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
