PortfolioAmanda Brehm, MBA

ContentsSAMPLES OF THE FOLLOWING:

Boar’s Head Inn

UberEats

Blue Apron

Johns Hopkins University

DressSwap

Tesla

Marvel Enterprises

WM Wrigley Jr. Company

Boar’s Head InnMarketing Analysis

Challenges

●Aging customer base

●Difficulties attracting younger

customers

●Disjointed communication within the

resort

Opportunities

●Gain younger customers

●Improve communication between the

different services of the resort

CompetitiveLandscape

Target Audiences

Millennials18-31 (1998-1985) •Gender: M 50% F 50% •HH Income: $50-$100K 49%+ •$100-$200k 29% •Marital Status: 57% •Children: 54% •Travel Habits:96% travel in US, •4.2 trips/year •69% vacation >1000 mi from home •Average Vacation Spend $888 •Key Factors: Family Vacations With Kids, Vacation With Friends

Gen X32-51 (1965-1984) •Gender: M 50% F 50% •37% of Affluents: median $145k, mean $227•Marital Status: 66% •Children: 57% •4- 6 trips/year •Spends the most per day on luxury travel $8,458 per year at a daily rate of $627 •Key Factors: Boar’s Head highest revenue generators, exploration hungry, food & cuisine driven, cultural interests

Boomers52-70 (1946-1964) •Gender: M 49% F 51% •33% of Affluents: median $145k, mean $227, 5% are seniors•“Sandwich Generation: 47% supporting parent 65+ and child •4- 5 trips/year •Seniors/Boomers spend the most per day on luxury at a daily rate $471/$522•Key Factors: Multi-Gen-family, vacations exploration, nature

Target Audiences

All-In-One Enthusiasts•Gender: M 64% F 36% •Reside: 55% in NE & South USA•Children: 77%•Average Vacation Spend: 48% > $500•Key Factors: 49% Vacation with kids, 30% Visit a mountain resort, 62% opportunities to learn something new, Iconic landmark, Engaging with nature

Sophisticated Explorers•Gender: M 26% F 74% •Reside: 67% in NE & South USA•Children: 27%•Marital Status: 57% •Children: 54% •Average Vacation Spend: 78% > $500; 22% > $1k-3k+•Key Factors: 38% Vacation with friends, 25% Quiet countryside holiday; More likely to visit cultural attractions

Active Adventurers•Gender: M 44% F 51% •Reside: 49% in NE & South USA•Children: 39%•Average Vacation Spend: 62% > $500•Key Factors: 44% Vacation with friends. More likely to participate in outdoor sports or health & fitness activities

UberEatsMarket Research Study

Is UberEats (Washington DC market) a sustainable service among the

rising competition?

•How do preferences differ between demographics (age, gender, salary, occupation, and spending habits)?

•What do customers value, where are they located, and what is their purchase sensitivity?

•Do customers want the best quality food (from gourmet chefs) to be delivered or would they rather have

this experience at the brick-and-mortar restaurant?

•Do customers value the fastest delivery service or the cheapest delivery service?

•Do customers want more of a range of options on the menu and/or a range of restaurants available?

•Do customers want to order delivery food during lunch hours at work or dinner time at home?

•Will customers order food for themselves or as a group with colleagues or family members?

Information That We Need to Know

For our experiment, we will compare factors with our competitors, Postmates and GrubHub. Thus, our null hypothesis is that for overall satisfaction is H0: U=P=G and our alternative hypothesis is U≠P≠G or U≠P=G or U=P≠G

Spending Habits H0: U=P=G and our alternative hypothesis is U≠P≠G or U≠P=G or U=P≠GAge H0: U=P=G and our alternative hypothesis is U≠P≠G or U≠P=G or U=P≠GGender H0: U=P=G and our alternative hypothesis is U≠P≠G or U≠P=G or U=P≠GOccupation H0: U=P=G and our alternative hypothesis is U≠P≠G or U≠P=G or U=P≠GSalary H0: U=P=G and our alternative hypothesis is U≠P≠G or U≠P=G or U=P≠G

In addition, we will look into the importance factors (User interface, Food price, Food Selection, Delivery price, Delivery Time estimate, and Overall satisfaction) among our survey subjects.

H0:U=F=FS=D=DT=O and our alternative hypotheses is at least one factor varies.

Hypothesis

By comparing the UberEats service with GrubHub and Postmates, Uber Eats received the worst satisfaction among the food selection and user. When we compared the user expectations to their actual experience using the apps we found that user interface is the key reason why people dislike UberEats compared to GrubHub and Postmates.

In fact, our respondents are willing to pay more for this service, if they had a pleasant app/online experience.

Results

Age, gender, and salary did not seem to have statistical significance on user preferences given our smaller sample size.

Based on our findings, our recommendation would be to improve the user interface, which would overall increase the acceptability of the service (further A/B testing needed).

UberEats should also work on expanding the food selection otherwise they will not be able to capture the market even with the superior delivery time estimates.

Results

Blue ApronDigital Marketing Analysis

Organic SEO

Paid SEO

Personas

Personas

Personas

Call to Action

DressSwapNew Product Developement

DRESS SWAP is a dress lending app that provides instant access to over

1000 dresses of all styles.

With $50 billion worth of inventory that sit in women’s closets, Dress swap connects fashionistas (w/

unused dresses) with users looking for quality dresses at a discounted price through a convenient exchange.

Position Statement

Competitive Analysis

Cost vs. Benefit

Johns Hopkins UniversityField Experiment Design

What is the effect of a revamped

eNewsletter design on student engagement?

In order to estimate the effect of a revamped eNewletter design, we must define our constructs:

z = 1 = sending a treatment emailz = 0 = sending a control email

d = 1 = treatment, individual receives redesigned email newsletterD = 0 = control, individual receives email with status quo subject line and status quo newsletter design

Yi = 1 = completion of survey responseYi = 0 = no completion of survey response

Schemez (sending an email) → d (receives an email) → Y (survey completion)

Design and Definitions

There is an important distinction in our experiment, as effectively:

z = d

This is because by our definitions, sending is the same as receiving (we are assuming bounces to be

effectively zero). In effect, everyone is a complier.

Therefore, a estimand of the CACE = E[(Yi(d = 1) – Yi(d = 0)) | di(1) = 1] reduces to simply the ATE of

receiving an email:

ATE = Yi(d = 1) – Yi(d = 0)

Estimand

Conducted to get an estimate of the number of subjects required to conduct the analysis with

appropriate false positives (α) and false negatives (β)

Discussed the experiment with school internal communications person and received following

inputs:

●Current response rate of surveys - 30 to 40% for both full-time and part-time students (pc =

35%)

●Changing email format will not involve huge investment which led to expected raise of 5%

considering the total number of students in school (pt = 40%)

●Survey response rate is significantly different between asian and non-asian students, which

can be used as one of the covariates

Power Analysis (i)

Other Inputs:

●Total number of students: 2073 (923 full time and 1150 part time)

●Baseline α assumed as 5%

Power (β) calculated based on

Power Analysis (ii)

Sensitivity Analysis with a two variable data table including pt and pc shows that using N = 2073,

the power of experiment is likely to range from 75% to 98%

Sensitivity Analysis (i)

Sensitivity analysis with Alpha (α) and response rate of treatment group (pt) as variables again

reflects that the power will lie between 75% and 95%

Sensitivity Analysis (ii)

TeslaMarketing Case Analysis

Industry Factors

STP

Objectives

Marvel EnterprisesMarketing Case Study

WM. Wrigley Jr. CompanyCorporate Finance Case Study

Stock price: $56.37 per shareShares outstanding: 232.441 millionMarket cap: $13.102 billion

Beta (unlevered): 0.75Risk premium: 7%20-yr treasury rate: 5.65%

Cost of equity: 10.90%Cost of debt: 9.31% (AAA)

% equity of total market value: 100%% debt of total market value: 0%

WACC: 10.900%

Pre-CapitalizationFormulas

re = rf + β × (rm − rf)

WACC=(weight of equity) x (cost of equity) + (weight of debt) x (cost of debt) x (1- tax rate)

Pre-cap market cap: $13.102 billionBeta (unlevered): 0.75Risk premium: 7%20-yr treasury rate: 5.65%

Leveraged Beta: 0.869

New cost of debt: 14.66% % equity of total market value: 79.02%% debt of total market value: 20.98%

WACC: 11.12%

Post-CapitalizationFormulas

Levered β = Unlevered β ×[1 + [(D/E) ×(1−t)]

re = rf + β × (rm − rf)

WACC=(weight of equity) x (cost of equity) + (weight of debt) x (cost of debt) x (1- tax rate)

RecommendationA share repurchase would increase Wrigley's voter control and the price per share

Pre-CapitalizationShares Outstanding 232.441 million

Stock Price $56.37

Common Stock Class B Stock

Shares Outstanding 189.8 42.641

Votes Outstanding 189.8 426.41

Wringley Shares 39.858 24.73178

Wringley Votes 39.858 247.3178

% of Ownership 21% 58%

Recommendation

Share Repurchase vs. Dividend- a high dividend payout is important to investors,

however, taxation is higher on a dividend than a capital gain. A share repurchase would increase Wigley's voter control and price per share.

Post-CapitalizationShares Outstanding 183.684 million

Stock Price $61.53

CalculationNew stock price: (3 billion debt * 40%tax)/232.441 million = $61.53

Common Stock Class B Stock

Shares Outstanding 141.043 42.641

Votes Outstanding 141.043 426.41

Wrigley Shares 39.858 24.73178

Wrigley Votes 39.858 247.3178

% of Ownership 28% 58%