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Skullcandy + Twitter surgery
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  1. Skullcandy + Twitter surgery Team PowderQuants

  2. Mining social data • Mining social twitter data can make for an ugly mess. How do we make sense of it, how do we provide data? • Solution: create word clouds based on questions of interest. ? More explained on the next slide.

  3. Questions of interest • If a tweet can be flagged it can be used to answer a question: • Tweets coming from the highest selling zip codes per capita vs tweets coming from the lowest selling zip codes per capita • Tweets from competitors vs people who follow us. • Tweets that like us (positive sentiment) and those users that don’t (negative sentiment).

  4. Tweets…. How to join? • Tweets can be weakly joined with our data using geolocation on the tweet to map it into a zipcode. Then using zip code we can join on the sales data. • Ideally…. You would be collecting your buyers social handles if possible. This would be more accurate.

  5. We have categorized tweets…now what? • Once we have categorized tweets we can build word clouds!!! Yay! words words words words words words words words words words Category A (could be negative sentiment, low selling areas, etc..) Category B (could be negative sentiment, low selling areas, etc..)

  6. You lost me at word cloud • A word cloud is just a combination of ALL of the words for that group. So imagine all of the tweets being dumped into a single massive tweet

  7. We have two word clouds • Now that we have two word clouds we can do some really cool stuff. For example, we can look at nonintersects between them. So what kinds of words or phrases are said in cloud A, but not in cloud B. • Doing this may identify the user demographic. For example, snowboarders, or ollie was mentioned only in cloud A.

  8. Finding your focus group! • So once we have identified the key differences between the two word clouds we can actually locate specific users that are the best representations of those qualities. So the focus group has been reduced down to a single twitter handle. If you need more information you can reach out to a very targeted group of twitter users now to get more insight in potential markets, or find out why they aren’t buying your product over a competitors.

  9. Where is all of this amazing data? • All twitter has been scraped and collected. If a presentation can be scheduled later in the week the cloud nonintersections and target focus group list generation can be demonstrated.