Social Radar Presentation: Customer Discovery and Business Model
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The Social Radar team's story about our journey through the I-Corps process, and how it informed our revised business model. Findings: Social Radar is a software platform that can be used to mine social media, comments, review and customer feedback for intelligence on a massive scale. customer experience online to increase revenue. The covers everything from customer feedback, reviews, to conversations online to make business decisions. The suite can be best utilized as Customer Experience Management product. It can optimize the various touch points with customers to understand their needs, create more loyalty and increase revenue. There are some players currently in the market but not many that can holistically analyze customer feedback on all channels.
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Social Radar Presentation: Customer Discovery and Business Model
- 1. Software platform for mining social media for intelligence on a massive scale Winstonn Tubbs ( EL) Nayanjeet Medhi ( TM) Stephen Manti ( TM) Social Radar winstonnt@gmail.com nayanjeet.medhi@gmail.com stephen.manti@rhsmith.umd.edu Team: 22_Mitre Total No of Interviews: 67 Total No of Interviews this week: 13
- 2. 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
- 3. 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
- 4. Weeks 1& 2 - What we learned? Cost Accuracy Convenience Differentiation
- 5. 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
- 6. 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
- 7. 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
- 9. 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
- 10. 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 $$$* Review aggregation problem is more of a convenience rather than a need
- 11. Social Media Analytics Go/ No Go + - No Go
- 12. Review Aggregation Application Go/ No Go? + - Not a burning need for the consumer $$$ depend on network effect Data gathering issues??? Helps to have aggregation of reviews Saves time and effort Easy and reliable insights Depends?
- 13. Customer Experience Management Tool + - GO
Hinweis der Redaktion
- TALK ABOUT THE product Talk about the different model ( we don’t own
- Improve the relevancy and timeliness of responses to consumers by more quickly understanding emerging topics and events to supporting decision making Improve insights from social media to formulate brand messaging. Lower online advertising costs by allowing marketers to avoid data brokers and tag their own demographic data and understand the behavior of those users
- Spoke to Marketers and Social Media Analyst. Industry Analysis Understand the unmet needs of each customer segment. Understand the competitors and products. Find out the willingness to pay. Better understand the Social Radar technology.
- Cost: A lot of tools are too expensive. Monitoring and getting insights from social media should not be too expensive. Social Radar needed dedicated Data Analyst to utilize the features. Accuracy: It is difficult to be 100% accurate but accuracy is very important. i.e.- Relevant content from keywords Convenience: A robust dashboard that includes multiple tools, user friendly interface, and easy to read and automate reports. 4) Differentiator: The differentiators in the Social Radar suite of products was not as important to the customer segment. a. Marketers did not the need for granular sentiment analysis from social radar. b. Pinocchio: Unique Tool however not enough willingness to pay.
- Improve the relevancy and timeliness of responses to consumers by more quickly understanding emerging topics and events to supporting decision making Improve insights from social media to formulate brand messaging. Lower online advertising costs by allowing marketers to avoid data brokers and tag their own demographic data and understand the behavior of those users
- How they use site, time spent and do they get the insights they are looking for and would they do this differently. Introduced value proposition for consumers who read through reviews before making their purchasing decisions
- Improve the relevancy and timeliness of responses to consumers by more quickly understanding emerging topics and events to supporting decision making Improve insights from social media to formulate brand messaging. Lower online advertising costs by allowing marketers to avoid data brokers and tag their own demographic data and understand the behavior of those users
- Invalidated Invalidated due to time constraints of the program. Pursuing the other value proposition. Value Propositions: Improve the quality of rating system of review websites by adding more context to company and product reviews. Customer Segments: Product managers at review sites Customer Segments: Social Media Managers. What did we want to test Do people really care about this? Do users look at multiple websites? What are the pain points? Do they look for insights in the review that don’t find in the rating.
- What we Found Invalidate one of the Value props and corresponding CS for time constraints. People want to index and find trends. Users are looking for specific insights. Different palettes – predefined review parameters are not helpful. Interesting features to add on the website.