Justin Wyman is Vice President of Business Development at Socialgist (www.socialgist.com), and will be speaking at LTI18. Socialgist is on a mission to help companies access the world’s vast and invaluable pool of social media data. Justin shared his thoughts with Philippe Wacker about the need to access, explore, and analyze this raw information to uncover valuable information.
Philippe Wacker, Secretary General, LT-Innovate: Socialgist has been providing data access via API for 15+ years, what has changed over that time frame?
Justin Wyman: There have been three major changes: data has become more complex, more global, and has more uses than anyone could have predicted. Social media today looks nothing like it did 15 years ago. We are talking about hundreds of millions of data points from millions of sources. Just accessing the raw data isn’t enough anymore because it’s so nuanced that you need to have it sifted and parsed to make any real use of it.
Social media is also a truly global phenomenon. Everyone uses a few key sites, but you have many regionally dominant platforms. Even without different apps, each culture has its own social media nuances, and you have to account for that when analyzing data. Finally, you have more uses and use cases when you look at social data. Practically any research question can be at least informed by one of these data sets.
Philippe Wacker: Can’t people just aggregate social content on their own?
Justin Wyman: Sometimes you can, but it’s time-consuming — I’d compare it to renting an office. Do you want to have to find your own source of water? Electricity? Of course not, but gathering those things is not in your wheelhouse and your energy is best used on other things. The insights from social media data today is right up there with water and power when it comes to keeping a business functioning. You need it, but just like you don’t want to run your own pipes and your own power plant, you shouldn’t have to find social media data relevant to your requirements.
Social data is a basic necessity and should be delivered to a business already mined and sifted so that analytics systems can do their work. If you have a truly huge business and want full vertical integration you can do your own social media mining, but it’s probably not worth it.
Philippe Wacker: How do you determine which data matters?
Justing Wyman: Here’s a tip to solve 90% of your problems all at once: work backwards from the question you’re trying to answer. Are you looking for a leg-up on customer engagement loops? Find the data points that indicate when interest peaks and bottoms out. Hoping to prevent fraud? Mine data about vulnerable points in your transaction process.
Once you’ve isolated most of the data relevant to your search, you may find multiple data access points that might help you really dig deep. In this case, it’s easier to validate an approach to make sure you’re looking at each access point from the right perspective and seeking out the right data before considering things like the data’s origin and delivery mechanism.
Philippe Wacker: How does Socialgist solve the “content avalanche” problem?
Justin Wyman: 100% percent of our goal at Socialgist is to create access points that solve your business needs most efficiently. It’s like asking how Tesla plans to make cars more energy efficient. They do it by making electric cars, and we do our job by taking a huge data avalanche and sifting it into neat piles so you know what information is where. We churn through the mountains of available social media data and arrange it however our clients dictate: by origin, topic, size, complexity. It’s only an avalanche when it’s a disorganized mess that crushes you. If falls neatly into useful stacks, it’s called a windfall.
Philippe Wacker: What are the access options available from Socialgist?
Justin Wyman: Socialgist offers a variety of ways to help our clients get the data they need the way they need it. The option you choose should depend on your technical specs and the issue you’re trying to solve. Sometimes you want a REST API because of the easy access to history, sometimes you’ll prefer streaming access. REST APIs are popular right now because clients can filter their data with search terms and get all uses of those terms from their selected sources at a requested frequency, while a streaming feed shows you everything as it arises in real time. Both are useful, but it’s up to you to decide when an option is right for your use case.
Philippe Wacker: Where is the analytics space going to next?
Justin Wyman: More data sets will be analyzed together for better insight. You’ll see bundles combining web, social, and Internet of Things (IoT) data in various combinations to see how different ideas from various areas of the online world weave together and influence one another. We’ll see, for example, how social media usage directly influences reliance on particular integrated IoT devices and vice versa. Eventually, the divide between different genres of data will erode and we’ll deal with data as a single entity.
With the rise of machine learning, the ability to analyze data is only getting better. That’s why we’ll be able to look at information much more quickly and organize it more precisely, which is great because there will be so much more useful data coming in. Our whole world is online, and IoT alone is going to load systems worldwide up with more data than we can conceive of. Better machine learning and heuristics are necessary just to keep up with the flood of information we’re expecting to see, and the companies that are best positioned to thrive in this digital tomorrow are the ones who make the best use of all this information. To do that you need the best, smoothest access to well-organized data.
