AMC Seltzer Final Analysis Report
Revolutionizing the Hard Seltzer Surge
Ariana Fazal, Myrto Kampouris, Christian Lane
December 12, 2021
Abstract
In this project, we are studying alcoholic seltzers in the alcoholic beverage market. The alcoholic seltzer market is a booming industry, expected to grow to a market size of $13.4 billion dollars by 2028 (source). Current competitors have created hard seltzer products with various combinations of product attributes, such as vitamin presence and low calorie content. As a startup hard seltzer company, we are surveying to assess which combination of product attributes is most lucrative for a new line of premium hard seltzers. Specifically, we hypothesized that there may be a legitimate opportunity to capture a significant share of the hard seltzer market by introducing a premium hard seltzer that is packaged in glass bottles, replicating the Corona effect in the beer market, and contains nutritional benefits such as low calories and vitamin presence. As a result, we surveyed the impact that the following key product attributes have on the hard seltzer consumer: price, packaging material, calories per unit, vitamin presence, sugar content, and alcohol content. Each of these attributes furthermore affects the decision variables for product design, which include price, packaging material, and nutritional benefits. Based on our market utility analysis, the decision to package hard seltzers in glass bottles is the least significant design decision assessed in terms of capturing market share. Price, alcohol content, and calories are dominating attributes for determining product market share. Therefore, as demonstrated in this report, our main recommendation is to maintain a low, competitive price while also prioritizing the production of a high alcohol content, low-calorie hard seltzer, and our secondary recommendation for capturing additional marginal market share is, if financially feasible, to market the hard seltzer product with vitamins and low sugar content.
Introduction
In recent years, hard seltzers have become a growing trend and have exploded all over social media. Various brands have emerged and previously existing alcoholic beverage brands have expanded to create their own line of hard seltzers to keep up with the competition and meet this new demand. We are analyzing what key attributes of a hard seltzer could out-compete with the ever-expanding hard seltzer market and incorporate those into our own new product. Our key attributes are price, sugar, alcohol content, vitamins, and material. We anticipate there will be a competitive advantage to packaging the hard seltzers into glass bottles as opposed to the standard aluminum cans. The inspiration of our design is based on capturing the “Corona on the beach” vibe; Corona beer in a glass bottle represents an upscale style of consuming beer (i.e. who would drink a Corona in a can?), and we want to replicate that effect with a line of hard seltzers. While it could come at a premium price, introducing desirable qualities such as low calories and antioxidant vitamin content will create a deluxe atmosphere around the product.
Survey Design
Our target population is open to all men and women over the age of 21. We are anticipating that our respondents will be in the subpopulation of men and women ages 21-35 because of our enhanced access to undergraduate, graduate, and doctoral students on GWU’s campus. Additionally, our sample size was amended by creating a Prolific account, which is a platform for survey sample collection. Given legal alcohol consumption is limited to individuals 21 and older, this question would ensure that all participants are viable customers.
In terms of data collection, we elicited each respondent’s year of birth (age), gender, income level, and zip code. We also asked two yes/no questions regarding whether the respondent enjoys alcohol and whether the respondent has ever consumed a hard seltzer. As an additional part of our survey design, we provided four real competing seltzer brands - Truly, Vizzy, Michelob Ultra, and Cacti - from which each respondent would choose their favorite of the four brands. The series of following conjoint questions would then present images of glass bottle or aluminum can seltzer designs reflecting the respondent’s brand of choice throughout the rest of the survey.
The product attributes being surveyed include: price, calories, sugar content, vitamin presence, alcohol content, and the material of the product. Price is the amount you pay per pack of 12 seltzers; calories is the amount of calories per serving; sugar content is the grams of sugar per serving; vitamins is the presence of vitamins in the seltzer beverage; alcohol content is the percentage of alcohol per serving (%ABV); material is the type of material of the unit (aluminum can or glass bottle). The ranges of each attribute were decided relative to the ranges of existing competition (See the competitor product attributes in the (Model Relationships Table)). The range of price per package is $15-21. Our calorie count is between 80-100 calories, our hard seltzer will either include or not include vitamins, and the sugar content will range 0-2 grams. The range of alcohol content is 4%-7% ABV. As for the material of the product, we would entertain an aluminum can and a glass bottle. For these attributes, we would present three different choices that have randomized values from the stated ranges for each attribute. The respondent would then choose which of the three choices they would prefer. We have eight choice questions per respondent configured this way, none of which includes a “no-choice” option.
Here is an example of a conjoint question we are asking in our survey:
Data Analysis
Sample Description
Our target demographic was anyone over the age of 21 and living in the U.S. We had a total of eight choice questions that were designed to help determine which attributes most of our respondents prioritized. In addition, we gathered some background information on our respondents which included age, gender, income, zip code, if they enjoy drinking alcoholic beverages, and if they had ever consumed hard seltzers.
Based on our data, we had a total of 210 respondents taking our survey, which was deduced by dividing the total entries in the survey data by 24 (8 choice questions with 3 options per question). The age range of our respondents was between 21 and 70 years old, with the mean age of 31.48 (31), the median age of 28, and a standard deviation of about 11. We also collected the gender of each respondent, which determined 99 men, 107 women, and 4 respondents who preferred not to say took the survey. For the first critical information question, asking if the respondent enjoys consuming alcoholic beverages, 189 out of 210 respondents answered yes, while 21 respondents did not enjoy drinking alcoholic beverages. For the second critical information question, asking if the respondent had ever consumed a hard seltzer, 194 out of 210 respondents answered yes, and the remaining 16 respondents answered no. From these demographic and informational questions, it is affirming that we are reaching a market that mostly enjoys drinking alcoholic beverages and have experienced consuming hard seltzers. The number of respondents who classified themselves as having an annual income below $30k was 37; for $30-60k, 55 respondents; for $60-90k, 54 respondents; for $90-120k 25; for $120k and above, 32 respondents; and 7 respondents did not share. In terms of the sample’s most preferred hard seltzer brand, Truly is the clear favorite, with 152 of 210 respondents (72%) selecting Truly. Vizzy came in second place, with 36 respondent selections (17%); Michelob Ultra returned 16 selections (8%); and Cacti came in last place with 6 respondent selections (3%). This diverse sample size and respondent information not only confirms that our survey captured many dimensions of the overall market, but also provides sufficient information to determine whether there are niche demographic subgroups for a specific hard seltzer experience, such as seltzers packaged in glass bottles.
Data Cleaning
The only way we ascertained such summary data of our survey sample is by cleaning the collection of data entries. After importing the CSV files that correspond to both sections of our survey in the survey platform formr, we began the process of cleaning the data. The first step was to compute the time values for each part and join both parts together using the session variable. The next step was to filter out bad responses and drop anyone who did not complete all the choices, filled out the survey too quickly, and got the attention check question wrong. We initially had 336 rows of data which then dropped to 246 after dropping anyone who didn’t complete all the choice questions. This number then dropped to 221 once we dropped anyone who finished in under the 10th percentile of completion times. From this leftover data, 11 people got the attention check question wrong. In summary, we went from 336 initial rows of data to 210 valid rows of data to analyze. Next, we created a reorganized choice data set. To do so, we gathered the data and used the pivot_longer function to create two new columns named “qID” and “choice,” and we converted the qID variable to a number. Then, we read in the choice questions from our Github survey CSV and joined it to the new data frame we created using the left_join function. After this, we converted the choice column to 1 or 0 based on if the alternative was chosen. And finally, we created new values for the respondent ID and observation ID, and reordered the columns in order to read the ID variables first. Once we completed all of the data cleaning steps, we created a new CSV file to proceed with modeling and analysis of the data.
Modeling
Below is the specific utility model equation we estimated for our baseline logit model, as well as a summary table presenting the utility coefficients ( \(\beta_i\) ) of each attribute and the set of attribute utility plots from the cleaned survey data. For conceptual understanding, continuous attribute coefficient values (price, calories, sugar, alcohol content), may be interpreted as the increase in utility per unit increase in attribute value; discrete attribute coefficient values for vitamin presence and glass bottles may be interpreted as the increase in utility by having vitamins instead of no vitamins, and the utility in having seltzers in glass bottles instead of aluminum cans.
\[u_j = \beta_1 x_j^{\mathrm{price}} + \beta_2 x_j^{\mathrm{calories}} + \beta_3 x_j^{\mathrm{sugar}} + \beta_4 x_j^{\mathrm{alc. content}} + \beta_5 \delta_j^{\mathrm{vitamins}} + \beta_6 \delta_j^{\mathrm{glass.bottle}} + \varepsilon_j\]
| Attribute | Estimate | Std. Error |
|---|---|---|
| Price | -0.4502117 | 0.0181329 |
| Calories | -0.0272422 | 0.0044861 |
| Sugar | -0.1762879 | 0.0443789 |
| Alcohol Content | 0.3740892 | 0.0300725 |
| Vitamins | 0.2904797 | 0.0716541 |
| Glass Bottle | 0.1439421 | 0.0726119 |
At a high level analysis, our findings indicate that higher prices, calories, and sugar deliver lower levels of utility to the consumer. Consumers prefer higher alcohol content, and very marginal preferences for vitamin presence drinking hard seltzers from a glass bottle relative to an aluminum can.
Diving deeper into the continuous attributes - price, calories, sugar, and alcohol content - the Utility plots demonstrate the uncertainty around the relationships between those attributes and utility by plotting the bounds of each coefficient’s 95% confidence interval. When analyzing the plots for price, calories, and sugar, the bounds of each plot do not vary much, which implies that we can be 95% confident that the relationships between price and utility, calories and utility, and sugar and utility are all negative. Thus, consumers prefer lower prices, lower calories, and lower sugar content. Conversely, the coefficient estimate for alcohol content was positive with a steep slope and narrow 95% confidence interval bounds in its utility vs. alcohol content plot, which implies that people definitely prefer higher alcohol content in their hard seltzers.
Looking at the discrete attributes - vitamin presence, and material - the utility plots demonstrate the uncertainty via each coefficient’s 95% confidence interval. Here, the upper and lower bounds are based on the discrete points rather than the linear relationship. For both vitamin presence and material, the lower bounds of each of their coefficient’s 95% confidence interval are greater than zero, which implies that we can be 95% confident that consumers prefer, at least to some extent, vitamins to no vitamins, and that consumers would rather drink hard seltzers from a glass bottle instead of an aluminum can. While this supports our goal of determining the worth of creating a premium seltzer brand that is packaged in a glass bottle as opposed to an aluminum can, the preference of glass bottle over aluminum can is quantified in dollar terms in the willingness to pay models of our analysis results.
Results
WTP Original Logit Model
Below are the results from the original logit willingness to pay (WTP) model, which include a summary table presenting mean willingness to pay in dollars of each attribute, the upper and lower bounds of the mean willingness to pay of each attribute as determined by its 95% confidence intervals, and the set of attribute willingness to pay plots. For conceptual understanding, continuous attribute mean WTP values (price, calories, sugar, alcohol content), may be interpreted as the average dollar increase in consumer willingness to pay per unit increase in attribute value; discrete attribute mean WTP values for vitamin presence and glass bottles may be interpreted as the average consumer’s willingness to pay in dollars for having vitamins instead of no vitamins in their hard seltzer, and the average consumer’s willingness to pay in dollars for having hard seltzers in glass bottles instead of aluminum cans.
| Attribute | Mean | Lower | Upper |
|---|---|---|---|
| Calories | -0.0605574 | -0.0799975 | -0.0410033 |
| Sugar | -0.3916810 | -0.5863524 | -0.1970637 |
| Alcohol Content | 0.8309400 | 0.7009725 | 0.9611342 |
| Vitamins | 0.6455813 | 0.3303888 | 0.9602828 |
| Glass Bottle | 0.3188147 | 0.0043864 | 0.6330820 |
The first willingness to pay plot shows that there is a significant willingness to pay for lower calories. The average willingness to pay per unit increase in calories is -$0.06 per calorie, meaning that people on average would be willing to pay $1.20 more for an 80-calorie option over a 100-calorie option, and $0.60 more for a 90-calorie option over a 100-calorie option. The second plot shows a similar trend for sugar to that of calories; people are more willing to pay more for a hard seltzer with fewer grams of sugar. An interesting and likely the most significant finding from the next plot is that people are big fans of alcohol! In fact, on average, people are willing to pay more than $2 for a 7% ABV (alcohol-by-volume) seltzer over 4% ABV, and over $1.50 for 7% ABV seltzer over 5% ABV seltzer. When looking at the WTP model for vitamins, we can see that people have a slight willingness to pay more for a hard seltzer that has vitamins with a mean WTP value of $0.64. Our initial assumption was that people would prefer to drink a hard seltzer in a glass bottle rather than in an aluminum can in order to attain the premium drinking experience. However, in this original willingness to pay logit model, we discovered that packaging a hard seltzer in a glass bottle does not yield a very high willingness to pay from our sample of respondents. Although there is a 95% confidence that there is definitely a willingness to pay for this attribute (since the lower and upper values from the Table of WTP with 95% CI are greater than 0), it is very marginally preferred, and a meant WTP of almost $0.32, and may not be worth the premium production cost of a glass bottle over aluminum can. From this model, the alcohol content seems to be a leading attribute in developing an ideal hard seltzer.
WTP Mixed Logit Model
Below are the results from the mixed logit willingness to pay (WTP) model, which include a summary table presenting mean willingness to pay in dollars of each attribute, the upper and lower bounds of the mean willingness to pay of each attribute as determined by its 95% confidence intervals, and the set of attribute willingness to pay plots. Creating a mixed logit model fits the willingness to pay of attribute to normal distributions, which assumes that the willingness to pay for each attribute is normally distributed (the main difference between the original and mixed logit models).
| Attribute | Mean | Lower | Upper |
|---|---|---|---|
| Calories | -0.0638052 | -0.0850406 | -0.0426757 |
| Sugar | -0.3287235 | -0.5388337 | -0.1191905 |
| Alcohol Content | 0.8115297 | 0.6697131 | 0.9532127 |
| Vitamins | 0.7978660 | 0.3718537 | 1.2206222 |
| Glass Bottle | 0.7044796 | 0.3507261 | 1.0575074 |
When comparing the plots from the mixed logit model to those of the original WTP logit model, all trends remain the same with minute differences among the mean values of each attribute. While there is no difference in mean WTP for calories or sugar, mean WTP for alcohol content is $0.02 less than the original WTP logit model, the mean WTP of vitamins increased by $0.15, and the mean WTP for glass bottle material increased by $0.38. While the mean WTP for glass bottle seltzers more than doubled with the normally distributed assumption in the mixed logit model, it is still the most marginal difference when considering the range of values for continuous attributes. Even considering this small increase in WTP, when comparing across all attributes by looking at the plot, the overall behavior of WTP among all attributes does not change. Furthermore, since the purpose of this project is to investigate the potential of a hard seltzer market with a glass bottle, we investigated if there’s a significant difference between subgroup willingness to pay for a glass bottle by analyzing first gender, then income.
Sub Group Analysis
Below are the results from our subgroup analysis on gender, with a focus on male and female willingness to pay for hard seltzers in a glass bottle.
Gender
Based on our plots, it indicated that females showed a marginally higher mean WTP for glass bottles than males. Likely due to the sample size being cut in half, both samples display negative lower bounds on a 95% confidence interval, thus, we cannot determine with 95% confidence that either gender maintains a willingness to pay for a glass. Since there is not sufficient evidence on WTP for a certain gender, and the difference in mean WTP extremely marginal, we cannot warrant targeting a bottled seltzer based on gender demographics.When assessing the willingness to pay of the remaining attributes, there was no significant difference between the male and female subgroups, as shown in the male and female willingness to pay plots in the Appendix of this report. The next subgroup analysis of willingness to pay for glass bottle hard seltzers is income level.
Income
Below are the results from our subgroup analysis on income, with a focus on the five income levels’ willingness to pay for hard seltzers in a glass bottle.
Our data for the WTP for a glass bottle based on income level does not yield a WTP greater than zero for any income level with 95% confidence. However, even if we overlook the large upper and lower bounds of the mean WTP per income level to determine if there is any correlation between income level and mean WTP, the plot shows that as income level increases, the WTP fluctuates and fails to yield a trend of any kind, positive or negative. In fact, our initial expectation was that as the income level increases, the willingness to pay for a glass bottle will also increase, but as seen in the plot, the lowest income level - less than $30k - had the greatest mean willingness to pay for glass bottles. We could speculate that a reason that the lowest income level is most willing to pay for a glass bottle, considered a premium attribute, is that the respondent who associated themselves as without an income could be reliant on parental financial support, but we do not have any data to back up that claim. Thus, income level WTP results also did not provide sufficient evidence to target a bottled seltzer toward a specific income level.
Sensitivity Analysis
Product Price
After iteratively running six market share simulations to test the relationship between the levels of product attributes and market share, we used the combination of attributes from the last iterative simulation and further investigated the sensitivity of market share relative to changes in product price, and the resulting sensitivity of revenue to changes in product price in a market size of 1000 people. Representative sensitivity plots with 95% confidence lower and upper bounds of the mean market share and revenue are respectively shown below. It is evident from the pair of plots that, keeping constant the 80 calories, 1 gram of sugar, vitamins, 7% alcohol content, and the aluminum can, market share is very sensitive to price, and revenue is not as sensitive from the $15-18 range, but starts to significantly decrease as price increases from $18. Thus, following the pair of plots, discounting price from $19.50 to $18 not only increases average market share by more than 15%, but also increases revenue by almost $3 million per market size of 1000 people.
Alcohol Content
Based on the results from the willingness to pay and iterative market share simulation analyses, we also wanted to test the sensitivity of our product’s market share relative to changes in alcohol content via %ABV. Keeping all other product attributes of the “ideal” combination constant, the sensitivity of our product’s mean market share relative to changes in alcohol content is shown in the plot below with 95% confidence upper and lower bounds. Based on this plot, even decreasing the %ABV of our product by 1% (from 7% to 6%) decreases our mean market share by almost 14%, which is extremely sensitive and contributes to the high market willingness to pay for high alcohol content.
Multi-Attribute Sensitivity Analysis
Having analyzed the sensitivity of our product’s market share relative to changes in price and alcohol content, we conducted a multi-attribute sensitivity analysis by compiling the sensitivity of product market share to changes in each product attribute in the tornado plot below. Using the “ideal” attribute combination ($19.50, 80 calories, 7% ABV, 1g sugar, vitamins, aluminum can) as a basis and previously analyzed ranges of attribute values, the tornado plot shows from top to bottom the attributes to which market share is most to least sensitive, i.e., which attributes drive consumer choice the most to the least in the hard seltzer market. As shown in the tornado plot below, price is the most dominating attribute for capturing market share. However, perhaps the most significant finding of this report is that this tornado plot demonstrates that the decision whether or not to pack seltzers in glass bottles captures the least market share out of all attribute decisions and drives consumer choice the least out of all attributes in the hard seltzer market. Therefore, our initial hypothesis of there being a competitive advantage for bottled hard seltzers is nullified, wherein our results indicate that high alcohol content and low calories at a competitive-to-low price are the design decisions on which we should focus for developing a hard seltzer that dominates the hard seltzer market.
Final Recommendations and Conclusions
At the outset of this project, we hypothesized that there is a competitive market advantage for packaging hard seltzers in glass bottles instead of aluminum cans. However, as outlined in our compilation of results and culminated in the multi-attribute sensitivity analysis, the decision whether or not to package hard seltzers in glass bottles or aluminum cans drives consumer choice the least out of all attributes in the hard seltzer market, which effectively negates our initial hypothesis and renders glass bottle hard seltzers insignificant. Although the willingness to pay analysis demonstrated 95% confidence in there being a WTP for a glass bottled hard seltzer, it was the most marginal WTP among all attributes. If our company already had a stake in the hard seltzer market, as well as the resources to afford and the desire to create a bottled hard seltzer, it can capture up to 4% more market share. However, the multi-attribute sensitivity analysis demonstrates that hard seltzer is not among the attributes that capture large portions of market share: price, alcohol content and calories are.
Our results, culminating multi-attribute sensitivity analysis, demonstrate that price, alcohol content, and calories are dominating attributes that drive consumer choice the most and determine product market share. Thus, our main design decision recommendation is to lower the price as much as possible, while also prioritizing the production of a high alcohol content, low calorie hard seltzer (7% ABV, 80 calories). This recommendation is very robust, as it is consistent with the high mean willingness to pay for high alcohol content and less calories, as well as the market share simulation results that showed a dominant hard seltzer product even with the highest-priced seltzer in the simulated market with real market competitors. If our company can maintain a competitively low price while delivering a low calorie, high alcohol content hard seltzer, the projected market share and revenue estimates are only set to increase.
Evidently, lowering price while ensuring a low calorie, high alcohol content hard seltzer is an inherent opportunity for increasing demand. However, another opportunity for increasing demand is to additionally invest in low sugar and vitamin presence. This is supported in our final iterated market share simulation, wherein we listed our product at a premium price ($0.51 higher than our highest-priced competitor). This showed us that there is a path to dominate market share by including high alcohol content, low calories, low sugar, and vitamin presence even when marketing our product at premium. Therefore, our secondary recommendation, if financially feasible, is to market the hard seltzer with vitamins and low sugar content (e.g., 0-1 grams of sugar). We still did not include glass bottle packaging in our secondary recommendation because even with its marginal market share advantage (approximately 4%), it is still the attribute that least drives consumer choice in the hard seltzer market, and we anticipate the marginal increase in market share would not be worth the added production cost of producing glass bottles instead of aluminum cans.
Limitations
In our project, there are certain sets of hard seltzer attributes that were left out of our model that could provide a greater context of the hard seltzer market. For example, our model does not include taste, flavors, or brands of hard seltzers, which could each impact consumer decision-making in the hard seltzer market. The budget given for creating this product is also outside the scope of this project, but assuming we have funding at our disposal, we can create our version of the most marketable and ideal seltzer. We are assuming that the combination of attributes we found are feasible to exist together, and do not account for cases in which certain optimal attribute levels are mutually exclusive. For example, our future research should entail how feasible low calories and high alcohol content are in the same beverage, since they are the top two design decisions in our main recommendation other than maintaining a competitive, low price.
Another limitation is our sample size. While we were able to collect clean survey samples from over 200 respondents, the more data we collect, the more holistic our results will be. A large sample size will also diminish the increased uncertainty in our subgroup analyses of gender and income level, which could then reveal more defined preferences based on those demographics… and who knows, maybe if we keep digging, there may be a bigger market for bottled hard seltzers than what we have discovered. However, as a startup firm looking to make a big splash in the hard seltzer market, this project has clearly revealed that we should focus our resources on developing a low-calorie, high alcohol content hard seltzer that maintains a competitive, low market price.
Appendix
Subgroup Analysis: Male WTP Plots
Subgroup Analysis: Female WTP Plots
AMC Seltzer Survey
Welcome to our survey!
We are AMC Seltzer and we are introducing our own new line of hard seltzers to compete with the ever-expanding hard seltzer market. In this survey, we are trying to assess what your ideal hard seltzer experience is. We want to test the competitive advantage of packaging hard seltzers in glass bottles as opposed to the standard aluminum cans. The inspiration of our design is based on capturing the “Corona on the beach” vibe; Corona beer in a glass bottle represents an upscale style of consuming beer (i.e. who would drink a Corona in a can?), and we aim to research if that effect can be replicated with a line of hard seltzers.
Consent form
Please be aware we are conducting a survey on alcoholic beverages which you must be 21 or older to consume. In order to collect relevant information for an alcoholic beverage market, we will be eliciting your date of birth, gender, and zip code in order to aggregate your information into a market data analysis. Please click “Consent” if you have read and understand the above information.
- Consent
Are you 21 years or older?
- yes
- no
Do you enjoy drinking alcoholic beverages?
- yes
- no
Have you ever had a hard seltzer?
- yes
- no
What is your favorite brand of hard seltzer from this selection?
Next!
Now that you’ve shared a bit about yourself, we’d like you to consider a shopping scenario in which you can choose a hard seltzer to purchase from a set of hard seltzers with different attributes.
Below is a list of attributes that pertain to variations of hard seltzer products:
Price per 12-pack
The amount you pay per pack of 12 seltzers, ranging from $15-$21.
Calories & Sugar Content
The amount of calories and grams of sugar per serving of hard seltzer, ranging from 80-100 calories and 0g-2g of sugar.
Vitamins
The presence of vitamin C and antioxidants in the hard seltzer.
Alcohol Content
The percentage of alcohol per serving of hard seltzer, ranging from 4%-7%.
Material
The type of material in which the hard seltzer is packaged in (i.e., aluminum can or glass bottle).
Now that you have a clear understanding of the attributes we are assessing, we are going to ask you about your preferences regarding hard seltzers with various combinations of these attributes.
In the following section, please anaylze each option based on their attributes, and choose which seltzer you would prefer. Your selection among a series of choices will help us gauge which qualities you find most important in a hard seltzer.
We’ll now begin the choice tasks. On the next few pages we will show you three options of hard seltzers and we’ll ask you to choose the one you most prefer.
For example, if these were your only options, which hard seltzer would you choose, given it is your favorite flavor?
[mc_button type question with the following three options]
Option 1
Price: $ 15 / 12-pack
Calories: 100
Sugar Content: 2g
Vitamins: No Vitamins
Alcohol Content: 4%
Material: Aluminum Can
Option 2
Price: $ 21 / 12-pack
Calories: 100
Sugar Content: 2g
Vitamins: No Vitamins
Alcohol Content: 4%
Material: Aluminum Can
Option 3
Price: $ 18 / 12-pack
Calories: 100
Sugar Content: 2g
Vitamins: No Vitamins
Alcohol Content: 4%
Material: Aluminum Can
Nice Work!
We will now show you 8 sets of choice questions starting on the next page.
[mc_button type question with the following three options]
(1 of 8) If these were your only options, which hard seltzer would you choose, given it is your favorite flavor?
Option 1
Price: $ 21 / 12-pack
Calories: 80
Sugar Content: 2 grams
Vitamins: Vitamins
Alcohol Content: 5 %
Material: Glass Bottle
Option 2
Price: $ 18 / 12-pack
Calories: 100
Sugar Content: 1 grams
Vitamins: No Vitamins
Alcohol Content: 4 %
Material: Glass Bottle
Option 3
Price: $ 15 / 12-pack
Calories: 100
Sugar Content: 2 grams
Vitamins: No Vitamins
Alcohol Content: 7 %
Material: Glass Bottle
Nice job!
We’re almost done! We’d just like to ask just a few more questions about you which we will only use for analyzing our survey data.
- In what year were you born?
[drop down menu]
- What is your gender ?
- Male
- Female
- Prefer not to say
- What is your zip code?
[open text]
- What is your annual household income?
- < $30,000
- $30,000-$60,000
- $60,000 - $90,000
- $90,000 - $120,000
- greater than $120,000
- Prefer not to share
- What is your Prolific ID? (if you don’t have one please type 123)
[open choice response]
Your completion code is: 158F6DF0
Finish