Project 3: Digital Marketing Analytics- MUST CREATE AND USE FREE GOOGLE ANALYTICS DEMO ACCOUNT
A. Review these instructions for how to activate your google Analytics demo account.
B. Scan Ying’s memo (Step 3) for a list of 10 client questions for which you will use Google Analytics to answer: The Google Analytics demo account will give you access to data from the Google Merchandise Store, which in this project represents CompanyOnes data.
Submit your answers to each of the ten questions in a Word document. Remember to include one or more screenshots of the relevant Google Analytics page to support each of your answers. If you need help with creating screenshots, review these instructions on capturing screenshots for your Microsoft, Apple, or Android system.
Refer to the Project instructions for full details.
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.
Find the number of active users (1-day, 7-day, 14-day, and 28-day) during January 2019. 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 e-commerce 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? 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 January 31, 2019.
The metrics in the report are relative to the last day in the date range. Given that your date range is January 1 to January 31:
1-day active users: The number of unique users who initiated sessions on your site or app on January 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 January 25 through January 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 January 18 through January 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 January 4 through January 31 (the entire 28 days of your date range).
Plot graphs of 1-day active users for the first quarter in 2018 and the first quarter in 2019. 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 2018-Q1 to 2019-Q1? Provide a screenshot to support your analysis.
Compare bounce rate for 2019-Q1 to 2018-Q1. What do you conclude? Similarly, compare page views for 2019-Q1 to 2018-Q1. Provide screenshots to support your analysis.
CompanyOne wants to focus on younger users (1824 and 2534) who shopped during the 2018 holiday shopping season. Has the share of younger users changed from the holiday shopping season in 2017? 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? Provide screenshots to support your answer.
What about gender? CompanyOne’s objective was to attract a larger proportion of female visitors to its online store during the 2018 holiday shopping season as compared to the same period in 2017. Was that objective met? Provide a screenshot to support your answer.
CompanyOne has invested in a targeted marketing campaign to attract new users to its online store since the beginning of 2019. Did CompanyOne attract more or fewer new users in 2019-Q1 compared to 2018-Q1, irrespective of gender? What about new male users? What about new female users? Provide screenshots to support your answer.
(a) What were the top three countries that sent users to the CompanyOne online store in 2018? In 2017?
(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 2018 as compared to 2017? Which one of the same three countries showed the least improvement? Use the whole year for your comparison. Provide a screenshot to support your answer.
(c) What were the top five US states that sent users to the CompanyOne online store in 2018?
CompanyOne wishes to target high-value users in future marketing campaigns. These are user groups with the highest e-commerce conversion rate or average order value. Which age group generated the highest revenue for CompanyOne in 2018 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 e-commerce conversion rate? Based on these observations, which age group or groups should be the focus of CompanyOne’s marketing efforts during 2019? 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 e-commerce data by selecting two dimensions: gender and age. Which gender and age group combinations had the highest and second highest revenue in 2018? Similarly, which gender and age group combinations had the highest and second highest average order value in 2018? What would be your recommendation to CompanyOne based on this analysis? Provide screenshots to support your answers.
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:
lifestyles and hobbies/business professionals
sports and fitness/health and fitness buffs
banking and finance/avid investors
media and entertainment/movie lovers
lifestyles and hobbies/art and theater aficionados
media and entertainment/music lovers
Identify the top three affinity categories for CompanyOne by gender: male and female, for 2018 in terms of the revenue from each affinity category. Provide screenshots to support your answer.
The two things every online business like CompanyOne cares about are users who convert (purchase a product) and users who don’t. Understanding users who convert (converters) will help CompanyOne refine successful aspects of its marketing and show the company where it can improve efforts to reach users who demonstrate untapped potential (nonconverters).
Developing insights into why certain users aren’t converting lets CompanyOne 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, 2018 to September 15, 2018).
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 nonconverters). Comment on these statistics.
Finally, evaluate the differences in user conversion by gender.
Provide screenshots to support your analysis.