I made it to Adobe Summit 2014 and my first session is How to build a social program using Adobe Social. This is a technical session presented by Carmen Sutter, Adobe’s Product Manager for Adobe Social and Greg Greenstreet VP Engineering at Gnip.
550 million tweets were sent in one day. Yet, there is almost no organization to those tweets. You can’t easily go find tweets about your brand, posted by your employees etc. Add in Facebook, Instagram, Google+ and others you can see that mining social data is not easy. But you must mine this data if you want to understand what people are saying about you.
To make sense of all this data, you want to “cast the right size net for your social campaign”. In other words you want to filter all the data using various techniques. The most basic technique is to use boolean And, Or, and Negation. Gnip uses this kind of filtering as the starting point to filter the huge amount of data coming from the social platforms. Adobe Social then takes that filtered data to further refine the data.
In addition to Boolean, you can also filter on geo-tagging. However only 1-2% of users actually make it easy by supplying or using geo-encoding when tweeting. So Gnip uses other techniques to grab geo-information.
Using public APIs you can also filter on language, hashtags and many other attributes of social data.
Next, you have to figure out what to do with the filtered data. Look at the goals of what you are trying to accomplish. This will affect the workflows you set up for monitoring and responding.
In the session the presenters talked about monitoring the Olympics Twitter feed. So they’ve already performed one level of filtering. Then they looked at specific hashtags, event names, event types and more.
A Social Buzz report showed distinct spikes during the Olympics – one at the opening and one at the closing. When looking at post by platform, Twitter represented 100 times the volume of any other platform. We then drilled down into specific tweets to see the actual contents.
In Adobe Social, you can go back into the history of Tweets. As an example, nobody expected Bob Costas to get pink eye, so no rules were available to monitor that when it happened. Using the historical data, they were able to set up a monitor for that and bring in the historical tweets.
Greg talked about the importance of Disqus. Disqus is a commenting engine that is easy to integrate into web sites. They have 9 billion comments and millions of commenter profiles. Often the comments made through Disqus are more meaningful than what you would see in Twitter. Of course, Adobe Social includes the ability to track Disqus as easily as Twitter and other data.
Tumblr is another platform that is important. They have 165m blogs and 72b posts. Tumblr content is repurposed and reused which accounts for 95% of all posts. These re-blogs can be important to monitor as they can show when something explodes in popularity. Tumblr has become the second most volume that Adobe sees.
Other platforms mentioned included Foursquare and VK. VK is the largest social platform in Eastern Europe.
I think the main point of this session is that Adobe Social gives you access to all the most important social content. Setting up a social program involves monitoring the right content at the right time. When you look to set up your own program, don’t just look at Twitter and Facebook. Many of the other social platforms are also tremendously important both for monitorIng and in which to participate.
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