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0 May 04 2017, 08:52 in Business Essays by ewritegigs1@gmail.com

6. Analysis Plan

We aim to gather information that would help the client, Waffle-Oh!, in making business decision that would best achieve their goals. The questionnaire is designed to collect people’s opinion of food trucks, their food preferences, and their dining habits. Demographics, such as sex, age, marital status, ethnicity, and educational attainment were also asked from the respondents so we can better gauge the cohort that is the best target market for the business, as well as the market that we can further improve on.

Basic descriptive statistics like mean and frequencies can provide us with substantial information for improvement. We have also established that further statistical test, specifically chi-square, would provide us with results that would help us answer the questions that we aim to address.

7. Results and Application

We will first run descriptive statistics to gain an overview of the characteristics of the sample. This is so that we can be ensured that we have fairly distributed among demographics. This would also ensure that the results from the tests are unbiased and

One major application of descriptive statistics is the marketing platform that the client can utilize. Using frequencies, we can determine the most effective form of advertisement by knowing the number of people familiar with the client’s brand and which platform they learned it from. For example, if majority of the respondents said that they learned it on social media, then the client can invest more to increase their internet visibility, and customer engagement.

Frequencies can also help the client improve their menu. Using their answers for the types of food they are most likely to purchase from a truck food, we can know which ones are preferred by the public. As such, we can establish the client’s very close competitors. Additionally, we will also make use of their opinion on the best sides for waffle. The sides that would be most popular might be considered to be added in the menu to increase the likeability of the product.

We will also look into how much people are most willing to spend in order to establish a price range that would be most appealing to the people. That is, majority of the client’s food items should have a price that falls under the most popular cost that the respondents chose. We can also use the frequencies to know if there are prospective customers for other products that may be priced higher or lower than what they would normally spend on. For example, we can add specialty waffles in the menu at a higher price because there are at least a certain percentage of people willing to avail the more expensive products.

Lastly, we will investigate which part of the day people are most likely to eat out to know what time the client should be most active and visible to the public. Furthermore, they can add more time-specific items in their menu if there are significant customers at that time (i.e. breakfast specials, coffee, and hot chocolate). We can also use this to know what the off-peak hours are. As such, the food truck can provide time-specific promo to encourage the potential customers to dine during that time of the day.

Establishing a target customer is a good move for a company as they can focus on enhancing their relationship with a certain cohort. A company’s improvement may also be hinged on the preferences of the target audience. On the other hand, knowing the cohorts that a company is weak with can help them improve their consumer base on wider demographics. With this in mind, we want to test two response variables: (1) the likelihood of purchasing food in a food truck that sells waffles, and (2) familiarity with Waffle-Oh!. The explanatory variables are (1) gender, (2) age, (3) marital status, and (4) ethnicity.

Since we are interested in testing the hypothesis of whether any of the explanatory variables are independent of their either of the response variable, we will perform chi-square on multiple means. Should any pair of variable show significant association between each other, the client can use this to tailor his brand to a specific demographic. Hypothetically, let us say that we have found that the likelihood of buying from a waffle food truck depends on gender, and females yield a higher likelihood than males. The client can utilize this to increase their appeal to male to expand their target audience, and/or to increase their engagement with females because to encourage them to become return customers.

On testing the level of familiarity vis-a-vis demographics, we can establish it to improve the marketing and promotional aspect of the business. For example, after dividing the age to a smaller age group (i.e. 18-29 as students/young professionals, 30-45 as adults, and 46+ as elderly), we can test this information against their level of familiarity of the brand. Hypothetically, we have established that students and young professionals are the most likely to be familiar with the client, while the older demographics are mostly aware of the brand. Furthermore, we have also seen that the difference in their familiarity is significant. If, for example, we have found that adult demographics and older people are highly likely to purchase food from food trucks, we may see this as a big opportunity that the client has not explored yet. As such, this can help the client increase its promotional efforts that reaches the adult and older demographics as they have high potential in this specific cohort.

These are only scenarios of how useful our selected statistical tests are. Ultimately, there is no single piece of information that can answer all our questions. We will be running multiple tests and using the aggregate information, we can formulate extensive business planning that would be beneficial to the client.

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