This exciting new text offers a hands-on, applied approach to developing the fundamental data analysis skills necessary for making better
management decisions using marketing research results. Each chapter opens by describing an actual research study related to the chapter content, with rich examples of contemporary research practices skillfully drawn from interviews with marketing research professionals and published practitioner studies. Clow and James explore the latest research techniques, including social media and other online methodologies, and they examine current statistical methods of analyzing data. With emphasis on how
to interpret marketing research results and how to use those findings to make effective management decisions, the authors offer a unique learning-by-doing approach to understanding data analysis, interpreting data, and applying results to decision-making. Covering key statistical concepts, the book includes exercises especially designed to teach students how to interpret and apply marketing research results. To make teaching and learning easier, numerous data sets and case studies are
offered through the online resources for instructors and students, which also offer step-by-step SPSS instructions. In addition, the easy-to-follow composition of the text and its accompanying learning aids make it an excellent choice for online courses as well as those taught face-to-face. Plus a blog with additional material to help you succeed in the classroom!- http://blogclowjames.net/ The Role of Marketing ResearchLearning ObjectivesAfter reading this chapter, you should be able to
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sign up today! What is data collection?Data collection is the process of gathering data for use in business decision-making, strategic planning, research and other purposes. It's a crucial part of data analytics applications and research projects: Effective data collection provides the information that's needed to answer questions, analyze business performance or other outcomes, and predict future trends, actions and scenarios. In businesses, data collection happens on multiple levels. IT systems regularly collect data on customers, employees, sales and other aspects of business operations when transactions are processed and data is entered. Companies also conduct surveys and track social media to get feedback from customers. Data scientists, other analysts and business users then collect relevant data to analyze from internal systems, plus external data sources if needed. The latter task is the first step in data preparation, which involves gathering data and preparing it for use in business intelligence (BI) and analytics applications. For research in science, medicine, higher education and other fields, data collection is often a more specialized process, in which researchers create and implement measures to collect specific sets of data. In both the business and research contexts, though, the collected data must be accurate to ensure that analytics findings and research results are valid. What are different methods of data collection?Data can be collected from one or more sources as needed to provide the information that's being sought. For example, to analyze sales and the effectiveness of its marketing campaigns, a retailer might collect customer data from transaction records, website visits, mobile applications, its loyalty program and an online survey. The methods used to collect data vary based on the type of application. Some involve the use of technology, while others are manual procedures. The following are some common data collection methods:
What are common challenges in data collection?Some of the challenges often faced when collecting data include the following:
What are the key steps in the data collection process?
Well-designed data collection processes include the following steps:
Data collection considerations and best practicesThere are two primary types of data that can be collected: quantitative data and qualitative data. The former is numerical -- for example, prices, amounts, statistics and percentages. Qualitative data is descriptive in nature -- e.g., color, smell, appearance and opinion. Organizations also make use of secondary data from external sources to help drive business decisions. For example, manufacturers and retailers might use U.S. census data to aid in planning their marketing strategies and campaigns. Companies might also use government health statistics and outside healthcare studies to analyze and optimize their medical insurance plans. The European Union's General Data Protection Regulation (GDPR) and other privacy laws enacted in recent years make data privacy and security bigger considerations when collecting data, particularly if it contains personal information about customers. An organization's data governance program should include policies to ensure that data collection practices comply with laws such as GDPR. Other data collection best practices include the following:
This was last updated in February 2022 Continue Reading About data collection
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What is the systematic collection and analysis of data?The process of collecting accurate data through interviewing, questionnaires, and other methods has not always been clear. However, data collection in field settings can be done in a structured, systematic and scientific way. These authors show us how.
What is the systematic collection analysis and interpretation of information in order to develop a marketing strategy?Market research is defined as the systematic collection and analysis of data about a specific target market or defined segment. It includes information for your business needs, such as supply and demand, competitors, products, and consumers.
What is systematic research in marketing?Systematic Market Research is an integrated approach to market research that connects different technologies, thought partners, and stakeholders in a way that delivers efficient and predictive insights over time.
What is collection of data in marketing?At root, marketing data collection is simply the collection of data from all your marketing efforts, campaigns, partners, and projects. Sounds so simple, right? Ultimately, however, it's an attempt to unify all your marketing data in a single place. And that means you need to collect, normalize, and standardize data.
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