O V E R V I E W
In a market where product life-cycles are a few months long and
competition is heavy, waiting for and relying solely on point-of-sales
data was less predictive and constraining in terms of quick course
corrections. The Personal Computer manufacturer wanted to utilize
the market buzz and indications obtained from social media on early
days of launch to predict potential growth path of the product.

A P P R O A C H
Crawled data from social media sources like Twitter, Amazon, Google
reviews, CNET etc. to create predictive indices around market buzz and
consumer sentiments on key features to correlate with potential sales
trajectory of launched product.
1. Creation of Social Indices
– Crawling of mentioned, reviews, comments from various sources 9-10
products launched in last 2 years
– Advanced text mining to identify key features and scoring sentiments
displayed
– Creation of social indices around mentions, promotion, average reviews,
sentiments across key features for each product lifecycle.
2. Build Predictive Model
– Standardization of growth trajectory of various similar products
through parametric curves
– Creation of an advanced panel regression model to relate the social
indices and trends with the growth observed over time for various
products
– Assessing most predictive factors for relating with growth trajectory
and build a scoring model involving various social indices
3. Operationalization of Solution
– Developed set of indices which are highly predictive about product
performance

O U T C O M E
The solution provided initial insights on by key social media indices to
track for assessing performance of a product and react quickly to
potential corrective actions. Such solution is expected to be technology
enabled and operationalized across various products.