Big Boulder: From Monologue to Dialogue with Disqus

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An interview with Daniel Ha and Ro Gupta with Disqus about how to engage using comments.

Big Boulder Panel at Disqus

Today Disqus is one of the most widely used discussion platforms on the web. Small blogs to large media brands use Disqus. Daniel Ha says Disqus likes to talk about how people don’t know their brand, but they are familiar with Disqus’s core discussion engine. When Disqus launched four years ago, they didn’t know anything about blogs, comments or publishers. Instead, Disqus wanted to tackle online communities to build more loyal audiences. Today audience development is equally as important as content.

Launch of Disqus 2012

The Disqus team wanted to analyze how they would launch Disqus if it were a new product in 2012: How would they build it?  Disqus knew their value was with their users; they knew 98% of people would never comment online, so they build a product for people who get value from lightweight engagement. “Comments” is very broadly defined. Over time, Disqus wants to move away from comments and move to how discussions power communities. Disqus knew the user experience and were able to produce Disqus 2012.

But they’re also providing hard metrics for publishers. With Disqus 2012, publishers saw a 41% increase in engagement across sites. They also have an incredible new feature in their real-time view of users on Disqus. You can view it at http://map.labs.disqus.com/

Social and Disqus

Daniel says, “Disqus has been described as a social commenting system, don’t necessarily agree with it.” Social adds an extra dimension that wasn’t available 10 years ago. Disqus fosters relationships and more topic-centric conversation. It’s not necessarily between friends, but rather connecting people on a common topic.  So yes, it’s social commenting, but it’s much deeper than that.

“Discussions have always part of the promise of the internet,” explained Daniel. He then gave the analogy of communities being like your favorite local bar.  Sure, you can anywhere to get cheap drinks and get hang out, but you have your favorite bar because you know that’s where you’re comfortable and you know the people there. Disqus’s communities attract experts and novices who want to come together and connect on a common theme.

Anonymity

As with any social platform, there’s a concern with identity and the intersection of level of engagement. Disqus has found there’s a middle ground of users who have an identity, though it’s not specific to their real identity. They provide high quality comments and many. Some level of identity choice is important in communities. It’s not about hiding something, but it allows a multi-faceted approach to expression. When there’s more freedom in the expression, Ro says, “Real insights can be drawn from the data.”

Fun fact about Ro Gupta; he coined the “Big Boulder” name. Cheers to that!

To end the session, Chris Moody also announced an easier way to filter comments from Disqus. More information will be available in the near future.

Big Boulder is the world’s first social data conference. Follow along at #BigBoulder, on the blog under Big Boulder, Big Boulder on Storify and on Gnip’s Facebook page.

Big Boulder: Measuring Engagement on Facebook with Sean Bruich

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An interview with Sean Bruich, head of measurement and Graham Mudd, head of measurement market development both at Facebook, about measuring engagement on Facebook.

Sean Bruich and Graham Mudd of Facebook

“Something’s wrong when the guys at Facebook are more dressed up than everyone else here,” – Chris Moody said before introducing Sean Bruich and Graham Mudd of Facebook.

The highly anticipated talk kicked off with the measurement issues marketers face online, specifically with Facebook. As Sean put, Facebook believes in solving measurement issues that every marketer is facing and allowing them to understand how online media can work for their businesses. As many marketers and brands attempt to brave the social media marketing ecosystem, it’s important to educate them on how this ecosystem can impact their business on a bottom-line level. Sean clearly put, it’s in everyone’s best interests to solve this problem and it’s very much at the forefront of Facebook’s plans. As a platform company, Facebook believes syndicating information can propel their business, however they want marketers to be able to engage with other platforms as well.

But how do companies attempt to navigate this ecosystem? Graham says it’s all about specialization. Facebook possesses a deep level of it that allows for truly deep measurement. Graham also states, “We can’t do it on our own.” Both Graham and Sean emphasized balancing innovation with standardization. Facebook wants and needs the help of other companies like Gnip to tell them what information they want to see and how they could use it better. But it’s not just about online. Marketers want to know about its offline effect:  how it incorporates into their business plan down the line and how it affects their bottom line.

Sean says traditional measurement hasn’t kept up with the technology that consumers are using. The big questions aren’t being answered. While developer communities are working towards that very quickly, there is still room for improvement on how ROI and marketing spend online fit into the marketing mix.  As in industry, we’re not answering the big questions that marketers need to know to justify spend and a presence online.

Standardization is the huge challenge. As Graham put, “Innovation is hard for the people who have to react to it.” It’s really hard to deviate from standards that brands have in place. While brands may want to jump into the deep end with online media, it’s difficult to take those chances on something that is so far removed from what they’re accustomed to. Some people who might benefit from innovation aren’t in a place to justify the changes.

So how does Facebook build this new set of standards? Investments. Facebook wants to invest in the people who can build new measurement platforms, and it’s not just about Facebook. They want cross-platform solutions for marketers to use to optimize and understand their consumers and online media. ”We do believe strongly in the platform; we believe strongly in the user side but also in the developer side,” said Sean. “The data is massive and there’s a lot of expectations around privacy, both user and marketer privacy. From a stability and access perspective we understand a lot, but we still need to hear from our users and marketers.”

While tough questions where asked, Graham says it’s not important to focus on why brands like GM pulled their Facebook advertising, but rather on the larger issue. Facebook believes it’s their responsibility to provide companies the insight and direction that actually has impact. Facebook isn’t the same as television and shouldn’t be approached with the same strategy. Whether or not that’s why GM pulled out, Facebook wouldn’t elaborate, but it’s a clear indication of the importance of measurement that companies at Big Boulder could potentially help to solve.

Facebook was tight lipped about product plans, but real time insights are important to FB. They want marketers to be able to see data as it happens. But there are challenges with this. From a measurement perspective, it’s not clear that marketers will even be able to take advantage of this data. As developers, Facebook wants to solve those problems too; how do we enable faster decision making through the tools they build? On a deeper level, Facebook wants to enable marketers to make decisions on a day-to-day basis, but it’s hard to have the level of intimate understanding of the data. If Facebook can get this feedback from it’s core marketers, they can better serve marketers and the end consumers.

Big Boulder is the world’s first social data conference. Follow along at #BigBoulder, on the blog under Big Boulder, Big Boulder on Storify and on Gnip’s Facebook page.

Big Boulder: Measuring Influence Online with Klout

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An interview with Klout’s Joe Fernandez and Matt Thomson about measuring influence online.

Joe Fernandez and Matt Thomson of Klout

Klout began as an idea in 2007 because Joe Fernandez had jaw surgery, and his mouth was wired shut for months. Unable to communicate on his own, Joe had to depend on social sites like Facebook and Twitter. As is only means to speak, Joe’s way of thinking was radically changed. His conversations with his friends made him think about influencers, and it was while he was wired shut that he starting building Klout. Joe wanted to find the answer to “how do we help every person understand their influence?” Four years into the business, Klout is tackling a very ambitious challenge to  understand conversations, relationships, and tie that back to influence. It’s an early start, but they are leaders in the space and hope to continue to grow and expand upon the idea of influence.

Measuring influence on the web can be a challenge. Joe says Klout strives to brand themselves correctly, which is why they chose their name. They wanted to push out the API for growth and not for monetization: to simple put the data out there so users can see it. It’s an easy entry point for consumers, albeit a bit counter intuitive for business plans. Though the data is often criticized for being incorrect or off, Joe says it’s a huge challenge to measure influence and they are striving to make it more measurable and more actionable. Klout is keeping up with ingesting every piece of data that is becoming available. While Klout is a leader in the space of influence, they’re still not satisfied with their product. They are consistently working toward better real world influence associated with online influence, and taking a first shot at addressing that. Matt Thomson gave the example of Google; In 2000 they had the best search engine available, but it was nowhere near where Google has taken search today. Matt says Klout’s algorithm will continue to change to incorporate the most relevant data becoming available.

Influence spans many topics and platforms online, so Klout must decide what matters more or less on the social web. They aim to include as many signals of influence as possible. Klout  chooses specific data to decide where influence lies and which signals trigger value in their platform. Their team of scientists works with more than 500 different variables to determine Klout scores. However Klout uses tools like ”Who is more influential” that asks a user to rate two friends and uses that against their algorithm to benchmark themselves and their data.

The real value of Klout lies in the context of influence: what someone is influential about, and how they get to a place to have influence. Joe emphasized that if you’re doing anything with customer service, targeting, or filtering, you know data can be a lot of noise. But a Klout score can help with decision making within a business. Klout is consumer-focused because they want something really digestible. Klout hopes marketers are using this, and on some level users are investing in the future of Klout, and where it can go. Klout ranks topics in the background as well, and hopes to bring that feature to the forefront. Topics are critical, and the second biggest investment for Klout after influential people.  Understanding topical analysis, is difficult because often there is so little context. It’s a big challenge, but Klout hopes to evolve to incorporate topics into their product.

Klout’s business model right now is very consumer-centric. One way users are benefiting from Klout is through their perks program. Klout Perks are exclusive products or experiences that you earn based on your influence. Influencers have earned sweet Perks like laptops and airline tickets. Chevy is a great example of this; they came to Klout looking to reach out to influencers about cars. The influencers were given a Chevy Volt for a weekend with gas money to burn, and in turn these influencers generated social proof on Chevy. While these influencers weren’t paid to do this, they felt empowered to talk about the Chevy Volt. And it worked: 180 million impressions on the Chevy volt were produced, and advertisers were happy.

Joe had a great personal example when he tweeted about a poor experience with Delta. Because Delta was using a tool that incorporated Klout into their API, they were able to immediately contact Joe and remedy the complaint. Joe says this is exactly what Klout is working toward: improving customer experience. Every interaction between a company and a consumer is an opportunity for a story to be told through social. If you have the most passionate people talking about your brand in good ways, it’s super valuable.

Big Boulder is the world’s first social data conference. Follow along at #BigBoulder, on the blog under Big Boulder, Big Boulder on Storify and on Gnip’s Facebook page.

Big Boulder: Data Science at LinkedIn

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An interview with LinkedIn data scientist, Yael Garten, and LinkedIn business strategist, Jennifer Weedn, about data science at LinkedIn and the applications of LinkedIn data.

Yael Garten & Jennifer Weedn of LinkedIn

LinkedIn is the largest professional network out there where users can find compelling products, look for a new job, and connect with other professionals. Founded in 2003, LinkedIn gets 2 new sign ups per second, 4 billion people searches annually, and supports international professionals in more languages everyday. When it comes down to information, LinkedIn is  ”Disney World for data nerds” as Chris Moody put it. And with data like “percent users who are decision makers” (42%!!!), LinkedIn has a jackpot at their fingertips. Amazing data sets of education level, company information, and number of companies worked for are just some of the pieces one can pull from LinkedIn. For example: What happens when someone senior leaves a company? Where do they go? This is all data that LinkedIn has a wealth of.

Yael Garten delved into the different areas of information that LinkedIn gathers and how they use it. As Yael put, normalized data is information. And what do we do with information? We gather knowledge. Within LinkedIn, “products” are defined as people, pages, groups, jobs, and more. At LinkedIn, they have a saying “If you can’t meaure it, you can’t fix it,” and this is how LinkedIn operates. To understand the data is to understand how users engage with LinkedIn’s services and products and how they can make products better for users. According to Yael, every decision is data driven, and with good reason.

To define a data scientist is to incorporate many different skill sets:

Data Scientist = curiosity + intuition+ data gathering + standardization + statistics + modeling + visualization + communication

Data Scientists use LinkedIn data in 3 ways:

  1. Products: LinkedIn’s newest product is “Skills”. Launched last year, it is a dictionary that allows for users to search by professional skills and qualifications to find new employees, see what’s current, and more. For example, the skill “Hadoop” has grown 43% year over year. Someone searching for “Hadoop” would also come across related skills. This new sections allows for really collaborative filtering, and huge insights for LinkedIn users and the company as a whole.
  2. Insights: When can look at growing and shrinking industries with LinkedIn. Even the government has used LinkedIn data for speeches on growing job industries. Data  around growing and shrinking in a geographic area can be found and used in practical ways. A great example of insights derived from this data: Where did people in the finance industry go after the 2008 financial crisis? A surprising answer, but they just redistributed into other financial institutions.
  3. Wisdom: With the wealth of data, it can be used to drive business. What is the value of an action that a user takes on the site? What early behavior on the site is predictive of future engagement? What is the value of a user? Does mobile usage impact site engagement? Mobile usage can cause actions that impact web engagement. LinkedIn uses this to understand implications for the product and the business, because wisdom is the ultimate goal of the data science team, and it is an art.

Jennifer Yang Weedn of LinkedIn’s Business Development launched into brand engagement and how brands are finding a presence on LinkedIn. Their sweet spot for brands is with B2B marketers. Jennifer says there are 5 steps to engagement on LinkedIn:

  1. Establish a presence on LinkedIn, on a community page. A brand’s company page is their record on LinkedIn.
  2. Attract followers organically or by paid sources
  3. Have a conversation with followers using targeting status updates.  Brands can send and target specific updates to certain types of followers who would most be interested in them.
  4. Drive amplification of engagement by followers sharing a brand’s updates and posts.
  5. Analyze follower base, and slice and dice the data to fit the brands’ needs.

There are 2 million plus companies on LinkedIn, and many have seen success on the site. Phillips, for example, increased engagement by 106% using targeted status updates. Jennifer says 70% of users follow or would follow companies on LinkedIn. Users follow companies for different reasons as well; some looking for job info, but more are following because they want insights from companies and content to help them make better professional decisions. From a data point of view: 60% of users want industry insights, 53% are looking for company news, and 43% are looking for products and services.

Brands can also have a presence in Groups. There are about one million groups on LinkedIn, and brands play a role in many. They can either be mentioned in the context of the conversations in groups, or they can sponsor groups on LinkedIn. GE was able to use groups to leverage their resources and become thought leaders in the space. By posting an infographic about how people should navigate their career path, they positioned themselves as thought leaders and could engage their customers better.

Data science at LinkedIn is taken very seriously, and with all of its uses, it should be. The valuable insights and wisdom gained from data are just beginning to show their uses, with many more possibilities on the rise.

Big Boulder is the world’s first social data conference. Follow along at #BigBoulder, on the blog under Big Boulder, Big Boulder on Storify and on Gnip’s Facebook page.

Big Boulder: Blogs, Comments, Forums and Rich Social Data Gestures

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A panel discussion on forums, comments and blogs and other rich social data gestures with Ro Gupta from Disqus, Mark O’Sullivan from Vanilla, Mike Preuss from FormSpring and Martin Remy from Automattic, and moderated by Nicole Glaros from TechStars.

Social Gestures Panel at Big Boulder

The definition of community can vary widely across platforms, but is there a real definition of community? At Disqus, they like to think of communities as a continuum. First come comments then conversations on twitter, blogs, and other platforms. Once the conversation is developed, it gives way to a community. Communities are about recognition and repetition, and forums allow for these communities to develop. Commenting systems are a jumping point for communities. Mark O’Sullivan of Vanilla coined them “community training wheels” because they are a good starting point for community forums. They enforce familiarity and often lead to offline communities as well. Mike Preuss explained what draws people into communities: FOMO. As social beings, the “fear of missing out” or FOMO drives communities. When 45% of daily users on FormSpring are creating content and engaging others, users feel the need to contribute to the conversation. About 74% of visitors to Disqus will return everyday or every other day. ”When you think you’re missing out on something,” Mike says, that defines a community.

Developing a community is a huge task, but the bigger task is engaging users. At Vanilla, they have a full range of social gestures because not everyone will be able to contribute to every topic. But by using “light weight” gestures such as “likes” or “smiles” in the case of FormSpring, content creators can receive feedback and give readers some way to signal back. It also helps to identify good and bad content, influencers and contributors in the community and drive moderation from these. There’s a tremendous push toward allowing anyone the chance to become a content creator. A recent and fascinating case of this is Pinterest; “pinning” photos is creating content and allows users to express who they are.

At Disqus, they focus on reaction tools, according to Ro Gupta. Ro says they want to be able to reengage after the fact, and this includes cross-pollinating on other platforms like Facebook and Twitter. Engagement can be measured by “daily active users.”  The 90:9:1 rule is something that Disqus deems true for their platform. 90% of users are passive clickers, 9% help curate content, and 1% create the most content and drive discussions. However, there is a middle ground because of lightweight gestures that encourage users to engage on a smaller scale. According to Ro, about 35% of users contribute solid participation in the form of  lightweight gestures. In the case of Vanilla, Mark said some users were hesitant to allow lightweight contributions, but over time, users found it encouraged new content and lowered barriers to engagement.

Lightweight interactions are relatively new, but do they really affect product roadmaps? The answer is always yes. Martin of Automattic says WordPress isn’t adding social for the sake of “adding social,” but rather because the feedback from lightweight interactions is motivation for content creators. WordPress is adding more tools to enable this as well. As Mike of FormSpring explains, “we want to reward good user behavior,” by releasing new features for users. Lightweight actions help them sort what’s actually relevant to communities, so FormSpring came out with a feature to sort by most popular and by language.

When it comes to platforms, each company agreed that it is extremely important to carry content across platforms. As Martin said, it’s important for people to publicize their content outside of their blogs. Users want to share on tumble, twitter, and elsewhere. Tumblr actually doubled engagement within WordPress. “Viralizing the content,” Ro of Disqus says, draws in more users. 50% of Disqus’ users connect with another social platform and 10-12% of comments are shared on Twitter. And while you’re always competing for eyeballs online, no single platform can own a conversation about something. When a user is particularly interested in a topic, it will naturally cross platforms. Facebook has even helped discussions grow through “Facebook comments”. They tend to increase the pie for everyone and open the eyes of new users.

One of the biggest concerns of content creators is engagement versus reach: which is more important? Both matter to different creators, and but it’s important to consider who is asking. For example, a blog like TechCrunch has more influence and reach than a personal blog, but both reach and engagement are valuable within different communities.

Big Boulder is the world’s first social data conference. Follow along at #BigBoulder, on the blog under Big Boulder, Big Boulder on Storify and on Gnip’s Facebook page.