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An in-depth look at how Facebook correlates with TV-viewing habits (April 2013)

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  • 1. An in-depth look at how Facebook correlates with TV-viewing Habits April 2013 Dan Benyamin, CEO CitizenNet Dr. Arshavir Blackwell, Chief Scientist CitizenNet We live in a world awash in data. From our digital pedometers to the words we write, the amount of data generated in two days is greater than all data collected from the dawn of time to 2003. Of course, in business, there has always been a desire to use data to inform decision-making. Few business sectors, however, have seen the same level of growth and adoption of data – especially social data – as publishing businesses. Content, and content delivery, are increasingly becoming a Web business. Netflix, some have argued, is now on pace to stream more than any cable TV network. Netflix has shown, even from its inception, that algorithms can choose content quite well for audiences, and has even applied that thinking to first-run projects such as House of Cards. Netflix of course has a myriad of signals to measure and assess the likelihood of a show being a hit; the ratings users have provided have famously spawned Netflix-sponsored competitions to improve on their own in-house algorithms. While these content predictions are fine for Netflix, is it possible to make content predictions more broadly? Social data is a new proxy for consumer behavior – even offline behavior such as TV tune-in Key Findings Facebook behavior is indeed correlated with TV viewing The most correlated metrics are the number of people who have liked a show’s Page and click-through rate (CTR) For each 3% increase in Page likes, there tends to be a 1% increase in TV viewership. What drives TV viewership is the right message to the right audience, at scale Understanding audiences is paramount to driving quality advertising
  • 2. 2 CitizenNet, April 2013 “Word at mouth can scale brand awareness” Today more than half a billion Tweets and 2.7 billion Facebook® likes are generated everyday. At CitizenNet, we are big believers in the power of social. Not only is the volume of social data huge, but in a world of device fragmentation, social identity will inevitably be more robust than cookies and other browser-based behavior. So what are some proof-points around the marriage of Social and TV? There certainly has been a lot of activity. Just this past February, Twitter acquired Bluefin Labs, who built a product that “marries the data from TV shows and commercials to audience reactions in social media. This means real-time feedback for marketers about the performance of media plans and creatives, something that hasn’t been available until now.” Facebook has also been active in the social TV landscape, with Kay Madati, the company’s head of entertainment strategy stating, “If the 90s were about browsing, if the new millennium was about search, today and into the future, we believe it’s about discovery. It’s structured around helping content producers surface their excellent content and leverage the idea that word-of-mouth at scale can raise brand awareness.” While interest in social platforms is certainly understandable, is this enough to justify a budget for a social media campaign? A recent study by Nielsen indeed confirms a correlation between Twitter volume and TV ratings, with an 8.5% increase in Twitter volume corresponding to approximately 1% increase in ratings for 18-34 consumers. So while there clearly is a relationship, this raised a lot of questions for our team. Specifically, what does the Twitter volume look like? Is it lots of conversation by few people? Is it related to content produced by the show? We set out to answer some of these questions, but this time, on Facebook.
  • 3. 3 CitizenNet, April 2013 While there are many different datasets available to a Facebook advertiser or Page administrator, we wanted to find something as broadly applicable as possible. Shows are marketed in a variety of ways, with differing budgets, so we stayed away from pure advertising metrics, and instead focused on Facebook Page Insights. These Insights account not only for ad-boosted impressions, but also such rich information as click traffic, “People Talking About This” (PTAT), and viral impressions. Working with our broadcast partners, we gathered insights for 77 different TV shows, across both broadcast and cable, from 2011 and 2012. Since season premieres are such highly scrutinized events, we decided to look at two weeks of data for each show, culminating on the premiere date. For each day, we utilized over twenty different metrics provided by Facebook’s Insights tool. We then performed a linear regression analysis to see if these metrics would correlate with Nielsen viewership for that episode. The result? The actions that people take on Facebook preceding a premiere are indicative of how many people tune-in to that show, as shown in Figure 1. But how? Aliquam dolor. Figure 1: A significant relationship exists between Facebook Page Insights and TV Viewership Our Methodology
  • 4. 4 CitizenNet, April 2013 Aliquam dolor. Further Analysis Of the dozens of metrics used to make the linear regression, which ones are the most significant? What are the important things marketers should watch out for? Our team performed Principal Component Analysis to find out how all these metrics fit together. The findings are illustrated in Figure 2. It turns out that many of the Facebook metrics are related to each other. For example, the number of people who are friends of people who like a Facebook Page is obviously related to the number of people who like the page, which is related to the total number of impressions of a page. So many metrics are statistically correlated with each other, in fact, that we can put all the Facebook Insights into just two categories and still largely preserve all the original information. In the figure, we see 20 different Facebook metrics, each radiating from the center of the diagram. The names of the metrics, such as “The number of people sharing stories about your Page” and “People who have seen any content associated with your Page”, are taken directly from Facebook. The two categories are represented as green and blue lines. The further out from the center, the more ‘influence’ that metric has on the category. So, for the green category the “Number of people who have engaged with your Page” is the greatest factor, whereas for the blue category it is the “The number of people who are friends with people who have liked your Page”. An important property of PCA is that the two categories themselves are uncorrelated; that is, where green has a high value, blue has a low value, and vice-versa. That means that what comprises the green metric are similar to each other, and dissimilar from the blue metrics. Looking closer at the green metric, in fact, we see things that are largely related to an action that someone takes: “clicked”, “liked”, etc. The blue metrics, however, are things largely associated with the number of people seeing your content: “impressions”, “seen”, “saw”. Figure 2: A plot of each much each metric contributes to an overall engagement measure (green), and an overall awareness measure (blue).
  • 5. 5 CitizenNet, April 2013 Aliquam dolor. Figure 3: Even using just two metrics shows a correlation Armed with this analysis, we see that there are really only two metrics publishers need to spend most of their time on, and it’s the ones that are the most basic: awareness and intent. You can’t expect to have large numbers of people tuning into a show without lots of people being aware of it – this is the blue metric. At the same time, lots of people who are aware but completely disinterested in what you have to offer does no good either – there has to be some level of engagement, and this is represented by the green line. To further show this relationship, we can use this as a guide to simplify your own analysis. Let’s use only a combination of: • The total number of people who have liked your Page • The total CTR of your content With these two values alone, we still see a correlation with TV viewership, as shown Figure 3. From this relationship, if we hold the total CTR at the average of 2%, we can estimate that for every 3% growth in Page likes, there tends to be a 1% increase in viewership. The Two Metrics that Matter the Most
  • 6. 6 CitizenNet, April 2013 The Social Sophomore Year It’s unfortunate that so many marketers are caught up in the myriad of measures and scores that come out of online advertising. As we have shown, many online metrics are correlated with each other, so not having a useful dependent variable makes some people come to the conclusion that social media metrics are a waste of time. By looking to see how online influences offline, we can see that successful marketers are just trying to appeal to people’s nature – regardless of the medium. It’s also unfortunate that so many marketers have focused purely on cost-efficiency and Facebook likes. As much as every industry needs to stretch their ad dollars, there’s no use in advertising to the wrong people. Our advice is to start building simple benchmarks of past performance, with an eye to overall CTR (not just paid, but organic as well), as well as cost efficiency. How do you drive up CTR? It’s through smart segmentation of your audience and experimentation with content. With CitizenNet’s analysis and predictive targeting, on top of Facebook’s rich channels, it’s not as hard as it seems. Take the Figure 4 for example. This is a collection of over one hundred different audience segments for a recent campaign done by CitizenNet. Figure 4: A CitizenNet Audience Map, which diagrams how different audiences have been segmented and respond to the ad campaign.
  • 7. 7 CitizenNet, April 2013 Aliquam dolor. Figure 5: A close-up of a particular section of the map. Every circle is an audience predicted, with the advertiser’s guidance, to engage with this content. Circles placed near each other are similar to each other in some regard. Once these audiences are targeted, the circles are colored to indicate their level of intent – with red higher performing than yellow. Notice how this map is ‘smooth’ – where you see red, the neighboring circles are red. Where there is underperforming yellow, there tends to be other yellow. Let’s focus on just one area of this map, shown in Figure 5. This ‘branch’ is of audiences targeted by their retailer interests. While most of these audiences actually showed tepid interest in the show, there is one group (marked with the arrow) that showed the most interest. It turns out that Urban Outfitters was the highest performing group here. Now imagine how valuable it would be to show to advertisers that, with positive proof, fans of Urban Outfitters are highly engaged in your content, all before the show even airs? Conclusion This brings us full circle with the original objective of this study. We have established that Facebook behavior is a great proxy for TV tune-in, and that marketers should focus on finding highly engaged audiences at scale. In addition, by segmenting those audiences to find the high engaging pockets, marketers can establish exactly which types of audiences are consuming what type of material, and can present those case studies to advertisers.
  • 8. About CitizenNet Inc CitizenNet, a Facebook® Preferred Marketing Developer, is ushering a new era of social data tools for marketing and advertising. Its predictive Audience Map enables brand marketers to better understand their core customers, uncover new (and sometimes surprising) potential customers, and optimize their campaigns to engage these audiences. CitizenNet technology lets our clients tap into a massive data set of the world's interests and opinions to automate all the steps of data-driven marketing: market analysis, segmentation, behavioral targeting, and runtime optimization, all based purely on the opinions of consumers. This information is then used to drive our automated Facebook advertising tools and our client’s broader marketing strategies. CitizenNet's technologies are covered under multiple patents. We're based in sunny Los Angeles and backed by world- class private investors. Facebook® is a registered trademark of Facebook, Inc. Contact us to learn what we can do for you! info@citizennet.com

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