What Should My Package Say?

of chronic diseases like stroke and diabetes ” will push an additional 6% of respondents from voting “ not interested ” to voting “ interested. ”

5. We see a few more elements that generate modest positive values. They mention crunchy texture, low calories, and weight loss. But none of these elements by itself comes across as “ Wow, this is what we need to capture for our product! ”

6. For the most part, the elements hover around 0, so they neither drive acceptance nor drive rejection. We already know that values ranging from 0 – 5 add little value to interest. This is the landscape where the majority of the data falls. There isn ’ t much in the data that will add to purchase interest among total sample.

7. Surprisingly, cereal from the local specialty or gourmet store is a turnoff ( − 8).

8. Trusted brands don ’ t bring much to the story. Surprising, yes! But this answers one of our ongoing questions: What drives consumer behavior when pur- chasing cereal?

9. Where are the healthy promises an organic cereal will deliver, or the innovative fl avors for the sophisticated taste buds? Weren ’ t any of the consumers interested in these areas?

Looking at the Frequent Cereal Eater

What ’ s happening if we look at the data based on the amount of cereal a person says he eats? We asked respon- dents to tell us how frequently they eat cereal. Do they eat it everyday as part of their daily routine, or occasion- ally, more like when the mood hits them? Here an inter- esting story appears among heavy cereal consumers (once a day or more often) versus moderate consumption consumers (several times a week). We didn ’ t put in all of the frequency subgroups in Table 10.2 , which shows the results.

Our “ heavy consumption ” consumers who ate cereal frequently had a constant of 43, similar to the total panel. This group was motivated by a cereal made with whole wheat goodness and fi ber with traditional taste and fl avors that were plain and simple with cinnamon and brown sugar. They wanted a crunchy texture of thick fl akes, big clusters of nuts, and lower in calories. Enhancing the taste and texture profi les with imported plump fruits also attracted them. This group wants a traditional taste and fl avor with the rewards of health benefi ts. They are similar to those people we mentioned Much of the story appears in the data tables. Let ’ s

return to Table 10.1 , which shows the results from the total panel of 446 respondents. Parenthetically, these types of studies often provide very strong data and are stable by the time we get to 50 – 75 respondents. The base size of 446 is somewhat “ overkill ” but will allow us to look at subgroups or different sets of people in the population.

Now we will go through the results in Table 10.1 , which come from the total panel. Each row has meaning.

Let ’ s look fi rst at the additive constant. The constant is 41. That means that 41% of the respondents are inter- ested in cereal if there is no element present. Clearly all concepts had elements, so this number “ 41 ” is an esti- mated parameter. Still, it ’ s an important number to keep in mind. It ’ s a baseline value. You can compare this number across different groups of respondents in the set of 446 individuals, or across studies. Just for comparison purposes, credit cards have a baseline value or additive constant of only about 15 – 20, meaning that only 1 person in about 5 or 6 is interested in credit cards to begin with, whereas for cereal we already start with 2 in 5.

The story starts to get more interesting when we delve into the elements, although we wouldn ’ t know that from the total panel. We ’ ll see the interesting fi ndings when we get to segments. Right now, however, let ’ s just look at what the average data from our 446 respondents tell us:

1. For this table we show the six different silos sepa- rately. Within each silo we sort the elements from best performing to worst performing, based on the impact or utility value.

2. There are some rules of thumb for interpreting the impacts of the different elements. First, the number is the proportion of respondents who would change their rating from not buy (1 – 6) to buy (7 – 9).

3. Second, there are some norms:

a. Impact > 15 = Extraordinarily strong performer, keep this element

b. Impact 10 – 15 = Strong performer, keep this element

c. Impact 5 – 10 = Signifi cant performer and relevant d. Impact 0 – 5 = Marginal performer

e. Impact − 5 – 0 = Poor performer, detracts, eliminate unless absolutely necessary

f. Impact less than − 5 = Causes damage, avoid 4. Our top scoring element, “ Made with whole grain, a

the underlying reasons why the four elements that strongly appeal to the frequent cereal eater do so. But hold on — there ’ s more to come in the next section!

Different Mind - Sets Lead to Stronger Messages!

Since we don ’ t see anything of signifi cant interest among the total sample, and only slight effects when we look at eating or purchase frequency, we should look somewhere else. Fortunately, researchers have recog- nized the fact that people profoundly differ from each other in what they like, but these differences may not manifest themselves in how people describe their behav- ior. These different groups are mind - set segments. We have seen the power of such segmentation again and again in these chapters, and we will continue to do so. These segments are “ real, ” and profoundly different from each other.

We grouped our 446 consumer respondents into three “ mind - set segments ” , according to what elements “ drive ” their stated purchase intents. The segmentation is straightforward. We used the statistical method of clus- tering, a set of well - established approaches, to group in the beginning of the chapter — those shoppers who

walk down the cereal aisle and know exactly where they ’ re going — to their old - fashioned favorite with no bells and whistles, just trusted goodness with a familiar taste.

We now know what to put on a package to attract them if they do the shopping for cereal! Let ’ s fi nd out more about shoppers to see whether we can continue with our discovery. Let ’ s also look at those who buy the cereal. A frequent buyer of cereal may buy it for someone else in the household. These may or may not be the ones who actually eat the cereal.

This time we divide our 446 respondents into two groups, those who are frequent purchasers and those who are infrequent purchasers. We use the classifi cation data at the end of the interview to fi nd out where a person fi ts. The bottom line here is that no element really pops. The only element to do anything is the whole grain, probably because we ’ ve added in the risk reduction for stroke and diabetes.

If we were to summarize, we would say that consump- tion frequency probably affects the impact of the concept elements, but buying pattern does not. The pattern is not clear why winning elements for frequent eaters really win at all. We really don ’ t know why. It ’ s hard to uncover

Table 10.2 Best performing elements based on how much cereal a person eats or purchases. We show only the extremes of the frequency subgroups, not all the frequency subgroups.

Total Sample Frequent Cereal Eaters Frequent Purchases of Cold Cereal Infrequent Purchases of Cold Cereal BASE SIZE: 446 100 240 84 CONSTANT: 41 43 46 22 Heavy Eaters

C2 Made with whole grain, a good source of fi ber, important in reducing your risk of chronic diseases like stroke and diabetes

6 13 6 5

B1 Plain and simple, made with brown sugar and cinnamon for a traditional taste

3 9 2 1

B4 Made with imported dried fruits that plump up nice and juicy when adding milk

2 8 3 − 1

F5 From your local supermarket 2 7 4 1

Frequent Purchasers

C2 Made with whole grain, a good source of fi ber, important in reducing your risk of chronic diseases like stroke and diabetes

6 13 6 5

Infrequent Purchasers

C2 Made with whole grain, a good source of fi ber, important in reducing your risk of chronic diseases like stroke and diabetes

Chapter 10 What Should My Package Say? 103

together individuals with similar patterns of what they liked. People with similar patterns (i.e., similar utility values for their elements) fall into the same cluster or segment.

You can see these results in Table 10.3 . Here we simply sort the elements from best to worst for each segment and show the results for the three segments. Let ’ s look at the segments one by one. We ’ ll only look at the winning elements for each segment. Otherwise the analysis will become unduly complicated. If you look at Table 10.3 you will see how each of the “ winning elements ” scores in both the segment it appeals to and how well it scores among the other two segments. Look closely and you will see that a winning element in one segment may be a losing element in another segment. This countervail- ing force of one segment versus another may be one reason why the elements don ’ t score very well among the total panel. The segments neutralize each other. The same neutralization story occurs again and again, in product category after product category. And so it occurs here, as well.

Now let ’ s delve into the data more deeply. The best way to follow along is by looking at the best scoring elements for each segment that we show in Table 10.3 . Once you understand that, step back and try to develop a “ story ” about each segment, using as cues the elements to which they strongly respond.

Segment 1: Conventionalists. These consumers look for the old tried and true: simple combinations of apples and cinnamon, plain and simple, made with brown sugar and cinnamon or a traditional taste. To keep them happy, make it simple and keep it traditional. There is only one element that appeals both to Conventionalists and to Indulgents . This element is made with imported dried fruits that plump up nice

and juicy when adding milk . It could well be that the

same element conveys two different messages, depending on the segment. To Conventionalists the hot button is “ plump up nicely when adding milk. ” To the Indulgents the hot button could be “ imported dried fruits. ” Of course this is only a hypothesis, but it could be tested easily by dividing the element into both halves, and testing each half again, but as a separate element.

Segment 2: Reassurance. Our largest segment looking for a brand they know and trust, a healthy cereal that ’ s good for them, one that they can rely on to deliver whole grain goodness, fi ber, and a crunchy texture.

Segment 3: Indulgents. Here is strong opportunity for a product developer looking to carve a niche appeal in the industry. Indulgents may be a group of savvy consumers with sophisticated palates. They ’ re looking for innovative fl avors such as Kahlua, Hazelnut, Amaretto, Vanilla Bean, and Milk Chocolate.

Table 10.3 Winning elements from the three mind - set segments evaluating cereal

Total S1 S2 S3

Base Size 446 80 287 79

Additive Constant 41 43 40 43

Segment S1: Conventionalists

Enjoy the simple combinations of apples and cinnamon 2 15 − 2 2 Plain and simple, made with brown sugar and cinnamon for a traditional taste 3 13 − 1 6 Made with imported dried fruits that plump up nice and juicy when adding milk 2 12 − 3 14 The old - time favorite Honey Nut 0 10 − 3 0 Segment S2: Reassurance

The crunchy texture of thick fl akes and big clusters of nuts 3 − 1 5 3 Made with whole grain, a good source of fi ber, important in reducing your risk

of chronic diseases like stroke and diabetes

6 4 4 16

Only 100 calories of wholesome goodness per serving 3 3 4 1 Segment S3: Indulgents

Now in Vanilla Bean and Milk Chocolate, an indulgent cereal 0 7 − 9 23 For the sophisticated taste buds, fl avored with Hazelnut, Amaretto and Kahlua − 4 14 − 15 16

troids or center points of different clusters is “ large. ” Distance itself can be measured in different ways. Depending on the measure of “ distance, ” we will create different looking clusters. However, for the most part the results will be reasonably similar across segments.

Wrapping It Up — Now What?

So, what have we learned from this exercise and how can a product developer use these fi ndings to create a package design for a new cereal?

1. The key fi ndings of this research lie in the impacts of element utilities (i.e., the power of messages to moti- vate interest or detract from interest). You need to know both the positive performing and negative per- forming elements when you develop visuals and mes- saging for packages.

2. No one silo of elements piqued respondent interest in and of itself. The story wasn ’ t that cut and dried. 3. The heart of the learning emerged from the mind - set

segmentation. Here the product developer has oppor- tunity for diversity in both product offerings and visual communications.

4. The Conventionalists segment is motivated by images that convey simple combinations of apples and cin- namon, plain and simple, made with brown sugar and cinnamon or a traditional taste. A package that when you look at it reminds you of a taste of old - fashioned goodness fi lled with childhood memories. Don ’ t miss the opportunity to add extra value to the customer experience with these nostalgic images. This group is not motivated by health benefi ts or brand names. 5. Or you can target the Reassurance segment with your

trusted brand name and messages which reassure them of health and that this is a cereal that ’ s “ good for them. ” This is a very strong segment of people that can ’ t be overlooked and don ’ t need much to keep them as customers.

6. And, last but not least, grab that very unique oppor- tunity that exists within the Indulgents group. The more exotic the images, plump imported fruits in a new and exciting fl avored cereal, entice these con- sumers. They are not turned on by brands but by the excitement of something new and innovative. Make the package splashy and sassy. Entice this group with innovative designs and fl avors of cereals that awaken the taste buds with a new cereal experience.

You can entice them with imported dried fruits in a cereal, which will also deliver whole grain goodness and fi ber. This group wants a new twist to an old staple. They ’ re looking for something new in the cereal aisle.

How Many Segments Are Best?

Throughout this book we will be referring to segments and using segmentation as a way to better understand the business opportunities. Sometimes we will present two segments, sometimes three, sometimes four, rarely if ever fi ve. The operative question here is “ How many segments and why? ”

First, keep in mind that segmentation is not an exact science. You can ’ t just approach the data and expect it to give up the segments in an absolute sense, just like you cannot divide a group of people and say that the division is the “ absolute best ” way of partitioning the group. The reality is that segmentation is subjective. Segmentation depends on the criteria or variables on which you segment, the statistical methods for dividing the respondents, and of course on the degree to which you want to have many segments versus a few segments.

Each of these issues deserves a short comment here, as preparation for our upcoming chapters.

1. Segmentation depends on the variables you select and the criteria you use to segment. We will do three types of segmentation in this book. The fi rst way will be dividing people by what we know about them. Thus, we might divide the people on the basis of gender (male versus female), by income, education, etc. The second segmentation will be on the basis of what they tell us about themselves, their attitudes, their body state, etc. We just saw a few examples of this when we divided the people by their self - stated frequency of buying cereal or consuming cereal. The third way will be on the basis of the response to concept or package design elements (so - called mind - set segmen- tation). We just saw an example of this for our mind - set segmentation.

2. Segmentation depends on the statistical methods you choose. This is important. We could divide the respon- dents using a procedure that puts people into different clusters so that the “ distance ” between people in a cluster is “ small, ” and the distance between the cen-

Chapter 10 What Should My Package Say? 105

Koh - Banerjee , P. , Franz , M. , Sampson , L. , Liu , S. , Jacobs , D.R. , Spiegelman , D. , Willett , W. , and Rimm , E. ( 2004 ) Changes in whole - grain, bran, and cereal fi ber consumption in relation to 8 - y weight gain among men . American Journal of Clinical Nutrition 80 , 1237 – 1245 .

Liu , S. ( 2003 ) Whole - grain foods, dietary fi ber, and type 2 diabetes: searching for a kernel of truth . American Journal of Clinical Nutrition 77 , 527 – 529 .

Slavin , J.L. , Lavin , R.D. , Jacobs , D. , Marquart , L. , and Wiemer , K. ( 2001 ) The role of whole grains in disease prevention . Journal of the American Dietetic Association , 101 , 780 – 785 .

SYSTAT . ( 2004 ) SYSTAT for Windows, version 11. SYSTAT Software Inc., Chicago, IL.

Technical note: All segmentation was done using SYSTAT. Triticale (Source: AskDrSears.com ).

W.K. Kellogg (Source: www.inventors.about.com ).

References

Burkitt , D. and Trowell , H. ( 1975 ) Refi ned Carbohydrate Foods and Disease: Some Implications of Dietary Fibre. London , Academic Press , London, UK .

Cereal grains (Source: www.Wikipedia.com ).

Flight , I. and Clifton , P. ( 2006 ) Cereal grains and legumes in the pre- vention of coronary heart disease and stroke: a review of the litera- ture . European Journal of Clinical Nutrition 60 , 1145 – 1159 . Harris , D.R. ( 1996 ) The Origins and Spread of Agriculture and

Pastoralism in Eurasia: Crops, Fields, Flocks and Herds . Routledge Taylor and Francis Group , London and New York .

Jacobs , D.R. , Jr. , Marquart , L. , Slavin , J. , and Kushi , L.H. ( 1998 ) Whole - grain intake and cancer: an expanded review and meta - analysis . Nutrition & Cancer 30 , 85 – 96 .

Kochar , J. , Djouss é , L. and Gaziano , J.M. ( 2007 ) Breakfast cereals and risk of type 2 diabetes in the physicians ’ health study I . Obesity 15 , 3039 – 3044 .

“ This humble food comes in a variety of shapes, fl avors, and with coatings that would have amazed the humble monk who invented the pretzel sometime between the fi fth and seventh centuries. Idling with leftover strips of dough, the monk - baker supposedly twisted and turned them until they resembled a person ’ s arms crossed in prayer, traditional posture for prayer in those days. The brother monks approved the tidbits, and began using them as rewards for the children under their tutelage.

Despite their royal status, pretzels were a con- venient way to hand food to the poor, and became a typical alms for the hungry. Apparently the home- less did not line up for soup or a sandwich, but for their daily pretzel. And those who gave the pretzels away were considered particularly blessed. Indeed, pretzels became such a sacred sign that they were often packed into coffi ns of the dead, no doubt replacing the jewels that were buried with the rich. ” (Pretzel history)

We see here quite an amazing evolution, from a background steeped in religion and goodness to an all - time favorite snack found on the shelves in supermar- kets, school cafeterias, and vending machines. And so we chose this interesting popular snack food. Let ’ s