MARKETING RESEARCHWegmans Supermarket Greek Yogurt Analysis

Yunfei Chen UID:28891376

EXECUTIVE SUMMARY• Women make up 85% of respondents

→ Data should be reweighted to match the actually shopper panel.

• Two major segmentations

→ “Eating On Its Own Only" and “Eating On Its Own and Cooking”.

• Preference differences

→ “Eating On Its Own Only” consumes less FAGE; most of them have never tried.

• Serving size preferences not clear

→ No business decision recommended.

• Popular mix-ins: fruits, nuts/seeds/trail mix and cereal

→ Market for mix-ins exists.

METHODOLOGY• The Wegmans Survey was sent to a set of households selected for previously purchasing Greek Yogurt. The respondents were offered a chance to win a $100 gift. The survey contained questions about demographics, shopping behaviors as well as behavioral and attitudinal questions about Greek Yogurt.

• In Our Analysis, We…Dropped some values like Prefer not to say/NA to attain accuracy.

Used chi-square tests and t tests to test the data and see:

· if the sample gender proportion is representative of the shopper panel.

· whether segments are different in shares of yogurt purchases / frequencies of eating / preferences of CHOBANI or FAGE.

Used summary, charts and chi-square tests to better understand the market of yogurt mix-ins.

GENDER OF RESPONDENTS

TABLE1Sample

ProportionDesired

Proportion

Male 15% 21%

Female 85% 79%

• Women make up 85% of respondents. (Table1)

• There is evidence that the sample is not representative in terms of gender proportion.

(chi-square test; p-value: 0.0002489)

• The sample should be reweighted according to Table2.TABLE2 Female Male

Weight 0.93 1.39

SEGMENTS

1%

64%

35%

Only For Cook-ingOnly For EatingFor Both

• The two segments “Only For Eating” and “For Both” make up 99% percent of the sample.

• The two segments are not significantly different in:

FREQUENCIES OF EATING

(chi-square test; p-value: 0.3695)

PREFERENCES OF CHOBANI

(chi-square test; p-value: 0.7544)

SEGMENTS • The two segments are different in terms of their:

PREFERENCES OF FAGE (chi-sq test; p-value: 4.47e-08)

SHARES OF YOGURT PURCHASES (t test; p-value: 0.025)

• People who use Greek Yogurt “For Only Eating”:

CONSUME LESS GREEK YOGURT

PREFER CHOBANI TO FAGE

MORE THAN 50% OF THEM HAVE NEVER TRIED FAGE

• Based on the data, FAGE is not very popular as a snack food. Wegmans can move FAGE closer to vegetables and meat, and focus the promotions on people who both cook and eat.

• “Only for eating” is a big segment in the market, but they consume less. Wegmans can also consider stimulate their needs for cooking.

0

100

200

Never tried Ocassionaly Regularly Tried once

Frequency of Eating FAGE

coun

t

usage

both

only eating

MEAN OF DATA ONLY FOR EATING BOTH EATING AND COOKING

WHAT PERCENTAGE IS GREEK YOGURT

88.2 91.4

SERVING APPROACH

less than once a w

eek

less than once every

two days

more than once every

two days

more than once a day

010203040

• Divide respondents into 4 groups

• Perceive no difference in group 1 and group 2 (t test; p-value: 0.574)

• Perceive a difference between group 2 and group 3 (t test; p-value: 0.0002)

• Perceive a difference between group 2 and group 4 (t test; p-value:0.001434)

• There is a trend in the sample data that proves the hypothesis.

• People are very diverse in their choices of serving sizes.

• The trend is not clear and I suggest no business decision is needed.

0

10

20

30

40

50

0 25 50 75 100percentage(0 excluded)

coun

t less than once a week

less than once every two days

more than once a day

more than once every two days

MIX-INS

• Lots of people frequently add mix-ins.

• No obvious relationship between “mix-ins” and “how often do you eat yogurt”.

→ Market for mix-ins exists.

• People more often add fruits, nuts/seeds/trail mix and cereal to their yogurt.

→ Create a mix-in facing containing fruits, nuts/seeds/trail mix and cereal.

0

25

50

75

100

0 25 50 75 100Percentage of time add extra ingredients to Greek Yogurt %

coun

t

Once a month or less

2-3 times per month

Once a week

2-3 times a week

3-5 times a week

Once a day

More than once a day

APPENDIX

Part 1 Gender

• Exclude people who have answered “prefer not to say”

• Create a table of the gender and use chi-square test to compare it with the desired proportion

• Divide the desired the proportion with the sample proportion to get the weight. Output:

1 2

1.3851515 0.9311733

Part 2 Segments• Used the prop.table function to get data for a pie chart.

Output:

1 2 3

0.01076716 0.63795424 0.35127860

• Used t test to test the answer of Q2_1.

• Used chi-square test to test the answers of Q5,Q7_2,Q7_1.

• Dropped the NAs and calculated the median of surveyDB$Q7_2[surveyDB$Q4==2] surveyDB$Q7_2[surveyDB$Q4==3]

Output: (left column refers to the answers in Q4)

• Created a subset to contain the values of Q4 and Q7_2, cleaned the data and drew a plot.

Part 3 Serving Approach

• Divided the respondents into 4 groups: "less than once a week“ / "less than once every two days“ / "more than once every two days“ / "more than once a day“.

• Used t tests to compare the means between groups.

(1st picture: "less than once every two days“ VS "more than once a day“ ; 2nd picture: "less than once every two days“ vs "more than once every two days“ ; 3rd picture: "less than once a week“ vs "less than once every two days“.

• Dropped the NAs and calculated the mean of each group and drew a chart.

Part 4 Mix-Ins

• Used ggplot2 to draw the histogram to directly see the relationship between “mix-ins” and “how often do you eat yogurt”. qplot(surveyDB$Q10,fill=surveyDB$Q5)+xlab('Percentage of time add extra ingredients to Greek Yogurt %')

• Created a subset (name: question4) with two columns. The first column contains the values of Question “how often do you add this mix-in” (values like rarely, sometimes). The second the column contains the correspondent mix-in type (values like nuts, fruits)

• Cleaned the data, dropped the NAs and draw the line chart. ggplot(question4,aes(x=factor(HowOften)))+geom_freqpoly(aes(group=mixins,colour=mixins),size=1)+xlab('never/rarely/sometimes/most times/always')+ggtitle("What type of your own inclusions do you add?")

• Changed the values in the first column into numbers and calculate the median.