Facebook — Social Data Analysis Process

Exhibit 25.15   Facebook Brand Page Social Data Analysis Process.

Transforming raw data into actionable insights requires a structured process. As depicted in Exhibit 25.15, this process comprises the following stages:

• Data Extraction: Utilize the Facebook Graph API to retrieve relevant data from your brand page, including posts and comments.
• Metadata Collection: Collect and organize post-level details like timestamps, likes, shares, and comments.
• Text Analytics: Analyze user comments under each post. Break down text into individual words (tokenization) and identify frequently used keywords, two-word phrases (bi-grams), and significant hashtags.
• Time Series Analysis: Identify trends in user engagement and sentiment over time. Track fluctuations in likes, shares, and comments to understand how consumer perception evolves.
• Emotion Analysis: Utilize tools like the IBM Watson Natural Language Understanding (NLU) (formerly the Alchemy API) to extract emotions embedded within user comments.
• Analysis and Recommendations: Based on the findings, draw insights and recommendations. Identify content themes that resonate best, adjust brand messaging to address user sentiment, and refine marketing strategies for improved engagement.

By leveraging the power of Facebook Graph API and a structured analysis process, brands can unlock valuable consumer insights hidden within their brand pages. This understanding empowers them to build stronger relationships with their audience and achieve their marketing goals.