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Editor's Notes

• #6: 1.5 B people around the globe are online with 600,000 of them on social media. Social media is big and ubiquitous. And lest we think this is an activity which is unique to our nieces and nephews… it’s happening across all demographics and age bands with the 35+ group being one of the fastest growing demographics, in fact. From choosing a hotel on the other end the planet, through to getting input on which doctors to go so and politicians to vote for, consumers are turning to social media at unprecedented rates to shape their decisions. Consumers are putting less stock in what companies say about themselves, and asking their ‘friends’ and networks what they think before they act, and before they buy. And that rather public evaluation of our brands has the ability to impact our brand health more than it ever has. So, if the real brand sentiment regarding our companies is “out there,” how do we get our arms around the data and tap into it? The answers are in the data….
• #14: And while social data is one very powerful source of information which a company can leverage, SAS is unique in its ability to help customers integrate their data with other existing data sources so you can make sense of your business overall. The social data from the chart here is pooled together and organized in accordance with your taxonomy and next you can layer in your existing customer service data for example, or call centre data (both key drivers of brand health). Next, you can take the existing information (structured or unstructured) and add in third party information such as client satisfaction and brand research. Doing so, helps you make sense of not only the social sentiment, but how that fairs in conjunction with all of your other business intelligence. This in turn allows you to understand correlations in your business and the leading indicators of brand health.
• #20: And then those topics which are relevant to your business are then made available through one means – called a SAS phrase cloud. This is one way to discover new topics and themes of discussion, including those which you may not have previously thought to monitor. SAS’ text mining technology searches for not just words that appear over and over, but also words that also appear frequently in conjunction with one another. For example, by themselves, the words “short” and “sale” are perhaps not noteworthy, but because they appear together so often, the system identifies this as a meaningful phrase. In one example in our work with an American bank, we noticed the frequency of occurrence of the phrase “move your money.” This phase helped them reveal a consumer movement which advocated that you should “move your money” to smaller, local banks instead of the large corporations undergoing bailouts. And in the case of this institution they were able to take that thread, drill down into the mediums where that was being talked about and identify the individual influeners who started that movement.
• #22: And that same sentiment can be looked at both at an individual medium level (ie the wall street journal) but als at an aggregate level based on blogs, discussion forums or twitter as an example. In this example we can see that the proportion of positive discussion is fairly consistent across media type, but that bloggers are the primary drivers of negative commentary.
• #24: SAS SMA collects and processes years of historical content, which allows you to instantly contextualize results by comparing them to the same time last year. By leveraging the traditional power of SAS you are able to use statistics to define relevant business thresholds that make sense, or predefined business rules. This helps you determine whether movement is significant and should be investigated further, or whether it is likely to be just a blip on the radar.
• #29: So let’s do a check to understand how influential the WSJ is to our brand overall. Looking at Twitter, we can see that it is the third most influential corporate entity – and though the WSJ handle has about the same number of followers as Fox News, its influence is about 8 times greater than that of Fox News.
• #30: And drilling all the way down to the individual level you can see that an individual named Marc Parent has not only a significant amount of followers, but also influence.
• #32: And often knowing the sentiment over time is not enough… bankers want to understand WHERE the sentiment is positive and negative so that it becomes easier to act. In this example, which is from a US bank, we looked at sentiment for the Wall Street Journal and other key banking sources over time.SAS allows you to compare two timeframes side by side to understand how corporate reputation fared on these sites in early 2009 vs. early 2010. We can see how during the height of the banking crisis, most sites had above average negativity towards our brand….but a year later, unfavorable discussion had abated on nearly all sites.