Module 7 Chapter-F2F

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Module 7 - Market Research on Caffeinated Products Background A start-up company in Boulder has an idea for a new energy product: caffeinated chocolate. Many details about the exact product concept are yet to be decided, however, the company wanted to get some consumer input before it moved ahead with developing the new product. To do that, they created concept statements for seven related product ideas and administered a survey regarding those concepts. You will analyze the data collected from the surveys. The seven concepts are 1. Caffeinated chocolate bar 2. Caffeinated cookies 3. Caffeinated chocolates 4. Caffeinated potato chips 5. Caffeinated water 6. Caffeinated cereal/granola 7. Caffeinated hamburger meat  The concepts numbered 1 and 3 (chocolate bar and chocolates) are closest to what the company has in mind for the new product. Concept number 2 is a similar idea, while concepts 4-6 are quite different categories from their focal idea. Concept 7 (hamburger meat) served as a benchmark: it was designed as an intentionally unattractive idea, and it was used to see if people were really paying attention to the survey or just answering randomly.  The survey first asked some background questions (gender, age, employment status, and usage of energy products), then asked four questions for each of the seven concepts. The four questions for each concept were about 1) purchase intent, 2) uniqueness of the product idea, 3) projected usage frequency, and 4) substitution behavior. The content of the module focuses on the analysis of the responses to the intent, uniqueness, and frequency questions.  The Excel workbook for this module consists of 3 tabs. 1. The “Data” tab contains all the raw data gathered from the 150 survey respondents. 2. The “concepts” tab contains the exact statements of the concepts. 3. The “response codes” tab contains the meaning of the response values for the *gender, age, employment status, intent, uniqueness, and frequency questions. 1 *While we acknowledge that gender isn’t binary, the data you will be looking at reflects the original survey questions and response options at the time the data was collected which included questions about gender.

Part 0: Mean and Weighted Mean Given a large set of data, it can be desirable to summarize the general tendencies of the data. One of the most common summarizing computations is that of the mean of the data. In some cases, you may want to allocate more/less weight to certain data and compute a weighted mean. To begin this Module, view the screencast Mean and Weighted Mean . Part 1: Purchase Intent Each respondent was asked a purchase intent question for each concept: “Based on the description, how likely would you be to purchase this product?” This is a standard question in market research for consumer products. In the data file, the responses to the purchase intent questions are in columns labeled INTENT(1) through INTENT(7), corresponding to Concept 1 through Concept 7 above. In those columns,  1 means the respondent answered, “Definitely would not,”  2 means “Probably would not,”  3 means “Might or might not,”  4 means “Probably would,” and  5 means “Definitely would." Note: 0 indicates that the respondent did not answer the question. 1) Average Purchase Intent a. For each concept, find the average purchase intent response. Also, find the number of people who answered the purchase intent question for each concept. # Concept Name Average Purchase Intent Number of Responses 1 Caffeinated chocolate bar 2.4857 140 2 Caffeinated cookies 1.8733 2 *While we acknowledge that gender isn’t binary, the data you will be looking at reflects the original survey questions and response options at the time the data was collected which included questions about gender. Screencast

3 Caffeinated chocolates 140 4 Caffeinated potato chips 5 Caffeinated water 2.0432 139 6 Caffeinated cereal/granola 1.7214 7 Caffeinated hamburger meat 142 b. Which concept has the highest average score for purchase intent? caffeinated chocolates c. Which concept has the lowest average score for purchase intent? hamburger meat 2) Distribution of Responses For each concept, what percentage of the responses are 1s, 2s, etc.? Give your answers as percentages to two decimal places. Distribution of Responses for Purchase Intent # Concept %1s %2s %3s %4s %5s 1 Caffeinated chocolate bar 26.43% 23.57% 29.29% 4 Caffeinated Potato Chips 17.73% 6.38% 3) Graphs of Distribution of Responses Below is a bar graph showing the distribution of responses for Caffeinated chocolates (Concept 3). 3 *While we acknowledge that gender isn’t binary, the data you will be looking at reflects the original survey questions and response options at the time the data was collected which included questions about gender.

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0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00% 35.00% Definitely would not purchase Probably would not purchase Might or might not purchase Probably would purchase Definitely would purchase Relative frequency of Purchase Intent reponses for the Caffeinated chocolates concept, n = 140 Create a similar graph in Excel showing the distribution for Caffeinated potato chips (Concept 4). 4) Top-Two Boxes Some companies look at the “top-two boxes” score for concepts. The top-two boxes score is the percentage of respondents who answered, “Probably would” plus the percentage of respondents who answered, “Definitely would.” For example, if 6% of respondents answered, “Definitely would” (a response of 5 in the data) for one of the concepts and 20% of respondents answered, “Probably would” (a response of 4 in the data) for that concept, then the top-two boxes score for that concept is 26%. A. What is the top-two boxes score for the Caffeinated cookies (Concept 2)? 6.34% B. Which of the seven concepts has the highest top-two boxes score? 4 *While we acknowledge that gender isn’t binary, the data you will be looking at reflects the original survey questions and response options at the time the data was collected which included questions about gender.

chocolates Purchase intent responses can be coded as probabilities. One way of translating the response phrases to probabilities is as follows:  Definitely would not = 0% chance,  Probably would not = 25% chance,  Might or might not = 50% chance,  Probably would = 75% chance, and  Definitely would = 100% chance. 5) Average Purchase Probabilities a. Using the probabilities above, what is the average probability of purchase for each of the seven concepts? Use all the responses, not just the top-two boxes. Average Purchase Probabilities, Using 0% , 25% , 50% , 75% , 100% # Concept Average Purchase Probability 1 Caffeinated chocolate bar 37.14% 2 Caffeinated cookies 21.83% 3 Caffeinated chocolates 4 Caffeinated potato chips 5 Caffeinated water 6 Caffeinated cereal/granola 18.04% 7 Caffeinated hamburger meat b. Which concept has the highest average probability of purchase? c. Which concept has the lowest average probability of purchase? Concept 6 d. If Concept A has a higher Average Purchase Intent (using the 1-5 scale) than Concept B, will Concept A necessarily have a higher Average Purchase Probability (using the 0%, 25%, 50%, 75%, 100% scale) than Concept B? (Note that you should not answer this question considering only the data presented from this survey, but in general for any survey results.) 5 *While we acknowledge that gender isn’t binary, the data you will be looking at reflects the original survey questions and response options at the time the data was collected which included questions about gender.

In this scenario, yes. People often overstate their intention to purchase. Instead of 0%, 25%, 50%, 75%, and 100%, a more realistic translation from response phrases to probabilities is as follows:  Definitely would not = 0% chance,  Probably would not = 2% chance,  Might or might not = 55% chance,  Probably would = 60% chance, and  Definitely would = 65% chance. 6) Using these values, what is the average probability of purchase for each of the seven concepts? Average Purchase Probabilities, Using 0% , 2% , 55% , 60% , 65% # Concept Average Purchase Probability 1 Caffeinated chocolate bar 29.22% 2 Caffeinated cookies 13.11% 3 Caffeinated chocolates 4 Caffeinated potato chips 5 Caffeinated water 6 Caffeinated cereal/granola 7 Caffeinated hamburger meat 2.62% a. Which concept has the highest average probability of purchase? Concept 1 b. Which concept has the lowest average probability of purchase? concept 7 6 *While we acknowledge that gender isn’t binary, the data you will be looking at reflects the original survey questions and response options at the time the data was collected which included questions about gender.

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c. If Concept A has a higher Average Purchase Intent (using the 1-5 scale) than Concept B, will Concept A necessarily have a higher Average Purchase Probability (using the 0%, 2%, 55%, 60%, 65% scale) than Concept B? (Note that you should not answer this question considering only the data presented from this survey, but in general for any survey results.) NO, it depends on the weight of the purchase probability. 7) Comparing Top-Two Boxes Percentages and Average Purchase Probabilities TRUE or FALSE: If a concept has the largest top-two boxes score, it will also have the highest average purchase probability. Explain your answer. FALSE it depends on the weights of the Purchase probability. 7 *While we acknowledge that gender isn’t binary, the data you will be looking at reflects the original survey questions and response options at the time the data was collected which included questions about gender.

8 *While we acknowledge that gender isn’t binary, the data you will be looking at reflects the original survey questions and response options at the time the data was collected which included questions about gender.

Part 2: Frequency and Uniqueness Each respondent was asked, “If you tried this product and it met your expectations for taste and effectiveness, how often could you see yourself using it?” This is a standard question in market research for non-durable consumer products. In the data file, the responses to the frequency questions are in columns labeled FREQ(1) through FREQ(7), corresponding to Concept 1 through Concept 7 as shown at the beginning of the module. In these columns,  1 means the respondent answered, “Once a month or less often,”  2 means “More than once a month, but less than once a week,”  3 means “1 to 3 times a week,”  4 means “More than 3 times a week,” and  5 means “Don’t know.” Note: 0 indicates that the respondent did not answer the question. 1) Distribution of Responses For each concept, what percentage of the responses are 1s, 2s, etc.? Give your answers as percentages to two decimal places. Distribution of Responses for Frequency # Concept %1s %2s %3s %4s %5s 5 Caffeinated water 57.78% 10.37% 14.81% 6 Caffeinated cereal/granola 60.90% 21.05% You can use the frequency responses to estimate annual usage behavior. Like our translation of intent responses to probabilities, you can translate the frequency responses to annual usage numbers. Of course, these are just estimates, but they give a reasonable approximation. Use the following values.  Once a month or less often = 5 times a year 9 *While we acknowledge that gender isn’t binary, the data you will be looking at reflects the original survey questions and response options at the time the data was collected which included questions about gender.

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 More than once a month but less than once a week = 20 times a year  1 to 3 times a week = 55 times a year  More than 3 times a week = 100 times a year  Don’t know = 0 times a year. Notice that these values are conservative translations, assuming people overstate their intentions. 2) Estimated Annual Usage Using these values, find the estimated annual usage for each concept. Estimated Annual Usage, Using 5 , 20 , 55 , 100 , 0 # Concept Estimated Annual Usage 1 Caffeinated chocolate bar 12.0741 2 Caffeinated cookies 8.2353 3 Caffeinated chocolates 4 Caffeinated potato chips 5 Caffeinated water 6 Caffeinated cereal/granola 9.1729 7 Caffeinated hamburger meat 3) TRUE or FALSE: If the numeric values of annual usage were changed from 5, 20, 55, 100, and 0 to the values 7, 21, 65, 115, and 0, the estimated annual usage of every concept would increase or stay the same, no matter what the actual responses to the survey were. Why? FALSE 4) Normalizing: Excluding the Don’t Knows Above, you treated “Don’t know” as “won’t buy.” That is, you estimated 0 annual usage for 10 *While we acknowledge that gender isn’t binary, the data you will be looking at reflects the original survey questions and response options at the time the data was collected which included questions about gender.

people who responded “Don’t know” to the frequency question. That’s a somewhat extreme assumption. a. Instead, you could just ignore or exclude the “Don’t know” responses. To do that, look at the percent of each response out of the total number of responses 1-4. Find those percentages and fill in the chart below. Distribution of Responses for Frequency, Excluding Don’t Know (5) # Concept %1s %2s %3s %4s 3 Caffeinated chocolates 20.17% 12.61% 5 Caffeinated water 17.39% 12.17% b. Using the same estimates of frequency for responses 1-4 from above (e.g., a response of 1, which is “Once a month or less often” means 5 times a year), find the estimated annual usage for each concept. Estimated Annual Usage, Excluding Don’t Know (5) # Concept Estimated Annual Usage 1 Caffeinated chocolate bar 14.2982 2 Caffeinated cookies 10.7692 3 Caffeinated chocolates 4 Caffeinated potato chips 5 Caffeinated water 6 Caffeinated cereal/granola 11.6190 7 Caffeinated hamburger meat c. The estimated annual usage for each concept is higher when the “Don’t know” responses are excluded. Why? 11 *While we acknowledge that gender isn’t binary, the data you will be looking at reflects the original survey questions and response options at the time the data was collected which included questions about gender.

The value is an average, when we exclude the low-ranking answers from the average, the entire value will increase. In the data file, the responses to the frequency questions are in columns labeled UNIQ(1) through UNIQ(7), corresponding to Concept 1 through Concept 7 as shown at the beginning of the module. In these columns,  1 means the respondent answered, “There is nothing else like it,”  2 means “There are other products that are something like this,”  3 means “There are other products that are just like this,”  4 means “There are a lot of other products that are just like this,” and  5 means “Don’t know.” Note: 0 indicates that the respondent did not answer the question. 5) Distribution of Responses for Uniqueness For each concept, what percentage of the responses are 1s, 2s, etc.? Give your answers as percentages to two decimal places. Distribution of Responses for Uniqueness # Concept %1s %2s %3s %4s %5s 3 Caffeinated chocolates 26.09% 5.80% 24.64% 4 Caffeinated potato chips 76.64% 20.44% 12 *While we acknowledge that gender isn’t binary, the data you will be looking at reflects the original survey questions and response options at the time the data was collected which included questions about gender.

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Part 3: By Employment Status and Age The column labeled EMP has responses to a question about employment. The responses are coded as follows:  1 means Student  2 means Work part time  3 means Work full time  4 means Unemployed The column labeled AGE has responses to a question about age. The responses are coded as follows:  1 means the respondent answered under 18 years old  2 means 18-25 years old  3 means 26-35 years old  4 means 36-45 years old  5 means 46-55 years old  6 means 56-65 years old  7 means 66-75 years old  8 means over 75 years old Note: 0 indicates that the respondent did not answer the question. 1) For each concept, find the average purchase intent (INTENT) response by Student respondents. Purchase Intent by Student Respondents # Concept Average Purchase Intent Number of Responses 1 Caffeinated chocolate bar 2.5652 23 2 Caffeinated cookies 24 3 Caffeinated chocolates 23 4 Caffeinated potato chips 1.3913 5 Caffeinated water 1.7826 13 *While we acknowledge that gender isn’t binary, the data you will be looking at reflects the original survey questions and response options at the time the data was collected which included questions about gender.

6 Caffeinated cereal/granola 1.6522 7 Caffeinated hamburger meat 24 2) For which of the seven concepts do students have higher average purchase intent than those who work full time? 3) Find the average purchase intent (INTENT) response by respondents 35 and under. Purchase Intent by Respondents 35 and under # Concept Average Purchase Intent Number of Responses 1 Caffeinated chocolate bar 2.6727 55 2 Caffeinated cookies 2.0526 57 3 Caffeinated chocolates 2.8182 4 Caffeinated potato chips 5 Caffeinated water 6 Caffeinated cereal/granola 7 Caffeinated hamburger meat 1.2500 56 4) For which of the seven concepts do respondents aged 35 and under have higher average purchase intent than respondents over 35? 2.345238 1 1.75 2.392857 14 1.392857 14 14 *While we acknowledge that gender isn’t binary, the data you will be looking at reflects the original survey questions and response options at the time the data was collected which included questions about gender.

2.047619 05 1.642857 14 1.154761 9 5) Distribution of Responses For each concept, determine what percentage of the frequency (FREQ) responses from Work full time respondents 55 and under are 1s, 2s, etc.? Give your answers as percentages to two decimal places. # Concept % 1s %2s %3s %4s %5s 3 Caffeinated chocolate 59.15% 9.86% 4 Caffeinated potato chips 61.11% 31.94% Part 4: Excluding Low Quality Responses The “caffeinated hamburger meat” concept wasn’t a real concept—it was just a check to see if people were paying attention to the survey. Although it is possible that someone would have a high purchase intent for that concept, the concept was included to help screen out people who were not taking the survey seriously. When people took the survey, the response for “Definitely would” was the closest to the “advance to the next screen” button, so people who were just trying to speed through the survey would be more likely to give that response. The company also wants to screen out people who didn’t answer all the INTENT, UNIQ, and FREQ questions. 15 *While we acknowledge that gender isn’t binary, the data you will be looking at reflects the original survey questions and response options at the time the data was collected which included questions about gender.

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1) Find the average purchase intent responses, excluding “low quality” responses. By definition, a low-quality response is a response in any row in the data set that meets at least one of these criteria:  a response of 3, 4, or 5 for purchase intent on Concept 7 (INTENT(7))  failure to answer all twenty-one INTENT, UNIQ, and FREQ questions. There are many ways to exclude the low-quality responses. Try to avoid using a manual process like deleting each of the low-quality rows. (Imagine if the data set had 150,000 rows instead of 150: you wouldn’t want to go through all of them, one by one.) Purchase Intent, Excluding Low Quality Responses # Concept Average Purchase Intent Number of Responses 1 Caffeinated chocolate bar 2.4960 125 2 Caffeinated cookies 3 Caffeinated chocolates 4 Caffeinated potato chips 5 Caffeinated water 2.0080 6 Caffeinated cereal/granola 1.7360 7 Caffeinated hamburger meat 16 *While we acknowledge that gender isn’t binary, the data you will be looking at reflects the original survey questions and response options at the time the data was collected which included questions about gender.

Selected Answers Part 1 1) b) Caffeinated chocolates (Concept 3) has the highest average purchase intent (2.5643). c) Caffeinated hamburger meat (Concept 7) has the lowest average purchase intent (1.2113). 2) Hint: Calculate the distribution of responses for the other concepts as well. 3) 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% Definitely would not purchase Probably would not purchase Might or might not purchase Probably would purchase Definitely would purchase Relative frequency of Purchase Intent reponses for the Caffeinated potato chips concept, n = 141 4) b) Concept 3 has the highest top-two boxes score (22.14%) 5) b) Caffeinated chocolates has the highest average probability of purchase (39.11%) c) Caffeinated hamburger meat has the lowest average probability of purchase (5.28%) d) The answer is “yes”, independent of the specific survey results. 6) a) Caffeinated chocolate bar has the highest average probability of purchase (29.22%) c) Although it is possible, in this case and in general, the answer is “no”. 7) Although it will often be the case that the concept with the largest top-two boxes score is the one with the highest average purchase probability, in general, the statement is false Part 2 1) Hint: Calculate the distribution of responses for the other concepts as well. 2) 3) True. Because the usage estimate for every category of response increased or stayed the same, the estimated annual usage for each concept will increase or stay the same, no matter what the survey results were. 4) c)When included, the “Don’t Know” responses were counted as “0 consumed” which lowered the average. 17 *While we acknowledge that gender isn’t binary, the data you will be looking at reflects the original survey questions and response options at the time the data was collected which included questions about gender.

Part 3 2) Students have higher average purchase intent than those who work full time for Concepts, 1,2,3,4,7. 18 *While we acknowledge that gender isn’t binary, the data you will be looking at reflects the original survey questions and response options at the time the data was collected which included questions about gender.

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Module 7 Chapter-F2F

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