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Software platform for mining
social media for intelligence on a
massive scale
Winstonn Tubbs ( EL)
Nayanjeet Medhi ( TM)
Stephen Manti ( TM)
Social Radar
Team: 22_Mitre
Total No of Interviews: 67
Total No of Interviews this week: 13
01
Teaching Feedback -
Value Propositions are too generic
No clear metrics to show significance of value propositions
Too many Customer segments – find one and go in depth
Week 1 – The Canvas
Weeks 1& 2 – What we did?
Spoke to Marketers and Social Media Analysts
Industry Analysis
To understand the unmet needs of each customer segment
To understand the competitors and products
Find out the willingness to pay
Better understand the Social Radar technology
Weeks 1& 2 - What we learned?
Cost
Accuracy
Convenience
Differentiation
01
Teaching Feedback -
Interesting pivot with the reviews websites
“Don’t lead the customer interviews with tech- uncover problems”
Not satisfied with the reasoning behind small firms not being interested
in social media analytics
Week 3 – The Canvas
Weeks 3& 4 - What we did?
Continued to interview the niche customers for
social media analytics – journalists, financial
analysts, employees at other social media
analytics firms
Introduced value proposition for consumers
reading reviews
Spoke to consumers about experience and
pain points with user review websites.
Social Media
Analysis
Review
Aggregation
Review Aggregation Experiment -
Reading reviews consumes too much time and the current
process is not effective
Hard to find themes in reviews and get insights from them
Weeks 3& 4 - What we learned?
Social Media Experiment -
Too many social media analytics tools out there
Difficult to break in into niche markets – Journalism, Financial
Analysis
01
The Canvas Today
Week 5 - What we did?
Ended the social media analytics experiment
Focused on interviewing consumers for review
aggregation problem areas
Identify definite pain areas for consumers
Week 5 - What we learned?
*source – Cornell Hospitality Report Vol. 12 No.15, November 2012
Opportunity to become the Kayak of reviews
As mobiles become the new platform of internet and social media use, quicker and faster insights on the smaller screen become important
Need for observation of ratings or feedback over a timeline
Ratings have a direct impact on $$$*
Review aggregation problem is more of a convenience rather than a need
Social Media Analytics Go/ No Go
+ -No Go
Review Aggregation Application Go/ No Go?
+ -
Not a burning need for the consumer
$$$ depend on network effect
Data gathering issues???
Helps to have aggregation of
reviews
Saves time and effort
Easy and reliable insights
Depends?
Customer Experience Management Tool
+ -GO
