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Managing Director at Trident Capital focusing on investments in Internet and software businesses. Prior to entering venture capital, Evangelos had more than 20 years experience in high-technology industries, in executive roles spanning operations, marketing, sales and engineering. Evangelos earned a PhD in computer science from Brandeis University and a BS in electrical engineering from Caltech.

3 responses to “Analyzing Social Analytics”

  1. Joe Tierney (@JoeTierney)

    Evangelos,

    Thank you for this write up. It is excellent. I’ve seen several firms leverage social analytics very effectively for marketing strategy, campaign monitoring, product development and customer service (mirrored customer conversation & scripts).

    Some firms understand big data better than others. The volume of conversation is just not something that is comprehended easily (or naturally). It’s important to help people move beyond counting and to work towards understanding relationships.

    I think the term “social” also clouds many people’s approach to the data. People hear social and put it in the “social media bucket”. Rather than thinking “what if I could learn the opinion of every customer and potential customer, what if I could ask any customer why they chose our competitor, what if I could see what the market thought about almost any topic imaginable?” Certainly some use cases are more challenging but we have reached a tipping point as nearly everyone can be a content creator in seconds and we have the capacity to find, store and analyze every bit of it.

    I agree that the combination of social analytics data with business intelligence or other data sets is the next step forward. It’s all about adding more context to reach a higher level of understanding. Infegy has been pushing this idea hard and recently released a weekly “Top 50 Social Brands” app (http://goo.gl/39Apx) to generate excitement/ideas specific to custom apps leveraging social analytics data APIs.

    Thank you for the write up. Look forward to checking out the MGI paper.

  2. Hagan Ramsey

    Would have appreciated some specific examples of different analytics tools as they apply to your main points (pros/cons of each tool).

    Ex: which tool is best for sentiment analysis? Crimson Hexagon maybe? Can the user edit incorrect sentiment returns within your preferred software? does this software understand people’s sarcasm in their speech? does this software “learn” after the user repeatedly changes a certain type of sentiment?

  3. esimoudis

    @Hagan: Not being a user of these tools makes it hard for me to provide a comprehensive evaluation of each tool’s merits. I’m commenting on the fact that there are many social analytics tools in the market that more or less do the same thing while they are not addressing what I feel are some of the harder problems. I was hoping that the readers of the blog would be able to provide more specific commentary about the tools and correct my assumptions. Suffice it to say though that I have not invested yet in any company that provides social analytics solutions. My own portfolio companies are developing their own solutions in this area because they couldn’t find an appropriate third-party tool

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