Measuring Impact on Facebook

An interview with Daniel Slotwiner, the Head of Measurement Solutions Group for Facebook, on measuring impact on Facebook. 

Daniel Slotwinter, Head of Measurement at Facebook

“There are a lot of misconceptions about Facebook and data,” Chris Moody eloquently opened the interview with Daniel Slotwiner, Head of Measurement Solutions Group for Facebook. For Daniel’s team, their job is to build tools and methods of analysis to highlight the value of Facebook’s media business. But as Daniel explained, it’s not a win for a brand to measure a brand campaign by the CTR it gets. Instead, he emphasized the importance of working with an advertiser who is defining objectives and setting the right measurement program alongside. The Measurement Solutions Group not only tries to build the tools the industry can use, but also educate and work with them to get the most out of the ecosystem. The hope is that the ecosystem will be self-sufficient.

Partnerships

Last year Facebook announced their partnership with Datalogix, initially for measurement. However, with Datalogix’s comprehensive roster of US households, Facebook realized the impact of the information they could provide to advertisers. Datalogix and Facebook have been able to append data of frequent shoppers with consumer purchase decisions. This has aided in analyzing the impact of Facebook in driving offline sales. With more than 80 campaigns executed with these tools, Facebook can see which segments are responding to the advertising and make smarter campaign. At the end of the day, the value of this data is just to calculate ROI, but rather the scale allows for in-depth analysis and huge learnings for not only Facebook, but also advertisers.

Scale 

If the unique advantage of Twitter is that everything is public, Facebook’s advantage is knowing who is saying what. The uniqueness of this data is two fold: scale and concept of identity (demographically and geographically).  If advertisers can understand the value of this data, they have a fantastic starting point.

It’s hard to argue Facebook isn’t doing a good job of scaling their users. “Obviously we love new users,” David said, and it’s still a huge focus for Facebook, as it expands internationally. And they’re prioritizing serving everyone in the world, especially through segmenting. When it comes to the level of use, Facebook has found light users are more receptive to advertising in comparison to heavy users. As  advertisers, understanding this user segmentation can help shape campaigns and execution on the social network. Facebook is intent building these insight back into the advertising systems to help advertisers make better decisions.

Value in Multi-Point Attribution

The world of influencing consumers is only getting more complex. In one sense it’s because there’s so many touch points. Facebook is focused on making sure the measurement systems are keeping pace with the world, but this is virtually impossible. There are a lot of approaches, but Facebook is pretty focused on multi-touch attribution systems to measure. One way they can look into this is through mobile.

Because almost all users access Facebook using mobile, they get to observe a lot and measure they information around mobile usage. This is information Facebook eventually wants to share with the industry. The platform allows for see the different paths to purchases because Facebook has so much visibility into the touch points. Facebook is in a excellent position to observe how many devices people have and how content is distributed across them.

At the end of the day, there’s a lot of data that can be utilized from Facebook. However, Daniel urges the proper use cases of the data. Research, for example is a huge opportunity given the quality of the data. Daniel cautions against the use of the data for its prediction. While a brand may use the discussion online to respond to an emergency or to participate in the conversation, it’s not clear if they should use it as an objective to drive more sales online.

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

Data Story: Jaime Settle on How Social Networks Affect Political Mobilization

This week we have a data story with Dr. Jaime Settle, a Professor at William & Mary, who studies how social networks affect how we think, feel and behave politically. Her work has been published in the Proceedings of the National Academy of Sciences, the Journal of Politics, Political Research Quarterly, and American Politics Research. We’re thrilled to have Professor Settle speaking at Big Boulder on a panel about research happening in the academic world on social data. 

In a recent Nature publication, “A 61-million-person experiment in social influence and political mobilization,” Settle and her co-authors looked at how political mobilization messages on Facebook during the 2010 US congressional elections affected real-world behavior.

Jaime Settle, William & Mary

1. How was your team able to get access to Facebook data?

Appropriately enough, the connection was made through the power of social networks. The collaboration was formed when I was a graduate student at University of California, San Diego. My advisor, James Fowler, was introduced to Cameron Marlow, the head of data science research at Facebook, through a mutual friend. This friend thought that James and Cameron had a similar vision for the power of online social network data to help us understand fundamental social processes that structure human behavior. Cameron and his team of scientists at Facebook are interested in many of the same underlying questions that academic social scientists want to study, and the collaboration is an effective way to tackle those tough research problems.

2. Do you think your findings would have been fundamentally different if you had scraped data?

What access to the universe of data provides is the ability to detect very small influences that are important because of the massive scale at which they operate. For example, the paper we published in Nature shows how behavior can spread through a social network and that our behavior is affected by the influences our friends receive. The amplitude of each individual influence is small, but the overall effect is massive because of the hundreds of friends we have and the millions of active Facebook users. These small effects would have been impossible to identify without “Big Data” even though the processes at work would be present.  We are also able to make broader generalizations about our results due to the access we have, whereas conclusions must be more circumscribed from research using scraped data because of the multitude of ways in which a small, potentially non-random sample of users may not be representative of the larger population of users on a site.

3. Your personal research has focused on how people behaved differently in battleground states? What were your findings?

I find that people living in battleground, or politically competitive, states are more likely to discuss politics online, and are more likely to do so emotionally than are people who live in less competitive states. These effects appear only in the most intense part of the campaign season, in the weeks leading up to the campaign. I also show that this increased propensity to talk about politics on Facebook explains part of the effect we observe that a higher proportion of people living in battleground states clicked on the “I Voted” button that Facebook displayed on election day in 2008.

4. What do you think social data can tell us about how people are influenced when it comes to politics?

The pace at which we are confirming processes we’ve observed in the offline world—as well as learning new things–about social influence from studies using online social data is really incredible. We are demonstrating that people are more influenced by people with whom they have closer “real world” relationships, and we’re identifying the most influential people in networks. We’re figuring out why some memes are more likely to spread than others, and thus what kind of memes are likely to have the largest influence on our attitudes. We’re able to characterize people’s political ideologies based on their patterns of behavior on social media, and will be able to look at the differences in influence from those we agree with versus those we don’t.

5. What are you interested in researching next?

I’m very interested in the process of how contention and disagreement affect people’s attitudes toward—and participation in—the political realm. My research moving forward is looking at particularly controversial policy debates, such as that over the Affordable Care Act, to see how the context in which people talk about the policy affects their rhetoric and attitudes toward it. I’m also interested in iterated online discussions instead of single expressions of attitudes in status messages.

Thanks to Jaime for participating in the interview! You can check out her fellow Big Boulder panelist’s data story with Sherry Emery of UIC, studying social data and smoking cessation. Click more to see previous data stories! 

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Big Boulder 2013

Big Boulder’s back for 2013 and better than ever.

The leaders in social data: Facebook, Twitter, Tumblr, Foursquare, Automattic, Disqus and many more are descending on Boulder again this summer to talk about the future of their platforms. Last year was a huge success and the expectations this year are even higher. We have a line-up that will deliver!

Headshots for Big Boulder

We’ll go deep into Asia and Latin America with speakers from China, Brazil and Japan, including the CEO of LINE, one of the fastest growing social networks on the planet. We’ll hear about non-traditional applications of Social Data with discussions on Finance, Government, Academic Research and Data Science. And to help us make sense of it all, we’ll have industry analysts discussing their views of the future. See the agenda and speakers pages for all the details.

In addition to all the great topics covered in the sessions, we’ve left plenty of time for networking with others in Social Data, including sunset cocktails with views of the Flatirons, a bicycle pub crawl, and since this is Boulder after all, morning yoga and hiking.

Big Boulder is an invite-only event for the leaders in the social data ecosystem. Space is filling up quickly so if you’re still thinking about it, sign up now before we hit capacity. Interested in coming but haven’t been invited? First check out our blog post about social data vs. social media. If you’re all about social data, email bre@gnip.com for information.

Big Boulder: Measuring Engagement on Facebook with Sean Bruich

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 BoulderBig Boulder on Storify and on Gnip’s Facebook page.

Are Facebook Users More Optimistic than Twitter Users?

New Year’s Eve gives us a sense of closure on the past and an opportunity to make new dreams. With the emergence of social media, we can now see these reflections and resolutions transpire in realtime. As we observed the posts, comments, and tweets related to the New Year, we saw the typical expressions on Facebook and Twitter of best wishes for the coming year and pithy observations about the past year. What we didn’t expect was that users of the two popular social media sites would have different outlooks on the world.

As we enter 2012, Facebook users are more optimistic than Twitter users.

You’re probably wondering how we can say that. Well, we looked at all of the public posts on Facebook and Tweets on Twitter that contained “Happy New Year.” For all of those posts and Tweets, we compared the use of positive words such as “better” and “good” to the use of negative words such as “worse” and “bad.” We found that Tweets with positive words appeared 8 times more frequently than Tweets with negative words. You might be thinking a ratio of 8 to 1 is pretty optimistic…

It may be, but posts on Facebook had a ratio of 40 to 1–such a huge difference lead us to speculate that Facebook is a more optimistic place than Twitter.

Interesting stuff. Could be a variety of reasons for the difference, from the mix of users on each service to the fact that Facebook is used to communicate with friends, while Twitter is user to broadcast to followers. We’ll leave the speculation up to you.

Social Media Knows As Much About The Holidays As Santa Does

The holidays are an exciting time at Gnip…and not just because our CEO loves bringing random bottles of excellent Scotch to the office. Around this time of year we get some visibility into the incredible ways our retail and consumer product clients are using social data. In fact, Mashable recently highlighted a study by Mr. Youth (a marketing firm) with an incredible stat that helps prove how valuable social data in holiday shopping truly is:

“66% of respondents who bought something on Black Friday did so as a direct result of social media interactions with friends and family.”

While that stat speaks to the impact social media has upon us as individuals, think more broadly about how powerful it is to analyze that data in aggregate, in real-time. Companies are leveraging data from WordPress blogs, Twitter mentions, Facebook likes and multiple other sources to inform critical realtime decisions for inventory management and operational planning, sales and marketing planning, revenue forecasting, and many others.

Example Scenario for Using Social Data: It’s holiday time, 2011. Your company begins to aggregate ‘mentions’ of a new product from Twitter, Facebook, WordPress blogs in realtime. You take that data and analyze it for # of mentions about the new product, geography of posts (where available), demographic information within user profiles (what keywords are most consistent within Twitter user profiles that mentioned your product?), etc.

You spread that data among multiple divisions, providing additional forecast, regional buying pattern, and customer habit data. Your teams use that to:

  1. Manage supply chain: Redirect inventory to areas with highest potential sales and (depending on how far out you are) use as a data point in the S&OP system for manufacturing forecasts to keep ahead of the holiday demand.
  2. Target marketing spend: Use regional buying patterns and customer habit data to inform what demographic you are, and aren’t, hitting. Do you need to reposition your marketing plan?
  3. Incorporate product feedback: Are there consistent reasons why people are buying your product – or why they aren’t? Information on quality, packaging, price, etc will be incredibly valuable for future products.
  4. Calibrate investor expectations: Inform your IR team of potential positive/negative performance feedback to give them running room ahead of any announcements.

Those are just some of the more common use cases we’re seeing. But new opportunities are popping up on a daily basis. We spotted this gem in a recent WSJ article about finding a parking space during crazy shopping times:

Bud Kleppe, a real-estate agent in St. Paul, Minn., watches Mall of America’s Twitter feed for parking updates. (The mall sends them out under the hash tag #moaparking.)

Imagine collecting data from update systems like this and using it measure parking turnover across prime shopping days. Now, overlay the turnover of spots in specific sections against a map of stores and you have some interesting potential for data on economic performance and forecasting. When incorporated with other traditional retail data and compared on a store-to-store basis, you’ve built a unique and realtime analysis tool.

You’re only limited by your imagination in how you can apply social media data to you business. The more software developers, corporations, and people use social media, and the more things they use it for (like parking updates!), the greater the possible use cases for analysis of that data and the more valuable it becomes.

Gnip Cagefight #2: Pumpkin Pie vs. Pecan Pie

Thanksgiving is a time for family gatherings, turkey with all the delicious fixings, football, and let’s not forget, pie! If your family is anything like mine, multiple pie flavors are required to satisfy the differing palates and strong opinions. So we wondered, which pies are people discussing for the holiday? What better way to celebrate and answer that question than with a Gnip Cagefight.

Welcome to the Battle of the Pies!

For those of you that have been in a pie eating contest or had a pie in the face, you know this one will be a fight all the way down to the very last crumb. In one corner (well actually it is the Gnip Octagon so can you really have corners, oh well) we have The Traditionalist, pumpkin pie and in the opposite corner, The New Comer, pecan pie. Without further ado, Ladies and Gentleman, Let’s Get Ready to Rumble, wait wrong sport. Let’s Fight!

Six Social Media Sources, Two Words, One Winner . . . And the Winner Is . . .

 

 Source  Pumpkin Pie  Pecan Pie  Winning Ratio
Pumpkin Pie to Pecan Pie
Twitter X 4:1
Facebook X 5:1
Google+ X 6:1
Newsgator X 3:1
WordPress X 5:1
WordPress Comments X 2:1
Overall +6 Winner! +0 :(

 

We looked at one week’s worth of data across six of the top social media sources and determined that pumpkin pie “takes the cake” (so to speak) across every source.

In this case, it is interesting to point out that in sources like Twitter, Facebook, Google+ and WordPress we see higher winning ratios, while sources that tend to have higher latency such as Newsgator and WordPress Comments were a little more even. Is this because, on further consideration, pecan pie sounds pretty good? Or is it that everyone will have to have two pies and, with pecan as the traditional second, it is highly discussed?

Top Pie Recipes

Even though pumpkin pie was our clear winner, we thought it would be fun to share a few of the most popular holiday pie recipes by social media source:

  1. Twitter – Cook du Jour Gluten-Free Pumpkin Pie and Pecan Pie Video Recipe from joyofcooking.com
  2. Facebook – Ben Starr’s Pumpkin Bourbon Pecan Pie Recipe
  3. Newsgator – BlogHer’s Pumpkin Pecan Roulade with Orange Mascarpone Cream Pie Recipe
  4. WordPress and WordPress Comments – Chocolate Bourbon Pecan Pie from allrecipes.com

Non-Traditional Thanksgiving Pies

Another interesting fact that came out of this Cagefight was the counts of non-traditional Thanksgiving pies that were mentioned across the social media sources we surveyed. Though we rarely find these useful for communicating numerical values effectively, you can’t not have a pie chart in this post.

Happy Thanksgiving!

Delivering 30 Billion Social Media Activities Monthly . . . and Counting

I’m excited to announce that, as of the end of October, Gnip is delivering over 30 billion paid social media activities per month to our customers. This is the largest number of paid social media activities that have ever been distributed in a 30 day period.Over the past year, we’ve seen extraordinary growth in the number of paid social media activities we deliver. At the start of 2011, Gnip was delivering 300 million activities per month.  By May, that number was up to 3 billion activities per month.  And in October, we delivered 30 billion activities.  In essence, we’ve been growing by a factor of 10 every 5 months.  At this rate, we’ll be delivering 300 billion activities per month by March of next year

Cool numbers, but what’s driving this growth?

We’re seeing three key areas that are driving this number. First, we’re signing on new customers at an increasing rate, as more and more companies are seeing the possibilities in social media data. Second, we’re seeing increased interest in our Twitter firehose products. From hedge funds using social data to drive trading strategies to business intelligence companies layering social data onto their existing structured data sources, interest in volume products from Twitter is consistently increasing.  And finally, we’re seeing a marked increase in the number of customers using multiple sources to enrich their product capabilities.  From boards and forums to YouTube and Facebook, our customers are seeing the potential in the many other social data we offer.

So, 300 billion per month by March? It’s a big number, but the way things are going, I’ll take the over.

Google+ Now Available from Gnip

Gnip is excited to announce the addition of Google+ to its repertoire of social data sources. Built on top of the Google+ Search API, Gnip’s stream allows its customers to consume realtime social media data from Google’s fast-growing social networking service. Using Gnip’s stream, customers can poll Google+ for public posts and comments matching the terms and phrases relevant to their business and client needs.

Google+ is an emerging player in the social networking space that is a great pairing with the Twitter, Facebook, and other microblog content currently offered by Gnip. If you are looking for volume, Google+ quickly became the third largest social networking platform within a week of its public launch and some are projecting it to emerge as the world’s second largest social network within the next twelve months. Looking to consume content from social network influencers? Google+ is where they are! (even former Facebook President Sean Parker says so).

By working with Gnip along with a stream of Google+ data (and the availability of an abundance of other social data sources), you’ll have access to a normalized data format, unwound URLs, and data deduplication. Existing Gnip customers can seamlessly add Google+ to their Gnip Data Collectors (all you need is a Google API Key). New to Gnip? Let us help you design the right solution for your social data needs, contact sales@gnip.com.

Get your Hack On! Gnip Helps Power an App Developed at the 2011 TechCrunch Disrupt Hackathon

Over 500 individuals recently gathered in New York City for this year’s TechCrunch Disrupt Hackathon. This annual event, fueled by pizza, beer, and Red Bull, features teams of die-hard techies that spend 20 hours, many without sleep (hence the Red Bull), developing and coding the next big idea. Participants compete in a lightning round of pitches in front of a panel of judges with the winners receiving an opportunity to pitch on the main stage at the TechCrunch Disrupt Conference in front of more than 1,000 venture capitalists and industry insiders.

We are excited that one of the apps that was developed at the 2011 Hackathon was powered by Gnip data! We love it when our customers find new and creative ways to use the data we provide.

Edward Kim (@edwkim) and Eric Lubow (@elubow) from SimpleReach (@SimpleReach), which provides next generation social advertising for brands, put a team together to develop LinkCurrent, an app powered by Gnip data and designed to measure the current and future social value of a specific URL. When fully developed, the LinkCurrent app will provide the user with a realtime dashboard illustrating various measures of a URL’s worth — featuring an overall social score, statistics on the Klout Scores of people who have Tweeted the URL, how many times the URL has been Liked on Facebook and posted on Twitter, and geo-location information to provide insight into the content’s reach. Call it influence-scoring for web content.

The hackathon team also included Russ Bradberry (@devdazed) and Carlos Zendejas (@CLZen), also of SimpleReach, Jeff Boulet (@properslang) of EastMedia/Boxcar (@eastmedia/@boxcar), Ryan Witt (@onecreativenerd) of Opani (@TheOpanis), and Michael Nutt (@michaeln3) of Movable Ink (@movableink)– Congratulations to everyone who participated! You created an amazing app in less than 20 hours and developed a creative new use for Gnip data. I highly encourage all of you to check it out: www.linkcurrent.co

Have fun and creative way you have used data delivered by Gnip? We would love to hear about it and you could be featured in our next blog. Drop us an email or give us a call at 888.777.7405.