Profile About Elodie Name: Yihan Yuan (Elodie) Role: Associate Consultant Joined: 2016 Location: Adelaide CBD [pic] As an excellent graduate in commerce faculty‚ it is my great honor to work with so many talented colleagues with versatile skills in professional accounting and advisory areas. More importantly‚ now I have enough confidence in assimilating this multicultural environment and master my current profession as soon as possible. Q&A Describe
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Document I. Input/Output Specifications A. Input Specifications (Customer’s View) An on-line web site will be designed that allows the user to input the following information from any computer with internet access: Their customer profile information: (account registration) Customer name (string format‚ 40 characters max.) Street address (string format‚ 40 characters max.) City (string format‚ 15 characters max) State (string format‚ 2 alpha characters) Zip code (numeric format
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organization. So no matter where the customer calls within the organization‚ everyone is fully informed and the customer does not need to repeat the issue (major dissatisfaction factor). Some of the examples are stated below: 1. Profile Customers 2. Retain Best Customer Profile Customers It mainly segment by demographic .This is partly because customer wants are
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interpret and discuss urban flood impacts and risk management measures in Jigjiga municipality. 4.3. Demographic Data of Respondents In this section demographic profile of respondents which consists of sex composition‚ age‚ educational status‚ and length of stay in the town is presented. Based on these demographic variables‚ summary of the profile of respondents is presented in tables 4.1 and 4.2
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Company profile Date of Establishment | 1935 | Revenue | 1386.83 ( USD in Millions ) | Market Cap | 249989.56450195 ( Rs. in Millions ) | Corporate Address | Mumbai Central‚‚Mumbai-400008‚ Maharashtra www.cipla.com | Management Details | Chairperson - Y K Hamied MD - Y K Hamied Directors - Amar Lulla‚ H R Manchanda‚ K A Hamied‚ M K Hamied‚ M R Raghavan‚ Mital Sanghvi‚ Pankaj Patel‚ Ramesh Shroff‚ S A A Pinto‚ S Radhakrishnan‚ V C Kotwal‚ Y K Hamied | Business Operation | Pharmaceuticals &
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will provide a clear idea regarding the customer’s awareness towards the health juice as well as towards different variety of fruits. The customer’s awareness to create a demand towards our product. Goal 2: Understanding the individual’s demographic profile of consumer. Objectives: The customer acceptance depends upon the knowledge for the variety fruit in the surrounding that they have gained their maturity level during growth of the age. The age factor is an important factor to know product demand
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networking sites evolve more features will be implemented to aide control over information. The government has created and is developing new policies that govern social networking sites. The information people put on display on their social networking profiles‚ is not up to the sites but the individual. Sites like Facebook let the user choose whether they want to display age‚ race‚ location‚ and occupation. The “publicness” as Auchard refers‚ is up to the individual‚ as the site has options to protect
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TRADE AREA ANALYSIS Trade Area Analysis‚ Development and Mapping Trade area analysis and mapping describe the characteristics of the area around a store or network of stores. Without accurate trade area definitions‚ you cannot measure the key statistics that impact a store’s performance. Use trade area analysis to aid site selection and target marketing. Trade area analysis and mapping tell you: • Where a store’s customers are coming from • How many customers you have in a trade area
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A Social Networ k-Based Recommender System (SNRS) Jianming He and Wesley W. Chu Computer Science Department University of California‚ Los Angeles‚ CA 90095 jmhek@cs.ucla.edu‚ wwc@cs.ucla.edu Abstr act. Social influence plays an important role in product marketing. However‚ it has rarely been considered in traditional recommender systems. In this paper we present a new paradigm of recommender systems which can utilize information in social networks‚ including user preferences‚ item’s general acceptance
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literature 8 3. Methodology 9 4. Results and Analysis 10-18 5. Summary 19-20 6. Conclusions 21 7. Bibliography 22 8. Appendix 23-26 LIST OF TABLES Sr .No Particular Page No. 1. Table 1: Demographic profile of the respondents 2. Table 2: Indicators for identification of a pirated product 3. Table 3: Frequency of purchasing pirated products 4. Table 4: Durability of pirated products 5. Table 5: Criterion rating for purchasing pirated products
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