Officially announcing that mBlast is now a Plugged In to Gnip partner (which we’ve just done in this sentence) is especially exciting because of a particular kind of analysis they specialize in – called resonance tracking – that they’ll be able to do on this announcement!
As a leader in the social media analytics space that is helping companies understand the trajectory of social conversations, it makes sense to include mBLAST among Gnip’s growing group of partners. Companies who are Plugged In are driving innovation in the social media ecosystem through their products and emphasis on incorporating multiple social media sources into their analysis. One of the ways mBLAST is defining social media analytics is through their development of resonance tracking, a variation on influencer tracking with some distinctly different capabilities. Effective resonance tracking necessitates the monitoring of multiple different platforms, which piqued our interest on the topic.
Wouldn’t we all like to stop a rumor in it’s tracks — or at least have a good idea of who started it? Knowing how a story perpetuates across the social sphere and who is responsible for influencing those moves is a valuable tool for companies and brands. If you can pinpoint which of your fans, or critics for that matter, is talking about you the loudest, with the most influence, and in which channels, you can directly address the message.
mBLAST has measured resonance within the analytics applied to social, blog and media data tracked in their mPACT platform for literally millions of stories. All of this tracking and measurement has lead to some pretty interesting observations which mBLAST will be releasing in a whitepaper in September titled, “Social Intelligence: The Role of Resonance”. The more we learned about resonance tracking and the many ways it can be applied to everyday customer service, marketing, and public relations scenario, the more we couldn’t wait to spread the word on just how relevant a tool it is. So we put together a short summary of their resonance tracking whitepaper to give you a sneak peek — focusing on how resonance differs from more traditional influencer tracking and why it is a key part of social media analytics.
So, how does resonance differ from traditional influencer tracking? A couple of ways, but probably the most significant is that it allows companies to identify which individuals are the most influential in a specific channel for a specific story and how that story is jumping from platform to platform. For example, a story about a CPG brand starts on a blog post and then hops from the blog post to Twitter and then to Facebook, etc. Perhaps the conversation is false or the product contents are reflected inaccurately. Whatever the case may be, the CPG company likely wants to engage with the people, and in the channels, where it will do the most to shape the conversation and protect the company’s reputation. Both can be done using resonance tracking.
We’re psyched to have mBLAST in Plugged In and look forward to working together. And we’ll be excited to track the resonance on this announcement!
If resonance tracking gets you excited or you want to know more, check out this webinar on the topic on September 12.
Data Stories is about telling cool stories about the amazing ways that social data is used. This week we’re interviewing Stefan Papp of Blab
, a Gnip customer, about their predictive analytics that are able to help customers understand the directions conversations online are headed in 24, 48, and 72 hour time frames. I absolutely loved this concept and wanted to understand more about how it worked.
1. Why did Blab decided to take a different approach instead of doing social media monitoring?
Typical social media monitoring tools use keyword-based searches – you put in your keyword and the tools return all historical results matching that keyword. The catch is that you will only find the insights you are looking for. Our approach is to listen to the entire conversation as it organically evolves, allowing you to discover much more of what your users are discussing — including the unexpected insights you probably would not have thought to search for. Finding those non-obvious but vibrant discussions gives companies whole new opportunities to engage with their target audiences.
2. What makes social data a good source in predicting behavior?
When you monitor social data you have a unique opportunity to listen to the unfiltered personal voices of millions of users. This offers insight into not just what is trending in social but what people are really thinking and feeling; their beliefs and true opinions. Standard behavioral prediction methods use things like focus groups and polls. But these approaches have long been known to produce skewed data – both consciously and subconsciously, users tend to tailor their responses to what they think the “best” response should be. Social data has none of this user bias and as a result is an excellent source of raw unfiltered intelligence.
3. How do you think Blab fits into the trend of real-time marketing?
The challenge that real-time marketing presents is creating on-topic content and getting that content out the door before the conversation is old news. Blab not only monitors current conversations in real time but predicts which of those conversations are going to be hot 72 hours from now. This takes the reaction out of real-time marketing and for the first time gives control to the brand. Blabenables you to put relevant content in front of an engaged audience at the right time – before a conversation has grown so big that your voice can’t be heard. You can also strike a chord by engaging your audience in those non-obvious conversations happening right now that you would not have thought to join.
4. What’s some surprising findings companies have found when using Blab?
One of the major insights that companies have gained from using our Predictive Social Intelligence engine is how conversations evolve online. So many companies only think about Facebook and Twitter when they think social, but social is so much more than that. Blab enables you to watch a conversation evolve across the entire spectrum of social networks. You can follow a conversation that begins with a YouTube post, which then drives a larger conversation on Twitter, and ends up being predicted to explode on Tumblr 72 hours from now. Without a holistic view like this companies can be led to believe that a conversation has ended when in fact it continues vibrantly on another untracked social platform.
Another interesting finding is that our clients get an unadulterated view of their standing in social discourse. One client, a global technology concern, was surprised and chagrined to find that while there was lively discussion around their competitors, there was no discussion at all about them in their area of expertise. As humbling as that was, it became a call to action and fueled enthusiasm for engaging more effectively. Blab helped that company discover a negative and use that knowledge to improve their position.
5. Clearly, Blab has huge implications when it comes to crisis communications. One of the things that has amazed me about social media is that you don’t need a huge following to start a fuss about a brand. How does Blab separate the wheat from the chaff when it comes to determining conversations that might spike?
We use two unique methods to identify truly relevant conversations and to make accurate predictions on when a conversation will spike. First, we throw NLP out the window and use a proprietary contextual classification approach to find the conversations that are related to a given topic. Rather than filtering out words like “got” we let our engine tell us if a term or phrase should be included. And guess what? There is a thriving “got” conversation among people who are passionate about “Game of Thrones.” We embrace acronyms, slang, abbreviations and sarcasm in a language agnostic manner (from Klingon to emoticon). The result is that we give you a picture of the whole conversation, unfiltered yet relevant. The second unique method is our proprietary approach to determining which conversations will spike or cool down. As conversations ebb and flow on the social canvas they establish patterns of historical facts. We’ve discovered that regardless of the topic, these patterns tend to repeat themselves. So while there are a huge number of them, the universe of conversation patterns is not infinite. When we see a familiar pattern we can predict, and often with high confidence, how a conversation will progress up to 72 hours into the future.
Taken together, Blab gives brands the ability to find potentially troubling conversations as they emerge; to determine if action is important by predicting which conversation is likely to take off; to engage that conversation or take other remedial action; and to know if the engagement is having an impact by watching to see if the prediction of growth turns into a prediction of decline for the troubling conversation.