The marketing research agency where you work has finished collecting survey data for an insurance company. The company was interested in determining how their salespeople are perceived and whether the number of awards they display on their wall matters for consumer perception. To this end, your agency deployed two surveys, resulting in two different datasets:

Dataset 1: Open-ended judgment of salespeople with awards

An online survey was distributed to a small number of potential insurance clients. A single question was asked: What comes to mind when you think of an insurance agent having sales awards? Write some words that you relate to these awards. Note that this is unfiltered and unstructured data, so pardon the language some participants may have used! ! This is very common in social media/review research or whenever unstructured text data is collected. Develop a word cloud by using WordItOut. You need to open the file “Assignment 7 – Judgment data.xlsx” and copy all the text in the file. Then, on the WordItOut website, hit “Create”, paste the text, then click “Generate”. A good practice when constructing a word cloud is to remove some of the most common words (e.g., “awards” – for large datasets, we might remove the top 30 words) or words that are not informative (e.g., “he”, “sales”, “the” probably do not convey any useful information). To do so, hit “Word List” on the WordItOut menu, and then click the words you want to remove. Experiment removing until you have developed a word cloud that contains mostly adjectives or informative words. Comment on what you see in the cloud. Given this distribution of words, do participants perceive having “many sales awards” as positive or negative?