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Conjoint Analysis for Starbucks

Maggie ThompsonMKT 315

3 February 2015

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Since Starbucks was established, it has become very well known and profitable. However, in comparison with its competitors, Starbucks’ market share is low1. So, Chi City Consulting offered its services to better examine how Starbucks can be more competitive within the coffee retail industry. We did this by determining the correct features necessary for Starbucks to relaunch its company. We assessed our client as well as its competitors using conjoint analysis2. After using this method, it is clear that Starbucks needs to fix some features within its coffee shops in order to create a better ambiance for its customers; this will make them happier when going to Starbucks3. When finding information about Starbucks and how to improve its business, we facilitated focus groups, received input from management, and gathered information about its competitors, Peets, Dunkin Donuts, and Pret A Manager. In order to analyze all of the data we received, we used Orthogonal Experimental Design, which provided a coding system to eventually be able to analyze the data (See Appendix, Figures A-D-1).

After looking at the conjoint bar graph, it is clear that there are relevant features and levels4 that make up a core coffee shop and produce more utility5 to consumers. Using these features, as a basis of what Starbucks should utilize, can help move Starbucks in a more successful direction.

The conjoint bar graph displays that the features that produce the most utility are coffee shops that are one mile away, have free Wi-Fi, tables, live music, sell snacks, coffee tea and juice, and to be opened for 24 hours (See Appendix, Figures E & E-1). Although it would be prime to have Starbucks achieve each of these seven features for their coffee shops, it is not realistic in order to still make a substantial profit.

Our goal is to help our client make more money than it is now. However, if Starbucks were to take all of these features into consideration, it is possible that it would do more harm than good.

As we make suggestions, it is necessary to assume that every product or service is a bundle of attributes, a change in a level implies a completely different product, and lastly, a change in a single level changes consumer preference. Below, are the listed recommendations we suggest for our client to consider:

1. After evaluating what Starbucks offers to its customers according to the seven most important features, it currently is one mile away, has free Wi-Fi, has a lounge, plays background music, sells sandwiches and seasonal and specialty drinks, and is opened during business hours. After examining the conjoint analysis bar graph, the Total Product Utility for the conjoint analysis equaled to 2.3296. Starbucks is advised not to choose all of the features that create this TPU of 2.329. However, they should still decide on seven

1 Market share is the percentage a company has in a specific market, such as in the coffee industry.2 A method that assists to better understand the structure of consumer value. It is based off of the utility value that consumers assign to various features and levels of a product or service, in this case coffee shops.3 The procedure to conduct a proper conjoint analysis study for Starbucks is first to define the core product and identify relevant features and levels, then decide the nature of the stimuli and expected consumer judgment format, choose and list relevant subset product combinations for coffee shops. The next step is to obtain preferences data by developing and fielding a large sample survey, and the last step is to analyze the data and interpret the output.4 Seven of the most relevant features and three levels were chosen to conduct the analysis. The features can be physical, performance, psychological, and aesthetic.5 The amount of happiness features can give consumers. 6 TPU helps determine the optimal product. It is found by adding all of the best features together (one mile away, free Wi-Fi, tables, live music, snacks, coffee tea and juice, and to be opened for 24 hours).

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features that have a TPU close to 2.329 even if there are different features chosen. This will cause a tradeoff between features7. The tradeoff can still help maximize profits because it is fulfilling maximum happiness for the consumers and therefore Starbucks will not lose any potential revenue (See Appendix, Figure F).

2. We recommend that Starbucks choose to be one mile away, provide free Wi-Fi, have tables and live music, sell snacks, coffee, tea, and juice, and be opened during business hours. If Starbucks were to change their features to the ones that produce the most utility, then its market share will increase and be more competitive in the coffee industry (See Appendix, Figures G&H).

3. The individual feature8 range displayed that location is the most important feature (See Appendix, Figure I). Since consumers have the belief that a good location for a coffee shop is key to making them happy, then we suggest that Starbucks ensure that there is a store a mile away. Management should also thoughtfully consider what three other features are considered to make consumers the happiest and these are layout, Wi-Fi setup, and music. According to consumers, these four features, including location, makeup 74% of what consumers find the most important in coffee shops (See Appendix, Figure J).

4. It is very important that Starbucks realize the sweet spots on the graph in order to determine what customers find the most pleasing9. It is decided, that consumers enjoy only being offered snacks at coffee shops. So, since this produces the most utility for customers and is a way Starbucks can reduce costs, we recommend that Starbucks should sell snacks as the only type of food (See Appendix, Figure K).

5. Any final features that our client decides should be either changed or kept, needs to be greater than the intercept10 on the conjoint bar graph, and therefore have a Total Product Utility that is greater than 1.000. With the recommendations we have made, it is ensured that customers will be happy since the utilities of all of the features are greater than 1.000 (See Appendix, Figure L).

7 If an optimal feature is not possible to use and may cause an enterprise to lose money, then a tradeoff may be necessary. This exchanges some features for the other but will still give back the utility to the customers that was previously lost.8 Individual feature range is found by subtracting the lowest utility value from the highest utility value for that same specific attribute. 9 Sweet Spots are determined through two ways; the first is when consumers are happy paying more, which helps companies, gain more money. The second is when consumers are happy with less, which saves the companies money. 10 The intercept suggests the market entry barrier as perceived by the target market. Any product’s TPU must be greater than the intercept value. The intercept’s value is the minimum acceptable value for a product to be part of the target market’s consideration set.

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Appendix:

Figure A:

This figure is the orthogonal array created by statisticians. It is a combination of 0’s and 1’s that help convert the code sheet into actual orthogonal profiles. The Orthogonal Experimental Design helps decide how many profiles and which profiles should be shown to consumers.

Figure B:

This is the code sheet that we created by using the orthogonal design shown in figure 1. 14 variables were needed which is represented by an X and this code sheet has 14 X’s. (3 levels – 1= 2) and then (2x7 features= 14)

Each X represents one level of a conjoint feature Each X can take one of two values, either 0 or 1

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Value of 0 implies that the particular level is absent from an orthogonal profile

Value of 1 implies that the particular level is present in the orthogonal profile

There are 18 profiles that are shown to consumers

Figure C:

We had a large sample of consumers rate the 18 different profiles from 1-7 (1= would definitely never consider and 7= would definitely consider)

Figure D:

This shows the multiple regression that is used to analyze the data and interpret the output which helps create a conjoint analysis bar graph. The adjusted R Square shows how much of the variance in the data is being explained and it needs to be between 0-1 (the higher the better). Significance F needs to be less than zero, and in this case, it is. The features and coefficients are used to create the bar graph after the coefficients are rescaled.

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Figure D-1:

The numbers to the right of the coefficients are the rescaled numbers that are used to make the conjoint analysis bar graph.

Figure E:

This conjoint analysis bar graph displays what features have the most and least importance to customers when it comes to coffee shops.

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Figure E-1:

It is important to notice that the location of a coffee shop is linear. As the location increases in distance, the units of happiness that consumers have towards a coffee shop decreases roughly around the same amount. Therefore, consumers rationally have decided that the farther the distance a coffee shop is, the less desirable it is to them.

Figure F:

Figure F adds up all of the utilities together from the best features, which gives a Total Product Utility of 2.329. Starbucks must decide what features it should change and/or continue to have so that they can maximize their customers’ utility.

Starbucks currently is 1 mile away, has free Wi-Fi, a lounge, plays background music, sells sandwiches, seasonal and specialty drinks, and is opened during business hours.

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It is feasible for Starbucks to gain a TPU of roughly 2.329 if it remains to be one mile away, have free Wi-Fi, and continue to be open during business hours. However, they should change the lounge area to tables, offer live music, and sell coffee, tea, juice, and snacks. The only exception is that Starbucks should not remain open for 24 hours. This can possibly hurt Starbucks because they will need to pay for their employees to be working and there may be a lack of customers who come during the middle of the night to order food or drinks.

Starbucks needs to make a tradeoff between being open 24 hours (utility of .241) with another feature with a utility close to .241. Since live music is such an important feature, Starbucks can offer live music (utility of .241) that can be held during specific hours of the day. This way, Starbucks can keep the customers happy but do not need to overspend on live performers.

Figure F-1:

This shows the worst possible TPU. This can give Starbucks a better idea of what not to do when planning the features they should add or remove.

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Figure G:

This picture displays Starbucks’ current market share along with its three other competitors. As shown, Starbucks has the smallest market share in the coffee industry. The market share is determined through this formula:

Figure H:

This picture displays Starbucks along with Dunkin Donuts, Peets and Pret A Managers’ market share if Starbucks were to make modifications to its coffee shops. The market share for Starbucks will increase significantly while its competitors’ market share will decrease.

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Figure I:

This figure shows the individual feature range. This is found from the difference between the highest utility value and the lowest utility value for a specific attribute. These numbers give each feature a value of how important they are to consumers.

Figure J:

0.12

0.188571428571429

0.1428571428571430.2914285714285

71

0.0571428571428571

0.0914285714285715

0.108571428571429

Feature Importance

_x0005_Music

Wifi Setup

_x0006_Layout

_x0008_Location

_x0005_Hours

_x000d_Drink Variety

_x000c_Food Variety

This pie chart displays the overall feature importance, which is found by dividing the individual feature range by the super range.

The super range is found by adding all of the individual ranges together.

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Location, Layout, Wi-Fi, and Music make up more than half of the pie chart which shows how these are the four most important features to customers.

Figure K:

Food options and hours of operation are both sweet spots that Starbucks should notice. As for the food options, consumers are happy with paying less and in this case, they are

just as happy to eat the snacks Starbucks sells rather than sandwiches or meals. This can be a great opportunity for Starbucks due to the fact that by only providing snacks within their cafes, they will save costs but still be able to make their customers happy.

Another sweet spot shown on the graph is hours of operation. Consumers would prefer to have Starbucks only be opened during the morning or for 24 hours. So, this sweet spot shows that consumers would rather pay more for the shop to be opened for 24 hours or they would be happy with it opened only in the mornings for fewer hours, which is cheaper for Starbucks.

However, even though hours of operation is a sweet spot that Starbucks could take advantage of, it realistically would not help the company. Since customers prefer to have live music, it would be very expensive for Starbucks to have live performers play for 24 hours while the café is open. Although, if Starbucks is open

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only in the mornings, most customers are purchasing food and drinks during that time before work. So, they would not have any leisure time to listen to live performers anyway. This explains how Starbucks would benefit the most by being open during regular business hours but then provide live music.

Figure L:

This bar graph displays the TPU for Starbucks’ current café shops, the optimal café shop, and then the minimum acceptable café shop (the intercept). In this case, the minimum accepted café shop has to have a utility of at least 1.000. If Starbucks decides to maximize its utility, then it will have a much greater TPU than the intercept value of 1.000.

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