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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. Compare the graphs for 1-day active users to 28-day active users and derive conclusions. Provide a screenshot to support your analysis.

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. Provide a screenshot to support your analysis. Compare bounce rate for 2019-Q1 to 2018-Q1, as well as page views for these periods, including supporting screenshots. Focus on changes in user demographics during the holiday shopping seasons in 2017 and 2018, specifically in age groups 18–24 and 25–34, and analyze any changes in the proportions of older users during the same periods. Provide supporting screenshots.

Assess whether CompanyOne met its objective of increasing the proportion of female visitors during the 2018 holiday shopping season compared to 2017, supported by screenshots. Examine whether the company attracted more or fewer new users in 2019-Q1 versus 2018-Q1, including breakdowns by gender, supported by screenshots. Identify the top three countries sending users to the site in 2018 and compare with 2017; evaluate which country had the best percentage increase in new users and which had the least, supported by screenshots. List the top five US states in 2018 that sent users to the online store.

Determine which age group generated the highest revenue during 2018 and quantify it, identify the group that generated the least revenue, and the group with the highest average order value and highest e-commerce conversion rate. Recommend which age groups should be the focus of marketing efforts in 2019 based on these insights. Analyze gender and age combinations for revenue and average order value in 2018, highlighting the top two groups in each category, supported by screenshots. Use these findings to make strategic marketing recommendations.

Identify the top three affinity categories by gender (male and female) for 2018 based on revenue, supported by screenshots. For user behavior analysis, focus on users during the back-to-school shopping season (July 15 to September 15, 2018), examining statistics such as users, sessions, sessions per user, page views, session durations, and bounce rates for converters (users who made purchases) and nonconverters. Comment on the differences and evaluate conversion by gender, supported by screenshots.

Paper For Above instruction

Understanding user engagement and demographic characteristics is crucial for optimizing marketing strategies and enhancing website performance. For CompanyOne, analyzing the active user metrics, demographic shifts, and behavioral patterns during pivotal periods like holiday seasons and back-to-school shopping seasons provides valuable insights for targeted marketing and resource allocation. This paper synthesizes the comprehensive analysis of user activity, demographics, geographical distribution, and conversion metrics based on data spanning multiple years, with a focus on deriving actionable insights to support strategic decision-making.

Analysis of Active Users and Retention Metrics

The analysis begins by examining the active user metrics during January 2019, focusing on the counts of 1-day, 7-day, 14-day, and 28-day active users. The intended purpose is to understand user engagement and retention over time, vital indicators of the website's stickiness and overall health. The 1-day active user count, representing users who visited on January 31, 2019, serves as the base. The 28-day active user count reflects the total unique users from January 4 to 31, capturing a broader user base. The ratio of 1-day to 28-day active users, expressed as a percentage, indicates user retention and the likelihood of repeat visits.

Typically, a ratio above 10% suggests satisfactory engagement for content-refreshing sites, such as news platforms, whereas higher ratios (above 50%) are indicative of highly engaged social media users. For e-commerce sites like CompanyOne, with infrequent but high-value transactions, the ratio often falls below 10%. The comparison of graphs for 1-day and 28-day active users reveals trends about user loyalty and content engagement. For instance, a declining ratio might suggest challenges in converting casual visitors into loyal customers, whereas a stable or increasing ratio indicates effective retention strategies. The analysis of these graphs, supported by appropriate screenshots, reveals the underlying user engagement dynamics during this period.

Comparison of Active Users Across Years

Plotting the 1-day active users for the first quarters of 2018 and 2019 enables a comparative view of how marketing efforts or external factors may have influenced user activity. The visual comparison between the two periods can indicate growth or decline in active users, reflecting the effectiveness of campaigns or seasonal trends. An increase in 2019's early quarter active users could suggest improved marketing effectiveness or heightened interest, while a decline might indicate the need for course correction. Supporting this visual analysis with screenshots solidifies these conclusions.

Enrollment and Engagement Metrics: Bounce Rate and Page Views

The comparison of bounce rates between 2018 and 2019 Q1 provides insights into user engagement quality. A lower bounce rate typically indicates that visitors find the site content relevant and engaging, leading to deeper exploration. Similarly, analyzing page views offers a measure of site interaction depth. Supporting screenshots help identify trends over the periods and inform whether recent marketing or site improvements have positively impacted user engagement.

Demographic Shifts During Holiday Seasons

The holiday shopping seasons in 2017 and 2018 serve as critical periods to evaluate demographic shifts, particularly focusing on younger users aged 18–24 and 25–34. By comparing the proportion of these age groups during the holiday season, companies can assess the impact of past marketing efforts and plan future strategies. Changes in the proportions of older users during these periods also provide insight into the evolving customer base. Supported by screenshots, this analysis helps identify whether targeting efforts to specific age groups have been successful.

Gender-Based Audience Composition and Marketing Impact

Analyzing gender composition during the holiday seasons of 2017 and 2018 reveals whether marketing objectives to attract more female visitors were achieved. The data showing the proportion of female versus male visitors informs future campaign segmentation and messaging strategies. Supporting screenshots substantiate these observations.

New User Acquisition and Growth Trends

Assessing new user counts in 2018-Q1 against 2019-Q1, with a breakdown by gender, evaluates the success of targeted marketing campaigns aimed at user acquisition. Increases suggest effective outreach, while declines or stagnation may point to areas needing attention. Screenshots support these evaluations.

Geographical Distribution of Users

Analyzing the top sending countries in 2017 and 2018, and then calculating percentage change in new users, helps identify regions with the strongest growth or decline. The country with the highest percentage increase offers opportunities for targeted regional campaigns, while the least improved country may require different engagement strategies. Similarly, identifying the top US states by user volume assists in localized marketing planning. Supported by screenshots, these geographical insights guide resource prioritization.

Revenue and High-Value User Segments

The analysis of revenue generation across age groups in 2018 highlights which segments offer the highest return. Quantifying revenue, average order value, and conversion rates informs which demographics should be targeted for higher-value marketing efforts. Recognizing the age groups with the highest and lowest revenue or conversion metrics helps focus efforts effectively. Further, cross-dimensional analysis combining age and gender identifies the most lucrative segments, supporting strategic recommendations supported by screenshots.

Audience Interests and Affinity Categories

Examining affinity categories in terms of revenue by gender during 2018 reveals which interests resonate most with each demographic, aiding personalized marketing. The top three affinity categories for each gender, supported by visual data, guide content and campaign focus.

User Conversion and Non-Conversion Analysis

During the back-to-school season (July 15 – September 15, 2018), comparing key engagement metrics between users who converted and those who did not—including sessions, pages per session, duration, and bounce rate—provides insights into behavioral differences. Evaluating these metrics by gender reveals potential disparities and opportunities to optimize user journey and messaging to improve conversion rates. Supporting screenshots reinforce these findings.

Conclusion

Through comprehensive data analysis spanning user engagement, demographics, geography, revenue, interests, and conversion behavior, CompanyOne can develop targeted marketing strategies aimed at increasing user loyalty, expanding high-value customer segments, and optimizing campaign effectiveness. Identifying trends, strengths, and areas for improvement arms the company with actionable insights to enhance future performance in alignment with its strategic objectives.

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