Social Media Analytics

Data : User comments, Free text, Blog information, Reviews, Responses, Questions, Complaints, Complements, Tweets, Face book comments

Analysis

1. Key Performance Indicators

Key Metrics Reporting:

Reports on number of comments, mentions, posts, blog posts, tweets, likes, fans, followers, replies, reviews, shares, time interval between posts across demographics parameters like location, age, gender and many more.


Key Metrics Analysis

• Time series analysis of above metrics & forecasting near future numbers
• Top influencing nodes (websites or individuals) & their trends
• Identification of Hotspot-1: In terms of demographics, which area has maximum buzz
• Identification of Hotspot-2: In terms of time, what is the maximum buzz hour
• Analysis on real-time data: Dynamic creation of alerts based on buzz, influencers, sentiment metrics. For example, a sudden increase in negative sentiment, long gap between two comments, latest influencers can be alerted.

2. Text Analyzer & Sentiment Analysis

• Use a Verbatim tool or an API that takes text comments as input and Decides the polarity (+ve or -ve) of the comment, Reports top N websites with +ve and -ve comments, Gives the frequency of keywords & Gives overall sentiment & sentiment across various cuts
• Driver Analysis: Identification top impacting drivers of satisfaction (sentiment) based on textual comments.E.g.: What are top drivers of satisfaction? (Lifestyle, Attitude, Beliefs, Personality, Buying motives, Age, Gender, Education, Income, Geography, State, ZIP, City size, Rural vs. Urban, etc)
• Identification of Themes: Divide entire comments into finite clusters which are homogeneous among them and heterogeneous compared to others. Each cluster gives a theme of discussion

3. Ranking Nodes (websites) in the Order of Importance:

Identification of most impacting websites/individuals (with respect to our brand) by scoring them based on below mentioned indicators

• Websites reach: Numbers of subscribers, fans, followers, readers, members etc.
• Buzz created by website (with respect to our brand): comments, likes, shares, replies, reviews, etc.
• Web site & followers characteristics: Website type, followers Age group, Geographie

4. Segmentation: Dividing the entire population (users mentioned about our product), into independent groups based on Sentiments (People who are most satisfied & least satisfied and their characteristics) & Buzz created (Top influencers segment & their behaviors)

5. Competition or Peer comparison: Analyze social media data of the competing products to find Weak links, strong points, Most frequent comparisons, Emerging competitors & their demographics etc.

-Venkat Reddy

Trendwsie Analytics

http://www.trendwiseanalytics.com/

Tags

KPI’s for Social Media Analysis, Metrics and Methods used in Social Media Analytics, Social Media Metrics, Social Media Reports Social Media Analysis & Reporting, Analysis of Social Media Data