6-2 Submission_Final Project Milestone Five

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1 6-2 Submission: Final Project Milestone Five Tamika Robinson DAT-210 Foundation of Data Analytics Professor Flores December 7, 2023

2 Running for Glory (RfG) has cultivated a loyal, devoted client base while remaining true to its running roots. To establish such a fan base, RfG must stay in touch with customer needs, show empathy in every conversation and conversation, and provide customers with the desired services and products. To remain competitive, maintain customer loyalty, and grow, RfG must be able to deliver fine-tuned solutions. Our consulting company has found several opportunities relevant to the data inquiry made on behalf of Running for Glory (RfG). To help RfG leadership make the best strategic decisions about expansion, we’ll provide the data we compiled into simple visualizations.  How will you summarize the tools, methods, and strategies you used for the analysis? To collect data, we used a combination of primary and secondary data collection solutions such as surveys, feedback from runner focus groups, questionnaires, internal RfG inventory records and sale information, and social media and online product/service reviews. An external third-party group was brought in to collect the data to alleviate bias. After collecting the data, a data quality strategy plan was created to clean and analyze the data. Description, inferential, and predictive analysis were performed to identify patterns, trends, and forecasting predictions. The data was broken down into qualitative and quantitative. Using experts and automation, the data was cleaned to ensure the quality and reliability of the data sets (Bougie & Sekaran, 2020). Excel, SAS, and Microsoft Power BI were used to perform an inferential and translate the raw data into useful information. Our strategy encompassed an iterative data discovery process, building models, and then refinement to help make the best accurate projections. With the results we needed, we were able

3 to interpret the data to help RfG determine the best course of action for the company. Microsoft PowerBI was used to create visualizations to convey our findings to crucial RfG stakeholders.  How will you address the specific audience the client represents? Describe the audience and how you will address the members. The specific audience of the clientele is professional, advanced, and novice runners. To effectively communicate with our audience, we must understand them. Data can be gathered from these clients via surveys and questionnaires via in-store, SMS, online, and phone. We can collect information such as age, gender, and location to help understand our customers. It can help determine who the targeted audience truly is and the suitable location for a new store location.  What data types and sources are important for the client to understand? Data types and sources can help drive valuable decision-making. Data types and sources such as surveys, focus groups, questionnaires, and online/social media reviews can all provide insight into customer needs, preferences, and behaviors. They can also aid with customer demographic information such as their gender, income levels, age, etc. Marketing strategies can be tailored based on this information. By understanding current trends, customer preferences, and interests, RfG can adjust business strategies accordingly.  What specific processed/analyzed results will you use in your recommendation? How will you present these? RfG needs data to confirm if expansion into the father suburbs and to a younger clientele is the proper decision for the company. Although client reactions are essential, we will focus on demographic data such as age and client location. With the zip codes provided, we can pinpoint locations. A visual representation such as a point distribution map or a bar chart can provide a

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4 geographical representation of where clients or potential clients reside. They can provide information on regional preferences or trends. Pie charts and bar graphs can be used to compare different groups effectively. This can identify which age groups are most interested in RfG products or what products are most and least popular amongst our respondents.

5 References Bougie, R., Sekaran, U. (2020). Research Methods for Business: A Skill Building Approach (eighth edition). John Wiley & Sons, Inc. Zhen Wen, & Zhou, M. X. (2008). Evaluating the Use of Data Transformation for Information Visualization. IEEE Transactions on Visualization and Computer Graphics, Visualization and Computer Graphics, IEEE Transactions on, IEEE Trans. Visual. Computer. Graphics, 14(6). https://doi-org.ezproxy.snhu.edu/10.1109/TVCG.2008.129

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