer Conquest: Easily identify new customers-easily import them into your CRM. Retrieved May 2010 from https://5603266437227755332-a-crm--gadget-com-s-sites.googlegroups.com/a/crm-gadget.com/wiki/lead-generation/WhitepaperCRMGadgetLeadGeneration.pdf?attachauth=ANoY7codBdH3UIc9I4QTXfbew81zYigaZy6NkQ8tPVfiGLB7kXhxwveK38liIccfytrhds8qHG3QrHzoQQJ1LtLYRTJ8nv2wjNDEtVHSVltHd1u9PHVMrxyIbWdKkOJ0KuKfMouv808YD-hKBAdO5u1leaSmnhZs3BMWQncHuMUT_OsO0VBLv16DjmSkG7UvGb3rUUqhN73_cRA0E9zstXIeTQLMNvFYCfJJG4pnUYHeM_k42bb6ji__gnSGEBhQUfJs1aFOoHa6&attredirects=0 Bain & Company. Conclude that customer loyalty is the key driver of online retail profitability, Business wire. March 30, 2000. Oracle (2006). Customer Loyalty, the new competitive advantage. Retrieved May 2010 from http://www.oracle.com/applications/crm/siebel/resources/customer-loyalty-white-paper.pdf Carter, G.M., Murray, M.P., Walker, R.G. and Walker, W.E. (1992) Building Organizational Decision Support Systems, Boston, MA: Academic Press. King, D. (1993) 'intelligent support systems: art, augmentation, and agents', in R.H. Sprague, Jr and H.J. Watson, Decision Support Systems: Putting Theory into Practice, 3rd edition, Englewood Cliffs, NJ: Prentice Hall. Fig 1.0 Diagram depicting a modern CRM system. Retrieved May 2010 from http://marketingmo.com/common/files/crm.jpg Read More