How Businesses Can Create Social Media Content for Engagement: An Exploratory Analysis
Introduction
In today’s digital world, businesses increasingly rely on social media to reach and interact with their target audience. Many companies, however, need help to develop content that continually grabs the attention of viewers, increases engagement, and turns them into actual consumers. Businesses frequently ask questions like, “What type of social media content can generate the most engagement for our business?”
As a content creator with experience on YouTube and other platforms and over 12,000 combined followers, I will be exploring this topic, focusing on how businesses may improve their content strategy to increase engagement. The stakeholders in this analysis include social media managers, content creators, and digital marketing teams looking to make data-driven decisions about content strategy.
My report will help make decisions about content formats, posting frequency, and the types of content that perform best on different platforms. I will examine data from major social media platforms such as YouTube, Instagram, and Facebook to identify patterns that businesses can use to generate more engaging content. By studying factors such as content type, posting times, and engagement metrics, I hope to provide actionable insights for optimizing social media strategy.
The Data
The data for this analysis includes metrics that are generally available on social media platforms, such as:
· Platform: The social media platform where the content will be posted, such as YouTube, Instagram, or Facebook. This allows us to compare content based on the type of platform.
· Content-Type: Whether the post is a video, image, text, or another type of media, such as polls or carousels.
· Engagement Metrics: This includes Likes, comments, shares, views, and reactions. This type of data gives a clear view of how users engage with the content.
· Posting Times and Dates: Knowing when content should be posted helps us determine whether certain times or days are associated with higher engagement.
· Reach or Impressions: These metrics indicate how many users the content is recommended to, and this also provides context for the engagement metrics.
· Hashtags and captions: These are textual features that might influence the post’s reach or relevancy.
· Audience Demographics: These include Information such as age, gender, and geography that can help identify which audience categories are engaged with the content.
Data Collection
For this exploratory analysis, I used a publicly available Kaggle dataset called “Social Media Engagement Report.” The dataset includes a wide range of social media performance metrics for multiple platforms such as Facebook, Instagram, Twitter, and LinkedIn. These metrics include engagement variables such as likes, comments, shares, impressions, and engagement rate, which are essential for determining the impact of social media posts.
The dataset was originally gathered from a variety of sources that track social media statistics, including APIs and third-party analytics tools. This provides businesses with a full perspective of how their posts perform across several platforms.
To access and use the dataset, I got the Excel file from Kaggle and used Python’s pandas package to read and convert it to CSV format for easy manipulation. The pandas library makes it easier to read, analyze, and clean the data.
Here is a code snippet that shows how I loaded the data:
NOTE: Businesses who want to acquire real-time data from social media networks can use APIs such as the YouTube Data API, Instagram Graph API, and Facebook Graph API. However, for the purposes of this analysis, I used a pre-existing dataset from a trusted source.
Exploratory Data Analysis
Based on the Data Metrics, I performed various data analysis in Python which focuses on analyzing different aspects of the data to uncover insights that are relevant to my analysis.
· Platform Analysis
Objective: Compare engagement metrics across different social media platforms. Analysis: Count the number of posts per platform. Calculate average engagement metrics (likes, comments, shares) for each platform.
· Content-Type Analysis:
Objective: Determine which types of content generate the most engagement.
Analysis: Count posts by content type. Calculate average engagement metrics for each content type
· Engagement Metrics Analysis:
Objective: Understand how different engagement metrics (likes, comments, shares) are distributed and related.
Analysis: Summary statistics and distribution of likes, comments, and shares. Correlation between engagement metrics.
· Posting Times and Dates Analysis:
Objective: Identify the best times or days for posting to maximize engagement.
Analysis: Convert timestamps to datetime format. Extract day of the week and hour of the day from timestamps. Analyze engagement metrics based on these factors
· Audience Demographics Analysis:
Objective: Understand how different demographics impact engagement.
Analysis: Summary statistics for audience demographics (age, gender, location). Analyze engagement metrics by age group and gender.
Data Cleaning
To ensure the accuracy and reliability of the exploratory data analysis, several kinds of data cleansing steps were required:
Handling Missing Values: Checked for and fixed missing data in important columns including ‘Likes,’ ‘Comments,’ ‘Shares,’ ‘Impressions,’ ‘Reach,’ and ‘Engagement Rate.’ To ensure data integrity, entries with significant missing data were either filled in with default values or eliminated.
Correcting Data Types: Ensured that numeric columns were formatted appropriately as numeric types and that timestamps were interpreted as datetime objects. This resulted in precise calculations and aggregates.
Removing Duplicates: Duplicate rows were identified and eliminated to prevent misleading engagement metrics and misleading results.
Text Field Standardization: To ensure consistency across the dataset, text fields such as ‘Platform’ and ‘Post Type’ were converted to lowercase and any unnecessary whitespace removed.
Handling Outliers: Outliers in engagement metrics were identified and treated to avoid biased statistical measurements, with extreme results adjusted or excluded as needed.
Validating Date and Time Formats: Ensured that all timestamps were properly initiated and valid in order to conduct reliable time-based analysis.
Addressing Missing or Inconsistent Data: Handled missing or inconsistent data in columns like ‘Hashtags Count’ and ‘Audience Demographics’ by either filling in defaults or eliminating problematic entries from particular analysis.
Figures & Tables
Limitations
Audience bias: Each platform’s audience is different, therefore an approach that works for one platform may not work for another.
Sample size: The analysis relies on data from a small number of business channels, which may not be representative of all industries.
Platform bias (TikTok): The analysis excludes TikTok data due to a lack of relevant datasets. This may limit the comparison’s impact across all major social media platforms.
Conclusions and Recommendations
· Best Platform
Platform: Instagram.
Number of posts: 150.
The average engagement rate is 7.5%.
Why: Instagram has the greatest average engagement rate of any platform, showing that its audience engages more regularly and positively with content posted here.
Recommendation: Use Instagram for your most important content and advertising initiatives. This platform has shown to be the most successful for engaging your target demographic.
· The best time to post.
Time of Day: 6 PM to 8 PM
Average engagement rate: 8.2%.
Why: Posts produced between 6 and 8 p.m. have the best engagement rates, indicating that this is when your target audience is most active and willing to connect with content.
Recommendation: Schedule your posts around this period to increase visibility and engagement.
· Best Age Group
Age group: 18–24.
Average engagement rate: 8.5%.
Why: The 18–24 demographic has the highest engagement rate, indicating that they find your content very interesting or relevant.
Recommendation: Create material that is specifically tailored to this age group, and consider targeting advertising and promotions to them.
· Best Content Type
Content Type: Video.
Number of posts: 80.
Average engagement rate: 10.0%.
Why: Video content has the highest engagement rate, which means it gets more attention and interaction from your audience than other types of content.
Recommendation: To increase engagement, create more video content and experiment with different styles and themes.
GitHub Repository
For the complete code used in this analysis, including data collection and visualization scripts, you can visit my GitHub repository;
