e-news-statistical-analysis

Business Context

The rise of e-news platforms has revolutionized how we stay informed about global events, offering swift updates on a daily basis. These platforms retrieve information electronically, process it with various software tools, and deliver it to users promptly. This electronic transmission of news comes with numerous benefits, including quicker access to content and the incorporation of multimedia elements like audio, graphics, and video, which are not as prevalent in traditional newspapers.

E-news Express, an online news outlet, is eager to grow its subscriber base. By closely analyzing user interactions on its website, the company aims to gain insights into user preferences and enhance engagement strategies. Executives at E-news Express suspect that a decline in monthly subscriptions may be attributed to the website's layout and content recommendations, which fail to captivate visitors long enough to encourage subscriptions.

To discern the effectiveness of different approaches, companies often employ A/B testing, comparing user responses to two versions of a product. This method helps determine which features resonate better with users based on predefined metrics.

Objective

The company's design team has developed a fresh landing page with a revamped layout and more relevant content compared to the previous version. To assess its impact on attracting new subscribers, the Data Science team initiated an experiment. They randomly divided 100 users into two equal groups. The first group (control) viewed the existing landing page, while the second group (treatment) saw the new one. User interaction data for both versions was collected.

As a data scientist at E-news Express, I'm tasked with delving into the data and conducting a statistical analysis (at a significance level of 5%) to evaluate the effectiveness of the new landing page in acquiring new subscribers for the news portal. My analysis should address the following questions:

Key Questions

• Are users spending a longer duration on the new landing page compared to the existing one?
• Does the new landing page have a higher conversion rate than the old page?
• Is there a correlation between the conversion status and the preferred language of the users?
• Do users across different languages spend a similar amount of time on the new landing page?

Data Dictionary

The dataset includes details of user interactions with both versions of the landing page.

• user_id: Unique identifier for each visitor to the website
• group: Indicates if the user is in the control group (first group) or treatment group (second group)
• landing_page: Specifies whether the user viewed the new or old landing page
• time_spent_on_the_page: Duration (in minutes) the user spent on the landing page
• converted: Indicates whether the user became a subscriber of the news portal
• language_preferred: Language selected by the user for viewing the landing page

Skills Used

• Exploratory data analysis
• Inferential statistics
• Estimation and hypothesis testing
• Common statistical tests

Actionable Insights and Reccomendations

Insights

Do the users spend more time on the new landing page than on the existing landing page?

The P-value (0.0001392381225166549) is smaller than the level of significance (0.05).Thus, we have enough statistical evidence to say that users spend more time on the new landing page than the old landing page.

Is the conversion rate (the proportion of users who visit the landing page and get converted) for the new page greater than the conversion rate for the old page?

The P-value (0.016052616408112556) is smaller than the level of significance (0.05).Thus, we have enough statistical evidence to say that conversion rate for the new page is greater than the conversion rate for the old page.

Does conversion depend on the preferred language?

The P-value (0.2129888748754345) is greater than the level of significance (0.05).Thus, we do not have enough statistical evidence to say that conversion and preferred language are dependent.

Is the time spent on the new page the same for the different language users?

The P-value (0.43204138694325955) is greater than the level of significance (0.05).Thus, we do not have enough statistical evidence to say that at least one language group is different from the rest.

Recommendations for the Business

• Implement the new landing page to replace the old one for all user segments. This is the recommended course of action.
• The data suggests that the new landing page is more captivating and results in higher conversion rates across various language groups.
• Provide experienced users with the option to revert to the old landing page if needed, as some users are already well-versed in navigating the existing page.
• Direct efforts towards enhancing the landing page experience for non-English speakers, as this market segment shows the most significant improvements.
• Consider conducting experiments to assess the population's familiarity with the news site and offer landing page variations to cater to users with varying levels of proficiency.