Social Media Analytics for Category Benchmarking

Posted by | Fuld & Company

A leading global luxury magazine sought to develop a luxury brand index to compare the performance of luxury brands based on several parameters, including social media.

Objective

To leverage social media and other metrics as inputs to create a luxury brand index.

Approach

• Collected social media data from Twitter, Instagram, and Facebook, using web scrapers to capture public data.
• Recorded parameters such as number of followers, number of posts, frequency of posts, number of shares, sentiment, key trending topics, etc., for each social media channel.
• Captured data related to revenue, profitability, new product launches, brand ambassadors, brand website and engagement, mobile app and its features, etc., via desk research or from third-party data providers (e.g., App IQ and Capital IQ).
• Leveraged Python and its NLP libraries to perform sentiment and bag-of-words analyses.

Outcome

The computed index and sub-indices provided critical insights into brands’ social media performance and benchmarked it against direct competitors and overall product category.

Algorithms Used: NLP, VADER, and bag-of-words analysis

Tools

Tags: case study, Consumer Products & Retail, Data analytics, index, luxury, social media