Answer the original question and reply to 2 of my peers posts.
Peer Question 1
RE: Week 6 Discussion 1
How can primary and secondary information improve your digital analytics marketing analysis? What would your ideal data-collection plan include if you had inside access?
Primary data will be very useful because I can look at it without the bias of anyone else’s opinions. New information should come across untainted and I can conduct analysis freely and freshly. Secondary data will be very key because someone may have done some of the “heavy lifting” for me. There could be legitimate facts that I may be able to rely on or connections that I didn’t make, especially those based on correlation or causation regarding my topic. With inside access, I’d just see what is available to streamline the end results of my research question. I would immediately utilize whichever data is more closely deemed to solve my problem.
Peer 2 question.
RE: Week 6 Discussion 1
In modern marketing, data is very important as it helps in predicting the future performance of a business. Data is the raw information or statistics that are historical or derived from experimentation and calculations (Wilson, 2019). This data is classified as either primary or secondary depending on how the data was collected. A combination of primary and secondary data provide rich data that is important to data analytics in improving the consumer experience, increase sales, as well as drive other offline and online actions.
To solve marketing challenges, researchers must collect adequate, reliable, timely and relevant data. This data is analyzed and interpreted and the information generated is then used to formulate strategies and decision-making (Leventhal, 2018). The primary data provides basic response to relevant marketing problems due to its originality. Secondary data supports the primary data as it helps in exploring, defining and detailed understanding of the marketing problems. Thus, secondary data if carefully chosen may help to improve the precision, consistency, reliability, and validity of the primary data. In addition, the complementarity of the primary and secondary data helps to reduce the margin of error to allowable levels.
A data collection plan details the steps and sequence to follow while collecting data for a given Six Sigma project. According to (Gelman & Nolan, 2017), an ideal plan should contain continuous data also called a scale. In addition, it should contain the attribute data and the operational definition of variables. An operational definition describes what will be measured, how it will be measured and the process of gathering and recording data. Finally, the plan must have an outcome measure, process measure and a sampling method that is representative. A proper data collection plan when correctly deployed on the right primary and secondary data is a precursor of an excellent digital analytics marketing research.
Gelman, A., & Nolan, D. (2017). Data collection. Oxford Scholarship Online. doi:10.1093/oso/9780198785699.003.0006
Leventhal, B. (2018). Predictive Analytics for Marketers: Using Data Mining for Business Advantage. London, England: Kogan Page Publishers.
Wilson, A. I. (2019). Secondary data, customer databases and big data analytics. Marketing Research, 62-95. doi:10.1057/978-1-352-00112-9_3
2 hours ago
Those are the 2 peers that has to be responded to. Just have to respond to there anwers in 2-3 sentences each.