Answer CompanyOnes Data Analysis Questions

by / On November 7, 2020 / In APA (edition "APA 6"), Business and Management

The past few weeks have flown by. You have just completed the GA tutorial when you receive a memo from Ying marked CONFIDENTIAL. You scan the memo to find a list of client questions that have been assigned to you. You are expected to use Google Analytics to answer the 10 questions in the memo by the end of Week 7. The Google Analytics demo account will give you access to data from the Google Merchandise Store, which in this project represents CompanyOnes data.

Review these instructions for How to Activate the Google Analytics Demo Account.

Submit your answers to each of the ten questions and the accompanying screenshots in a Word document to the dropbox located in the final step of this project.

Remember to include one or more screenshots of the relevant Google Analytics page to support your answers. If you need help with creating screenshots, review these instructions on capturing screenshots for your Microsoft, Apple, or Android system.The next step provides a summary of all deliverables due during this project.

The next step provides a summary of all deliverables due during this project.

MEMO

Subject: Confidential MemoCompanyOne
From: Ying Bao

Directions: Review and answer the following questions, which have been assigned to you in the CompanyOne case. You will need to capture screenshots to complete these questions; if necessary, review these instructions on capturing screenshots.

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? CompanyOnes 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.

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 CompanyOnes 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 dont. 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 arent 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.