Understanding Nutritional Labeling: Case Study—Ice Cream

nutritional facts was based on the FDA defi nition of nutrient content claim “ Light ” (21 CFR 101. 60[b]).

4. Reduced Calorie Ice Cream: Another example of an FDA - oriented nutritional content claim. The nutri- tional facts panel was based on FDA defi nition of nutrient content claim “ Reduced Calorie ” (21 CFR 101.60[b]).

included the nutritional facts panel as well. You can see these different types in Figures 15.2 and 15.3 .

1. Original Ice Cream: The basic ice cream.

2. Organic Ice Cream: A “ healthful ” method of production.

3. Light Ice Cream: An example of an FDA - oriented, nutritional content claim. The panel content for

Serving Size 1/2 cup Nutrition Facts

“Original” & “Organic” “Light” “Reduced Calorie” “Heart Smart”

Amount Per Serving Calories 140 Total Fat 7 g Saturated Fat 4.5 g Trans Fat 0 g Cholesterol 20 mg Sodium 40 mg Total Carbohydrate 16 g Dietary Fiber 0 g Sugars 16 g Protein 3 g 11 % % Daily Value* 23 % 7 % 2 % 5 % 0 % 6 % Vitamin A 10% Vitamin C 0% Calcium 10 % Iron 0% *Percent Daily Values are based on a 2,000 calorie diet.

Calories from Fat 65 Servings Per Container 14

Serving Size 1/2 cup

Nutrition Facts Nutrition Facts

Amount Per Serving Calories 110 Total Fat 3.5 g Saturated Fat 2 g Trans Fat 0 g Cholesterol 10 mg Sodium 50 mg Total Carbohydrate 16 g Dietary Fiber 0 g Sugars 16 g Protein 3 g 5 % % Daily Value* 10 % 3 % 2 % 5 % 0 % 6 % Vitamin A 10% Vitamin C 0% Calcium 10 % Iron 0% *Percent Daily Values are based on a 2,000 calorie diet.

Calories from Fat 30 Servings Per Container 14

Serving Size 1/2 cup Amount Per Serving Calories 65 Total Fat 3 g Saturated Fat 2 g Trans Fat 0 g Cholesterol 10 mg Sodium 50 mg Total Carbohydrate 6.5 g Dietary Fiber 0 g Sugars 6.5 g Protein 3 g 5 % % Daily Value* 10 % 3 % 2 % 2 % 0 % 6 % Vitamin A 10% Vitamin C 0% Calcium 10 % Iron 0% *Percent Daily Values are based on a 2,000 calorie diet.

Calories from Fat 30 Servings Per Container 14

Nutrition Facts Serving Size 1/2 cup Amount Per Serving Calories 90 Total Fat 1.5 g Saturated Fat 1 g Trans Fat 0 g Cholesterol 10 mg Sodium 50 mg Total Carbohydrate 16 g Dietary Fiber 0 g Sugars 16 g Protein 3 g 2 % % Daily Value* 5 % 3 % 2 % 5 % 0 % 6 % Vitamin A 10% Vitamin C 0% Calcium 10 % Iron 0% *Percent Daily Values are based on a 2,000 calorie diet.

Calories from Fat 15 Servings Per Container 14

Figure 15.2 The different nutritional labels for Study 1, with a 140 - Calorie Original.

Serving Size 1/2 cup Nutrition Facts

“Original” & “Organic” “Light” “Reduced Calorie” “Heart Smart”

Amount Per Serving Calories 210 Total Fat 14 g Saturated Fat 10 g Trans Fat 0 g Cholesterol 50 mg Sodium 50 mg Total Carbohydrate 18 g Dietary Fiber 0 g Sugars 18 g Protein 3 g 22 % % Daily Value* 50 % 17 % 2 % 6 % 0 % 6 % Vitamin A 10% Vitamin C 0% Calcium 10 % Iron 0% *Percent Daily Values are based on a 2,000 calorie diet.

Calories from Fat 125 Servings Per Container 14

Serving Size 1/2 cup

Nutrition Facts Nutrition Facts

Amount Per Serving Calories 145 Total Fat 7 g Saturated Fat 5 g Trans Fat 0 g Cholesterol 25 mg Sodium 50 mg Total Carbohydrate 18 g Dietary Fiber 0 g Sugars 18 g Protein 3 g 11 % % Daily Value* 25 % 8 % 2 % 6 % 0 % 6 % Vitamin A 10% Vitamin C 0% Calcium 10 % Iron 0% *Percent Daily Values are based on a 2,000 calorie diet.

Calories from Fat 65 Servings Per Container 14

Serving Size 1/2 cup

Amount Per Serving Calories 95 Total Fat 6 g Saturated Fat 4 g Trans Fat 0 g Cholesterol 20 mg Sodium 50 mg Total Carbohydrate 7 g Dietary Fiber 0 g Sugars 7 g Protein 3 g 9 % % Daily Value* 20 % 7 % 2 % 2 % 0 % 6 % Vitamin A 10% Vitamin C 0% Calcium 10 % Iron 0% *Percent Daily Values are based on a 2,000 calorie diet.

Calories from Fat 55 Servings Per Container 14

Nutrition Facts Serving Size 1/2 cup

Amount Per Serving Calories 100 Total Fat 1.5 g Saturated Fat 1 g Trans Fat 0 g Cholesterol 10 mg Sodium 50 mg Total Carbohydrate 18 g Dietary Fiber 0 g Sugars 18 g Protein 3 g 2 % % Daily Value* 5 % 3 % 2 % 6 % 0 % 6 % Vitamin A 10% Vitamin C 0% Calcium 10 % Iron 0% *Percent Daily Values are based on a 2,000 calorie diet.

Calories from Fat 15 Servings Per Container 14

Study 2 worked with an “ original ice cream of 210 calories per serving ” with the nutrition facts panel of other ice cream type messages (category 2) including organic, light, reduced calorie, and heart smart, again changing appropriately for a 210 - calorie original.

Running the Ice Cream Study

E - mail Invitation

We used e - mail invitations, with each respondent getting one of the studies. Respondents did not have a chance to participate in both. Instead, any respondents were ran- domly allocated to the study. The invitations for both studies were identical. The invitation did not mention the specifi c content of either of the studies and simply included the following phrase: “ We would like to fi nd out what consumers like YOU think about different types of ice cream. ” We see this invitation in Figure 15.5 . It ’ s important to keep in mind here, and in the subsequent studies in other chapters, that a well - written invitation substantially increases the likelihood that an individual will accept the invitation. The text in Figure 15.5 can be used for future studies as well. All that one needs to do is change the topic and some of the information.

One important thing to keep in mind is how to offer incentives to get the respondents to participate. When the Internet fi rst appeared on the scene in the mid - to late 1990s, it was an exciting place to visit. People liked to participate. It was fun, novel, and interesting. As a result, it was pretty easy to fi nd respondents. Over time however, the Internet became simply another vehicle by which to connect with the outside world. Many respon- dents stopped participating so actively. Response rates dropped. What looked like a wonderful world in the late 1990s and early 2000s soon evolved to the typical research situation, with a lot of people rejecting the offer to participate.

5. Heart Smart Ice Cream: An example of an FDA - approved health claim. Nutritional facts panel content was based on FDA defi nition of health claim “ plant sterol/stanol esters and risk of coronary heart disease ” (21 CFR 101.83).

Silo C: Flavor

Again we resisted the temptation to explore the unusual fl avors, concentrating on the more conventional fl avors to which most individuals would respond “ knowingly, ” with at least some experience. Ice creams come in both single and mixed fl avors, and often have pictures associ- ated with them to make the fl avor more “ real. ” We used a picture with each fl avor name in order to make a more realistic package design for the test. Our fl avors were vanilla, strawberry, and chocolate, the three most popular single fl avors, and two of the many possible mixed fl avors, strawberry - banana and vanilla - chocolate chip. We see these fl avor labels and pictures in Figure 15.4 .

Looking at the Total Calorie Content

A recurrent issue in these types of studies is background context against which the decision is made. We wanted to separate out the two levels of calories (140 and 210 calories) so that we could treat the former as reduced fat/ calorie and the latter as the more traditional. This con- sideration led us to divide the ice cream evaluation into two studies, which differed in the nutritional facts panel (i.e., calories, total fat, cholesterol, and total carbohy- drate) (Figures 15.2 and 15.3 ).

Study 1 worked with an “ original ice cream of 140 calories per serving ” with nutrition facts panel of the ice cream types (Silo B) including organic, light, reduced calorie, and heart smart, changing appropriately for a 140 - calorie original.

Chapter 15 Understanding Nutritional Labeling: Case Study—Ice Cream 153

tangible evidence that there is something in this survey for them, even if it is only a chance at a sweepstakes.

Study Welcome Page

When the respondent clicked on the link to participate in the study, the respondent was guided to the study welcome page. Keep in mind that the welcome page does not “ tip the research hand. ” That is, from reading the text in Figure 15.5 , one does not know what to expect in terms of the politically correct or appropriate answer for any test package design. All the respondent knows is that there will be a 15 - minute interview. The respondent was told that they would evaluate a new set of ice cream package labels, each label on two scales (purchase inter- est from not interested to interested; description from very indulgent to very healthful).

What is the best way to write the invitation? If you look closely at Figure 15.5 , you will see a couple of key things. The fi rst is an engaging, respectful opening. In the invitation we give a legitimizing reason about why the study is being done: I - Novation ™ , an independent research company, has been asked to fi nd out what consumers like YOU think about different types of ice cream. Your opinions are very important and will help us design the next generation of ice cream products . The second is WIIFM (what ’ s in it for me).

We make the survey attractive by promising a possible reward: As our way of saying “ Thank You ” for your input, everyone who completes the survey before 9 PM Eastern time on Thursday, April 27, will be entered in a prize drawing featuring a fi rst prize of $100 and a second prize of $50 . Over the years, the nature of the reward has changed. But one thing has remained certain — it is important to give the respondent some

I-Novation, an independent research company, has been asked to find out what consumers like YOU think about different types of ice cream. Your opinions are very important and will help us design the next generation of ice cream products. Here’s your chance to tell us what you think! Simply click on the link below (if your email does not support hotlinks, cut and paste the link into your browser) and complete the short, easy-to-answer survey.

http://12.109.160.59/NJL734/NJL7344091 Front. asp

Depending on your connection speed, the survey should take about 15 minutes to complete.

As our way of saying “Thank You” for your input, everyone who completes the survey before 9 PM Eastern Time on Thursday, April 27th, will be entered in a prize drawing featuring a first prize of $100 and a second prize of $50.

Because this is a Web-based survey, you will be able to take it when and wherever is most convenient for you, as long as you have access to a Windows-based computer with an Internet connection. Unfortunately, the survey software will not support Mac or Web TV.

Please be assured that any information you provide will be held in the strictest confidence. You will not be contacted by an sales or other research organization as a result of your participation in this survey. Thanks in advance for your input, and good luck!

The I-Novation team.

We respect your privacy. If you feel that you received this message in error, or no longer wish to receive invitations to participate in market research surveys from our compay, please click on the “Unsubscribe” link. I-Novation, 1025 Westchester Avenue, Suite 444, White Plains, N.Y. 10604

i-Novation Inc.

The Respondent Experience

Let ’ s now move quickly into what the research discov- ered. Keep in mind that the respondent evaluated two scales (purchase interest and indulgent - healthful). Each respondent evaluated 35 combinations, about the right number when we keep in mind that each package gave us the opportunity to perform two ratings studies. On a practical note, it ’ s a lot easier to evaluate 100 combina- tions of pictures with one attribute than the 50 combina- tions of pictures with two attributes. Both are far easier than 33 combinations of pictures with three attributes, and so forth. This practical piece of information is impor- tant for Internet studies. It suggests that the variation from package to package is less onerous than the evalu- ation of the same package on multiple attributes.

One other factoid is important to keep in mind because it is the basis of a lot of potential analyses. That is, each respondent saw different combinations of package designs, rather than the same set of combinations. There is a reason for this. Many times the researcher creates a limited set of combinations to test and tests the SAME combinations among many respondents. The replicate or repeated evaluations ensure that we get a good, reliable measure of the mean and top - 3 box values. However, what happens when there is a hidden bias in the combina- tions (e.g., some combinations work unusually well, although we don ’ t know it)? We simply propagate that hidden bias across all of the respondents. So, by giving each person different combinations of the same elements, and with each person getting unique sets of pictures, we minimize this bias.

As always, we followed this set of 35 screens with a self - profi ling classifi cation. We ended knowing a lot about each respondent, with information ranging from standard demographics (age, gender), to attitudes to ice cream and health. Finally, the study was only modestly time consuming, taking about an average of 20 minutes to complete.

Looking at Data — The Heart of the Matter and What We Learn about Ice Cream

If you have been following the chapters in this book, you will fi nd that we deal with the data in a number of different ways. Although we use experimental design, the topics we deal with change, the questions change, and what we look at sometimes involves aspects other than the data alone. And so that will be what we do here.

The Actual Evaluations

Now, let ’ s get into the heart of the study. The respon- dents each evaluated 35 different combinations, rating the combination on both purchase intent and on a scale of indulgence — healthfulness. The rationale for the two scales is simple. One gets at overall interest but not why. The other on healthfulness gets at the nature of the “ type ” of product that is being communicated.

We have an example here of two things at play. On the one hand, the experimenter is varying the stimulus. That way, using regression analysis is very straightfor- ward to fi gure out just which of the different package features drive the response. We have seen that and will see that approach all through the book. On the other hand, we have the respondent doing two things, one after another, namely shifting point of view. The respondent fi rst chooses the appropriate scale point for evaluation, and then chooses the appropriate scale point on another scale for description.

Researchers do this type of multiple ratings quite often. If we were to work with only one picture, then we probably would ask many questions, not just one. After all, from one question and one package design you don ’ t get very much, just a single point, and certainly no pattern. With many questions and one package design you get a little more. You get different angles from which to view the single stimulus. You may fi nd out that the package is perceived as indulgent. Another package might be perceived as less indulgent.

Continuing this train of thought, you can see that with many package designs, preferably varied systemati- cally, and with a number of rating questions, you get a lot more. You get the patterns from the different products from the experimental design. You get the different points of view from the various scales. What one should guard against, however, is the desire to have it all, to ask one respondent many questions about many systemati- cally varied stimuli. After two or three ratings of the same package on different scales, a normal respondent stops paying attention. With two scales we are probably safe; with three, four, fi ve or more scales for that same stimulus, we are okay on the fi rst test stimulus in the interview because the respondent is still excited to par- ticipate. By the second or third test stimulus, it becomes quite boring to answer the same three - to - six rating scales, UNLESS the respondent is paid, and thus, highly motivated!

Chapter 15 Understanding Nutritional Labeling: Case Study—Ice Cream 155

At the individual level, we begin with 15 independent variables corresponding to the graphical 15 elements (recall 3 silos, 5 elements per silo), and 35 cases corresponding to the 35 test concepts or graphics com- binations. For each of our respondents, the ordinary least - squares regression analysis creates an individual model or equation showing the contribution of each ice cream element to the binary rating of not interested or interested (Fox, 1997 ; SYSTAT, 2004 ). We write the straightforward equation as the sum of the additive constant (k 0 ) and the part - worth combinations of the 15 elements, Element 1 to Element 15.

Binary Rating k k Element

k Element k Element = + ( ) + ( 0) 1 2 15 1 2 # #  ( ##15)

We can see the parameters of this model in Table 15.1 . We will spend the rest of the chapter discussing these results, with some more detailed analyses as well. Let ’ s move into the data now.

We ’ ll look at topics other than pure ice cream and ice cream labels. These experimental designs are rich with information about people, if we only know where to look. So without ado, let ’ s jump into the data and what we learn about ice cream, about interviews, and about the minds of people.

Who Logs in and How Many Complete?

If a topic is interesting to respondents, then we expect to see a high number of log - ins and a high completion rate. Study 1 had 278 total log - ins and 199 completes. This gave a completion rate of 72%. Study 2 had 301 total log - ins and 205 completes. This gave a completion rate of 68%, and so we can say that 70% of the respondents who start the study complete it. Ice cream is clearly a popular topic. For both studies 1 and 2, once a respon- dent agreed to participate in the topic of the study (ice cream), the content of the elements held interest for the majority of respondents. Let us put this into perspective with some other data. Andrea Maier and her colleagues reported completion rates of 50% (fruit smoothie), 46% (fl avored water), 55% (yogurt beverage), and 47% (fl a- vored tequila) for similar types of conjoint analysis studies (Maier, Moskowitz, and Ashman, 2008 ; Rabino et al., 2007 ).

In these studies typically more women than men par- ticipate. Females comprised 74% of respondents in the fi rst study (reduced calorie) and 81% of respondents in the second study (full calorie). Let ’ s put this into per- spective, however, because we ’ re going to see that the ratio of women to men in the study changes, depending upon the food. Look at Figure 15.6 to get a sense of the proportion of women to men in different types of studies. These were run in the It! studies (Beckley and Moskowitz, 2002 ).

What Do We Learn about Interest in the Ice Cream?

Our analysis followed the modeling approach discussed in previous chapters on modeling the results. We focused here on measures of interest, or membership in the group of respondents interested in the ice cream, based on what they saw. We used the binary transformation, which we discussed throughout this book. Thus, ratings of 7 – 9 for purchase get transformed to 100, and ratings of 1 – 6 for purchase get transformed to 0.

Food Chocolate Candy Cheese cake French Fries Tortilla Chips Cinnamon Rolls Taco Potato Chips Olives Gravy Pretzels IceCream Cola Cheese Peanut Butter Coffee Nuts Pizza BBQ Ribs Chicken Hamburger Steak % Female 86% 84% 81% 80% 80% 79% 76% 76% 76% 75% 74% 74% 73% 69% 69% 67% 67% 62% 62% 60% 56%

Figure 15.6 Percent female respondents for concept studies, using IdeaMap.net ® . Data courtesy of It! Ventures, and taken from the 2002 Crave It! ® database.

Table 15.1 Base size, additive constant, and utility values for percent top - 3 box purchase interest (1 – 6 → 0; 7 – 9 → 100), and for indulgent ( − numbers) versus healthful (+ numbers) for ice cream positioned as having 140 calories or 210 calories

Purchase Purchase Indulgent

versus Health Indulgent versus Health 140 Calories 210 Calories 140 Calories 210 Calories Base Size 199 205 Additive Constant