MBA 640 University of Maryland Global Campus CompanyOne Questions Worksheet

User Generated

Wnzfgre007

Business Finance

MBA 640

University of Maryland Global Campus

MBA

Description

Question 1

Find the number of active users (1 Day, 7 Day, 14 Day, and 28 Day) during July 2020. Calculate the ratio of 1 Day Active Users to 28 Day Active Users, expressed as a percentage. Typically, this ratio is considered a measure of the “stickiness” or retention of users for your website. It should be 10% or higher for sites where content is refreshed daily, like news sites, or where the site derives its revenue primarily from advertising. For social sites like Facebook and WhatsApp, the ratio could be a lot higher (>50%). For Ecommerce sites like CompanyOne, where usage is less frequent but of higher monetary value, the ratio is typically lower than 10%.

Also, compare the graphs for 1 Day Active Users to 28 Day Active Users. What conclusions can you derive? Please provide a screenshot to support your analysis.

Note: Active Users refers to the number of users who visited the CompanyOne website within the last 1, 7, 14 or 28 days looking back from the last day of the period which in this case is July 31, 2020.

The metrics in the report are relative to the last day in the date range. Given that your date range is July 1 to July 31:

1 Day Active Users: the number of unique users who initiated sessions on your site or app on July 31 (the last day of your date range).

7 Day Active Users: the number of unique users who initiated sessions on your site or app from July 25 through July 31 (the last 7 days of your date range).

14 Day Active Users: the number of unique users who initiated sessions on your site or app from July 18 through July 31 (the last 14 days of your date range).

28 Day Active Users: the number of unique users who initiated sessions on your site or app from July 4 through July 31 (the entire 28 days of your date range).

Question 2

Plot graphs of 1 Day Active Users for the second quarter in 2019 and the second quarter in 2020. Compare the number of active users for both periods from the two plots. What do you conclude about the change in marketing effectiveness, if any, from 2019-Q2 to 2020-Q2? Please provide a screenshot to support your analysis.

Question 3

Compare Bounce Rate for 2020-Q2 to 2019-Q2. What do you conclude? Similarly, compare Pageviews for 2020-Q2 to 2019-Q2. Please provide screenshots to support your analysis.

Question 4

CompanyOne wants to focus on younger users (18-24 and 25-34) who shopped during the 2019 holiday shopping season. Has the share of younger users changed from the holiday shopping season in 2018? Note: November 1 and December 31 are the start and end dates for the holiday shopping season for CompanyOne. How about changes in the proportions of older users during the same period? Please provide screenshots to support your answer.

Question 5

What about gender? CompanyOne’s objective was to attract a larger proportion of female visitors to their online store during the 2019 holiday shopping season as compared to the same period in 2018. Was that objective met? Please provide a screenshot to support your answer.

Question 6

CompanyOne has invested in a targeted marketing campaign to attract new users to their online store since the beginning of 2020. Did CompanyOne attract more or fewer new users from January - June 2020 compared to the same period in 2019, irrespective of gender? What about new male users? What about new female users? Please provide screenshots to support your answer.

Question 7

(a) What were the top three countries which sent users to the CompanyOne online store in 2019? In 2018?

(b) When parsing the percentage change in the number of new users, by country of residence, which one of the three countries identified in (a), had the best percentage change in new users during 2019 as compared to 2018? Which one of the same three countries showed the least improvement? Use the whole year for your comparison. Please provide a screenshot to support your answer.

(c) What were the top five U.S. states which sent users to the CompanyOne online store in 2019?

Question 8

CompanyOne wishes to target high-value users in future marketing campaigns. These are user groups with the highest Ecommerce Conversion Rate or Average Order Value. Which age group generated the highest revenue for CompanyOne in 2019 in dollars? How much was the revenue from this age group? Which age group generated the least revenue? Which age group had the highest average order value? Which age group had the highest Ecommerce Conversion Rate? Based on these observations, which age group or groups should be the focus of CompanyOne’s marketing efforts during 2020? In other words, which age group is likely to provide the most bang for the buck?

CompanyOne desires to examine the performance across the six age groups in further detail. You will examine the Ecommerce data by selecting two dimensions: gender and age. Which gender and age group combinations had the highest and second highest revenue in 2019? Similarly, which gender and age group combinations had the highest and second highest average order value in 2019? What would be your recommendation to CompanyOne based on this analysis? Provide screenshots to support your answers.

Question 9

CompanyOne wishes to understand its site visitors better in order to fine tune its future marketing efforts. Understanding audience composition in terms of gender, age, and interests will allow CompanyOne to develop the right creative content and decide the media buys to make.

Google Analytics has over 100 affinity categories such as:

  • Shoppers/Value Shoppers
  • Lifestyles & Hobbies/Business Professionals
  • Sports & Fitness/Health and Fitness Buffs
  • Technology/Technophiles
  • Banking and Finance/Avid Investors
  • Travel/Travel Buffs
  • Travel/Business Travelers
  • Media and Entertainment/Movie Lovers
  • Lifestyles and Hobbies/Art and Theater Aficionados
  • Media & Entertainment/Music lovers
  • and many more ...

Identify the top three affinity categories for CompanyOne by gender: male and female, for 2019 in terms of the revenue from each affinity category. Please provide screenshots to support your answer.

Question 10

The two things every online business like CompanyOne cares about: users who convert (purchase a product) and users who don’t. Understanding users who convert (Converters) will help CompanyOne refine successful aspects of their marketing, and show them where they can improve their efforts to reach users who demonstrate untapped potential (Non- Converters).

Developing insights into why certain users aren’t converting lets them address the weak spots in how they approach them. For the purpose of this analysis, CompanyOne wishes to focus on the Back to School shopping season (July 15, 2019 to September 15, 2019).

CompanyOne wishes to obtain statistics of users, sessions, sessions per user, page views, average session duration and bounce rate for these two segments (Converters and Non-Converters). Comment on these statistics.

Finally, evaluate the differences in user conversion by gender.

Provide screenshots to support your analysis.

User generated content is uploaded by users for the purposes of learning and should be used following Studypool's honor code & terms of service.

Explanation & Answer

Attached. Please let me know if you have any questions or need revisions.

Running head: COMPANYONE

1

CompanyOne
Student’s Name
Institutional Affiliation
Course
Date

2

COMPANYONE
Answers
Question 1
Day 1
Active users = 1488
Average = Active users/Day = 1488/1 = 1488
Day 7
Active users = 15426
Average = 15426/7 = 2204
Day 14
Active users = 28527
Average = 28527/14 = 2038
Day 28
Active users = 49473
Average = 49473/28 = 1767
Ratio of 1-day active users to 28-day active users
1488/49473) *100 = 3.01%
2500

2000

1500

1000

500

0
1

2

3

4

From the graph above 1 Day had fewer active users compared 28 Day.

3

COMPANYONE
Question 2

USERS 2018 AND 2019
2000
1800
1600
1400
1200
1000
800
600
400
200
0
1 DAY

7 DAY
2018

14 DAY

28 DAY

2019

From the graph above, we experience an increase in the number of new users in 2019 compared
to 2018, which brings us to a conclusion that 2019 market effectiveness was more sticker than
2018.

Question 3

Bouncing rate/pageview
50
45
40
35
30
25
20
15
10
5
0
2018

2019
Bouncing rate

Pageview

The bounce rate in 2019 is higher than the one in 2018 in both age and gender. Even though in
both years the rate ranges in the bracket of (40-55%); this shows that the bounce rate is usually
okay, but in 2019 there is a slight improvement. In 2019, the age bracket of 18 to 24 years had

4

COMPANYONE
highest bounce rate and male seems to be leading in that. In 2018, the age bracket of (1824years) had the highest bounce rate and this was led by male. This drive to a conclusion that in
both years men had highest bounce rate than ladies. Men have negative attitude towards the
usage of website.
In 2019, the pageview was rate was high than in 2018.this shows that in 2019 most of people
have a positive view towards the usage of website. The age bracket with highest page views is
35-44 years in both years. And in both years, men took the front part in page views.

Question 4

Shopping Season
450
400
350
300
250

200
150
100
50
0
non-holiday

Holidays
18-24

25-34

From the graph above, during non-holiday shopping season, young age of 18 – 24 recoded a
revenue of 0, while the medium age of 24 – 34 recorded a revenue of 319. After much focus had
placed on these two age brackets, an increase in revenue was observed. This is most probably
because, during holidays these ages has more increased needs. Comparing these changes of
revenue in young age to the old ages, we notice that it is inversely proportional. Old age shops
during non-holidays, where young do shop more during holidays....


Anonymous
Just what I needed. Studypool is a lifesaver!

Studypool
4.7
Trustpilot
4.5
Sitejabber
4.4

Similar Content

Related Tags