Social media analytics tool Viralheat is launching a new product today: Social Trends bring fresh visualization features to Viralheat’s steadily expanding toolkit.
The startup, which launched in July 2009, provides affordable social media analytics from across multiple portals, from Twitter to YouTube, or your own social app. Viralheat’s goal to bring this data to the masses, by way of organized charts and graphs, is another instance of real-time data repurposing.
Viralheat’s new Social Trends provide graphically enticing ways to compare social data sets. Want to know which NFL team is getting the most tweets, or the social reach of a brand’s last campaign? The new charting tools conjoin access with answers, in a way usable by publishers, marketers, bloggers, activists and anyone else with a penchant for curiosity. The InfoGraphics feature provides an expansive library of graphics to choose from, offering custom content for far less than you’d expect to pay.
As fun as this sounds, Social Charts is still an analytics tool at its core. Through the new feature you’ll be able to measure two distinct aspects of sentiment, as demonstrated through its social media spread. Natural launguage and key cluster (sentence structure, grammar) analysis set out to extract the meaning of socially shared content, adding another layer of measurement to your comparative data sets. While sentiment is still difficult to measure accurately with algorithms, it’s important to note Viralheat’s steps in this direction.
Social Trends for Publishers Include:
Support to build unique real-time dashboards for any topic of interest to the publisher audience.
Tools to drive more traffic to the websites by allowing users to embed these charts on their blogs and share interesting stats on Twitter, Facebook and other social networks.
Present your readers with unique data that keeps them coming back, creates new real-estate for advertising, and ultimately drives more revenue.
Social Trends API Features Include:
Completely free access to developers, no need to be a paying customer of Viralheat
There will be 2 calls available.
List all Publicly Available Profiles
Get stats on those profiles. The stats will include everything that is available on Social Trends (a small subset of our current data set).
No API Key required.
Unlimited number of Calls, no restrictions or throttling
Includes the subset of analytics from Twitter, Facebook, Google buzz, Real-time web and viral video.
For Viralheat, the ability to provide broad access to previously exclusive data is a matter of scale. Owning its own stacks, Viralheat can process data and API calls more efficiently and in an affordable manner. The freedom has enabled Viralheat to sustain an interest in the aesthetics of its product, utilizing it as a way to connect this data to a wide range of users.
Given the real-time trends around data exchange networks, I wondered at Viralheat’s expectations around this explosion of data access. I had these questions for the team (answers below):
SA: What direction do you think this will take–could it eventually aid in the development of a new reputation-based system for assessing social media presence? Tie-ins with credit or reputation scores, beyond traditional recommendations?
Viralheat: Absolutely — social reputation is becoming increasingly more interesting to digital agencies and advertisers. Social media analytics services that integrate with reputation scores, such as Klout as we do in Viralheat, specialize in and offer actionable analytics that help agencies find highly influential voices and interact with them in near real-time.
However, reputation-systems are not perfect yet. There is still a good amount of work that needs to be done in this area. Processing the entire social graph of a user and his or her network is a very hard to do in real-time.
Also, the number of reputation factors is growing: the relative behaviors and influence of their followers, the user’s activity, the user’s influence score, a sophisticated understanding of their entire social graph, and more. All of these factors present their own challenges, and ultimately need to be combined and weighed to decide whether or not to engage a community member for the current or upcoming campaign.
This is a formidable task, buts as we see it, the first step is to start aggregating different pieces of information from all the different networks and provide a unified view of the user’s data. Eventually, we’d like to see a social score for every brand, product and person, and then combine it all to make something very similar to a q-score for all things social. [Reference via]
SA: What are your thoughts around the dangers of real-time analytics and publishers pushing quickly-reached conclusions too often? What will the consumer side of this look like, in terms of their need to filter the data hose, or do a little digging of their own for verification?
Viralheat: There’s probably always a risk that people will jump to the wrong conclusion whether their information is delivered in real-time or not. We see social trends as a way to surface the data that informs people’s thinking, rather than just surfacing the conclusions. If people are making the wrong conclusions or interpreting the information wrong, then the data is available completely for free for others to verify and cross-check.
In the context of publishing, traditional reporting is almost like snap shots in time. We want to offer tools that better reflect the conversation in real-time because we have all seen how fast the news and our world evolves. That does mean that the data and analytics could change soon after a story was written, but that also helps put the story in context, and provides the reader with a reason to dig deeper and really engage with the meme.
For example – we did an infographic about the launch of Google buzz, and it tracked everything from the very positive excitement around the initial launch, followed by a spike in negativity when security concerns soon followed. If you were to write a story or blog post at the time of launch it wouldn’t include information about the backlash driven by privacy concerns. But a widget alongside the story would indicate that something has changed since the story was first published. And the reader would likely want to click on a related article that gets them more up-to-date, accurate information about the situation. In this scenario, the reader is better informed, and less likely to reach a conclusion based on information that is out of date.
That’s why we feel so strongly about Social Trends – it democratizes data and analytics that have traditionally been prohibitively expensive for the average person. Getting that data to the average person can reduce the risk of misinformed conclusions.
Of course – as you mentioned – even if you have the data, you have to make sure you have the right data. There will always be human error as far as generating search terms that provide an accurate view of a given situation, and we have done several things in the a Viralheat system to help people understand how to create searches that get them the best information. But as with any research or analysis, cross-checking sources and fact-checking will always be a critical part of the process – that’s how you get a sense of the broader context.