Many people consider the National Football League’s choice of Madonna to headline the 2012 Super Bowl Halftime Show as, well, curious. It’s been more than 20 years since the artist released her landmark albums “Like A Virgin,” “True Blue” and “Like a Prayer.” Of course, a lot of music fans think artists from the 80s are timeless. Just the same, we thought we’d explore which acts sports fans talk about most in social media to see if there might have been a better fit.

Audience analysis is a key, unique aspect of Networked Insights social media analytics. In this case, we created an audience based on the people talking about the Super Bowl across all social channels. By analyzing their comments, we were able to uncover the musical acts they most discussed. We also looked at conversations around Madonna to see how well sports fans received the news of her appearance.

Using our proprietary real-time analytics and topic discovery engine, we learned that the most desired halftime acts are performers famous for rocking the stadium, especially bands with a front man. The Foo Fighters were the unanimous top choice, with Hank Williams Jr., Tom Petty and Peter Frampton also mentioned.

Super Bowl fans were less than kind toward the Material Girl, however. Many feel Madonna is past her prime, and showcasing her is a desperate attempt to appeal to an older female audience. Of the posts we uncovered, the measurable sentiment was 41 percent negative in nature, while only 3 percent positive.

To avoid such blowback, Networked Insights uses Content Sync to help networks, brands and agencies leverage real-time data to better understand their target audiences. Staying in sync with your audience allows you to uncover trends and insights that can improve marketing decisions. Content Sync helps eliminate guesswork or gut-based decisions on product placement and celebrity endorsement by allowing your audience to drive decision making.

Had the NFL tapped its audience for insight into who should perform at halftime, the result would have been a halftime show that increased social buzz and viewership – in other words, a can’t miss, must-watch Super Bowl experience aligned with the desires of its target audience.

Download our Media Optimization Guide >>
Make Every Ad Perform Like a Super Bowl Ad

The largest advertising spend for most brands usually focuses on TV. Companies expend tremendous effort and risk large chunks of their marketing budget to make sure their on-air advertising buys deliver the most reach for the dollar. Networks, meanwhile, are staking their reputation, and putting viewer patience on the line, every time they greenlight a new show.
This process is risky for both advertisers and networks because the current decision-cycle model (pre-informing, optimizing and measuring) relies on traditional metrics (like gross rating points) and studies (such as focus groups) that are expensive, time consuming and not always unbiased. In short, TV placement decisions haven’t been made in real time.

With the emergence of social media we now have access to the world’s largest focus group. Through real-time audience analysis, marketers and content creators can understand the audience around a TV show before it premieres. This data provides insights into audience members’ state of mind, discovers their interests, and measures their sentiments regarding various topics. All this knowledge allows marketers to make smarter advertising decisions and reduce the risk associated with traditional media buying during the upfront purchasing process.

Last May, TV analysts at Networked Insights helped several clients leverage real-time data in both buying and selling negotiations. We started the process by using synonyms, or look-a-likes, to the proposed TV shows to understand what it was about a show’s content that the clients liked, how involved they were with that content, and, most importantly, who was engaging with that content. Because this data was collected in real time, our clients had access to information the same day the new shows were officially announced. This data allowed media planners and buyers to instantly know which new shows to avoid and which ones would guarantee them the largest reach with their desired audiences. Sellers were able to understand which shows had more social capital, allowing them to sell more dayparts on nontraditional shows.

For example, last year, using our Audience Sync for brand, trend and audience discovery, we predicted that “The Playboy Club” and “Allen Gregory” would fail and that “New Girl” and “Revenge” were on the road to success. As a result, our planner and buyer clients achieved more reach in fall 2011 with their same spend, and our sellers had higher profit margins.

With the next upfront season rapidly approaching, and the economic downturn still a factor, the need for more efficient media spending – and higher sales – has never been greater. Real-time analytics, Audience Sync and Networked Insights are here to help innovators gain a competitive edge and improve performance during their next negotiation process.

Download our Media Optimization Guide >>
Make Every Ad Perform Like a Super Bowl Ad

Now that we have the most boring sports weekend of 2012 out of the way (come on, who could stay awake for the Australian Open, and the Pro Bowl – really?), it’s time to crank up the Super Bowl hype. Advertisers are certainly obliging. Some are already previewing the game spots that they’ll be spending $3 million to air.

Feeling left out of the action because you can’t spring for that kind of scratch? Not to worry. Just a couple of clicks will take you to Networked Insights’ Media Optimization Guide, Super Bowl XLVI Edition, a treasure chest of ideas that can help you make every ad perform like a Super Bowl ad

Topics the guide covers include using real-time social data to understand your audiences and deliver them relevant content. We reveal how you can reach NFL fans without an NFL budget, and how you can overcome a media lockout. The guide also has tips on leveraging social data to understand a TV show’s audience before it airs. And, it takes a look at how you can improve your TV marketing with real-time audience intelligence.

The guide has some entertaining information on two aspects of the big event – the halftime show and the program that NBC airs immediately after the game – that are stories unto themselves. All I’ll say is with what we’ve been hearing ahead of Madonna’s appearance, I can’t wait for the social chatter as her performance grows nearer and once she hits the stage (prediction: it isn’t going to be all bouquets). And, if you’re doubting that The Voice is going to keep football fans tuned in postgame, you might be surprised by who’ll be rooting for Team Adam, Team Blake, Team Cee Lo and Team Christina.

Finally, throughout the guide you’ll find examples of how Networked Insights tools make all these insights possible – Audience Sync, to discover who is talking about your product or service across the entire social web; Content Sync, which taps real-time data to better understand target audiences; and Media Sync, which enables networks, brands and agencies to leverage real-time data to uncover where their audience is consuming media. Together, they provide a playbook for you to unleash Super Bowl-power advertising.

Download our media optimization guide >>
Make Every Ad Perform Like a Super Bowl Ad

Last night we saw over 700k Tweets that had mentioned the Golden Globes, but this was just a drop in the hat for the overall social conversation related to these awards.

Using Networked Insights’s advanced topic discover engine we are to organically take everyone who discussed or commented on the Golden Globes last night and collect all the posts, tweets, and comments they’ve made over the last month and cluster them in order to understand in real-time what kind of topics, products, and content is interesting to fans of the Golden Globes. Listed below are the top themes and products for this audience as well as their demographic make-up:

Golden Globes Thematic Analysis:

• 62% of the conversation was about who won/the winners
• 48% of the conversation was about the Red Carpet
• 12% were about the upsets – Viola Davis not winning best actress, Damien Lewis losing to Kelsey Grammer
• 9% of the conversation was about Ricky Gervais being the host
• 4% of the conversation was related to Madonna

Ricky Gervais Thematic Analysis:

• Last night Gervais was set-up in a position where there was very little middle-ground – he would either succeed at being entertaining, or fail to be funny. Leading up to the Golden Globes 24% of his conversation was about people being excited to watch him host.
• His opening monologue was only 4% of the conversation, but was very well received with +20% positive sentiment
• However after that the pacing of the show and the direction made many feel like he was absent from the stage for long periods of time and that when he was on he wasn’t nearly tossing out as many jokes as he should have been (32%)
• 9% of his conversation was about his jokes with Madonna
• His Kim Kardashian joke (2%) and his Jodie Foster/Beaver  joke (5%) were also fan favorites

Red Carpet Analysis

Top 5 brands:

1. Prada – 42% (Zooey Deschanel’s dress represented 20% of the overall Prada-related conversation)
2. Dior – 22% (Charlize Theron contributed the largest share of the discussion at 34%, but Milla Kunis was close at 29%)
3. Gucci – 15% (Jessica Alba [23%] and Selma Hayek [36%] contributed the largest shares to the overall brand conversation)
4. Vera Wang – 4% (Sofia Vergara was discussed 55% of Vera Wang’s brand conversations while Naya Rivera was only discussed 36% of the time)
5. Marchesa – 3% (Lea Michele’s outfit represented 62% of the overall brand conversation)

What Received the Most Attention on the Red Carpet:

1. The Dresses – 71%
2. The Hair-dos – 25%
3. The Tuxes and Suits – 4%

Top 10 Celebrities – Share of Voice

1. Madonna – 10.5% (While Madonna did win an award for best original song – the social conversation around her was largely not in her favor. Many commenters were first off surprised by her victory (32%), then how inconsistent her accent was between being British or not (21%), how long-winded her conversation was (12%), and finally her tiff with fellow nominee Elton John (42%)
2. Meryl Streep – 5.3% (While Meryl did clinch an award for herself her night was up and down between forgetting to wear her glasses (22%), to talking too long (9%), and getting censored for her language (15%))
3. George Clooney – 5.1% (People enjoyed the fact that he made a lewd joke (39%), but questioned why Meryl was bleeped, and he was ok)
4. Octavia Spencer – 4.7% (“Pretty in pink” was used to describe Octavia several times (12%), but when she won the award for her role in The Help the online conversation exploded in celebration for her (72%))
5. Michelle Williams – 3.8% (while not everyone was a fan of My Week with Marilyn (14%), people were still mostly congratulated her for winning (57%))
6. Angelina Jolie – 3.4% (Angelina was the only celebrity in the top 10 that did not win, or was even nominated for an award, people just loved gossiping about her, Brad (22%), and what she wore (60%))
7. Claire Danes – 3.2% (Won for her role in Homeland – which lately has been one of the most positively discussed shows in social media. Claire also received additional attention for this being her 5^th Golden Globe win (28%))
8. Jessica Lange – 2.9% (Won for her role in American Horror Story, a show she’s no longer a part of (23%), but she was she was considered the highlight by many (10%))
9. Kate Winslet – 2.7% (Won for her role in Mildred Pierce, and the response was largely congratulatory (65%))
10. And a special award goes to Matt Leblanc (2.6%) for winning an award for playing “Matt Leblanc”. In fact after it was announced that he won “Yay Joey” started trending on Twitter

Millions of people use keyword searches every day to find what they’re looking for online. New cars, Italian restaurants, definitions of unfamiliar words, competitors’ views on various issues. But when it comes to social media, keyword searches can send you off into the wilderness if you’re using traditional monitoring tools to discover conversations and trends.

By definition, the intent of search is to uncover the best responses to a query. A search engine retrieves hundreds of thousands of posts that match the word or phrase programmed into the query. It attempts to rank them in order of relevance. Its goal is to put the post most likely to be the one you’re looking for at the top of the list.

But what if the goal is to analyze millions of posts to identify trends that can inform marketing decisions or uncover insights that can reveal business opportunities? With social data analysis, more data points are sometimes much better than a few. In these cases, search will undermine your efforts as explored in the recently published Search vs Text Classification Report by Networked Insights. The first 20, or even 200, posts might be great matches. But the last 20 or 200 might not match at all.

Worse yet, search cannot contemplate the context of how words and phrases are used in relationship to one another. It simply identifies whether or not that word or phrase is present. In social media data analysis for marketing purposes, this is a huge limitation.

Text classification is an alternative to search that may be more appropriate for social media data analysis. Text classification is the task of assigning predefined categories to free-text documents. It can provide conceptual views of document collections and has important applications in the real world.

In contrast to search, text classification uses machine-learning algorithms to learn from a set of examples how to separate posts into topics. If an algorithm, or program, is presented with examples of how a human would separate posts based on topic, it can learn to mimic that person’s process on new, previously unseen posts. One major advantage of this approach is that the program can scale up to perform its process on millions of documents. As a result, classification offers the potential to produce a dataset in which all of the posts are relevant to the topics being analyzed. The last 20 are as valuable to the analysis as the first 20.

So stop searching. Instead, start asking how real-time data can support your existing decision-making processes and then use classification techniques to cut through the noise and sharpen your social analysis.

Interested in learning more? Download the Search vs Text Classification Report today!

You have a killer piece of original content that starts rippling out from its source. The two things social lift analysis can tell you are how far and how fast those ripples move. If the content ripples 900 times, but that takes 10 years, you won’t see much benefit. If it ripples 900 times in 28 days, that can be really valuable information. Those rapid ripples are an indicator of what’s happening to the things that you’re doing. They help identify valuable, highly efficient venues in which to place your brand.

Celebrities can be one good source of social lift. In using celebrities, it’s not just about the number of followers or fans someone has. That’s just a point in time.

Instead, you want to know how likely that number is to grow. The best celebrities for delivering social lift are those whose following has increased and will continue to do so over a period of time. In thinking about whether to select a celebrity, a key indicator of his or her potential is, when other types of content feature this person, how far does it reach and how fast does it get there?

Another source of social lift is TV shows. There are two types that exist today, those that are currently on the air and those that are in development. For the ones on the air today, you have to determine what happens when certain types of content, celebrities and advertising appear on that show. What does the overall social lift look like?

In considering shows that are yet to air, you should assess the overall reach of the show concept by finding corollaries to it. What is the overall reach of this type of content? What is the overall reach of celebrities that appear in those shows?

Want to learn more? Read our point of view: “Social Lift: How to make your media plan go further.” Then let’s talk!

Let’s say you’re an auto insurance company. You want to target micro-segments where people think about buying auto insurance. We know that people buy auto insurance when they buy a car. But where else can we find people who intend to purchase insurance?

Using social data, we have discovered that people tend to think about auto insurance when their kids are going to prom. They think about it then because they’re worried about whether they have enough insurance. A risk mitigation scenario is taking place that you can target with your media plan.

Another “decision intersection” might be when men have had a mid-life crisis and they’ve just bought a big, fast car. If you can learn where those men congregate in the social media arena and how you can place your media in those areas, you can improve the efficiency of your media buys. To answer that, you need to discover where men go to have those conversations and then place your media there. And that media could be in the form of an advertisement or in the form of paid content.

By using social data analysis, including topic discovery, you’re likely to have a much more efficient media plan.

To read about more clever ways to strategically plan media, check out our FREE eBook on the 5 new tricks for media planning.

A small relatively un-noticed posting on the Facebook blog gave marketers who use social media one of the greatest gifts I have seen in marketing in quite a while.

Take a look at the original posting below …

Improving Facebook Page Insights
by Facebook Pages on Tuesday, November 23, 2010 at 7:48pm

Facebook Pages are a great way for admins to learn about their audience and view Facebook Insights about people connected to your Page. We are launching a new feature for all Facebook Page owners and Facebook Platform developers that will provide additional metrics around your Page content. All Page admins will now be able to see per post impression counts for each story posted on your Page after June 25, 2010. Per post impressions will be collected in raw format and all impressions will be counted toward the impression total. Unique impressions are not available at this time.

The true meaning of this post is Facebook has given us the ability to track the impression count of an individual piece of content posted on your Facebook Page. This was previously only allowed for Pages with more than 10,000 fans/likes.

This is significant because now you can measure impressions across all your “earned” social media such as your Facebook Page postings, YouTube Views, Twitter, Blog Impressions etc. And if you can officially measure impression data across all of these forms of media then you can attach a CPM to that number and define the Media Equivalent Value (MEV) you can get by participating in Social Media.

Some clever firms saw this and immediately launched Social Media dashboards that can derive a MEV for you such as SocialEye by Overdrive Interactive and SocialSenseFB by Networked Insights. Which means you can now truly measure your progress daily, weekly, monthly in social media. And better than that you can report back to your executive team how much media value you were able to drive for your company by using social media, giving you a nice tidy way sum up all your media value backout the cost of your social media program and show an ROI.

Marketers have been typically looking for a tool to measure ROI in social media but because the metrics were so different (fan, followers, views of videos etc) it was impossible to “normalize” those metrics to create a single measurable metric which was why it was so hard to measure the ROI in social media. Ultimately all marketers will be heading to a place where we can monitor spending across all forms of media – Paid, Earned and Owned in order to know where to place our very next dollar of media spending. Furthermore I think you will see this type of media analysis emerge more this year. So little did we know in the quiet of an evening in November just 2 days before Thanksgiving, Facebook gave marketers something really to be thankful for on Thanksgiving!

Today there is no competitive advantage between Coca Cola and Pepsi when it comes to planning media. They both use the same data, whether it’s Nielsen data, transaction data or other research they’ve commissioned.

Social insights or social analysis around television audiences is the obvious next big competitive advantage. It is the next layer that you’ll put on top of your Nielsen data to compliment your decision making!

How would you use it? Here are four examples.

The first way is to identify a different segment watching TV. Traditional target ratings suggest that “Two and a Half Men” skews mostly male when, in fact, it skews mostly female. We know this to be true because of content fans create about the show online — content we’ve identified through topic discovery. Such insight allows media planners to think about planning and targeting that audience in a completely different way. Perhaps that show then becomes a better fit for your brand or perhaps there is a different 30-second spot you might want to run because you know that the audience is really mostly female.

The second is to identify the actual vs. estimated size of an audience. Nielsen data, for example, might suggest that the “Tonight Show” has 3 million viewers. In fact, we may see 5 million viewers engage around the show during a specific time of the year or when certain topics are discussed or guests appear on a given episode. Based on that topic discovery process, we now know that if you buy a rating point on that show, you’re actually getting 5 million viewers instead of 3 million. That’s a huge arbitrage efficiency play, and at Networked Insights we love to make those kinds of finds to recommend to our clients.

The third example is when we take a company’s media plan and show you all the earned media value you received from it. We can show you the “social lift” you got from buying that media. For instance, with this year’s Super Bowl, we found the “extra efficiencies” that earned media got for media planners (see “The Lambeau Leap Into Social Lift”).

Final example: “Gossip Girl” is given a 0.9 rating by Nielsen. Technically, no show with a 0.9 rating should still be on TV. Eight years ago, a 7.0 or a 9.0 would stay on TV. Now a 4.5 or a 5.5 will stay on TV, but a 0.9 would never stay on TV. However, “Gossip Girl” is a very successful show in social media with Millennial viewers, so it has stuck around. Through the use of social data analysis, you can find these types of “diamonds in the rough” before they become big hits.

The counterargument can happen as well. For example, “Dancing with the Stars” is thought to have a huge following when, in reality, we know it does not. An opportunity exists to optimize there to ensure you are getting the most efficient media buy possible for your brand.

To read about more clever ways to strategically plan media, check out our FREE eBook on the 5 new tricks for media planning.

The Super Bowl might be the world’s greatest match of football titans with one of the world’s largest audiences, topping out at around 111 million tuning in for the game. But only slightly half of the audience are there to watch the actual football game according to a new report from Lightspeed Research who surveyed over 2000 Americans online and found that nearly as many viewers were interested in the advertising as they were in the football.

The kingpin who started the advertising revolution on the Super Bowl was none other than Apple – with their “1984″ ad, which launched the Macintosh computer. They reportedly got $150 million dollars in media value from that one Super Bowl spot because of the commentary on ABC, CBS, NBC, BBC and others. So, for our third year running, we set out on a quest to declare a winner of the Super Bowl from a different perspective: the brand that got the most media value (what we term Social Lift) from their advertising on the Super Bowl.

We are defining this Social Lift as the increase in buzz from a baseline we took before the Super Bowl (Jan 1 to Feb 4) compared to Super Bowl and directly after the Super Bowl from Feb 6 and 7. And the other dimension we measured was the efficiency of spend, which is the total media value divided by the estimated spend on the ads. The numbers were averaged to create an index. So a “2″ is twice as efficient in creating social lift per dollar spent as the average ad in Super Bowl 2011.

And this year’s winner is … Teleflora! This is their third “Insighty” in as many years.

• Like any good mix of paid, earned, and owned assets — which is the secret to maximizing efficiency of media spend — Teleflora placed only one ad, but leveraged social conversation around that to achieve the highest efficiency of spend.

• In contrast, Chrysler had the highest social lift — 377% compared to Teleflora’s lift of 178% — but they had to spend a lot more to get it, which still places them a respectable ninth in the efficiency field. In these days of carefully watched budgets and increasing marketing expectations, efficiency is the name of the game.

• Sentiment is always a factor, and Teleflora did well with 79% of comments positive. The negative 7% focused mostly on the edgy remark about the “nice rack” of the engineer’s girlfriend.

• Best sentiment: Volkswagen had the highest positive sentiment at 89%. They also ranked third in both social lift and efficiency.

• Bailout fallout: Chrysler had the highest negative sentiment of the top 10 — tied with Best Buy at 19%. Most of that focused on griping about the auto bailout and the cost of a Super Bowl ad.

Download the full report: A Lambeau Leap Into Social Lift.

The article highlights a major shift in the advertising world where paid, earned, and owned assets are increasingly being coordinated to maximize synergies between the three. This is exactly the area we have been working in over the past year, helping clients determine the minimal effective media spend that is going to achieve the maximum impact in the market with no waste in dollars. This translates into efficiencies of 10% and more in their media spend by creating social lift, the buzz about your ad and brand that adds earned value to your media buys.

Even a crude awareness and approach to manipulating these three key areas of marketing will yield results: toss a hand grenade in a pond and you’ll catch some fish, right? But leveraging social data can turn this kind of marketing into a science by directing the sequencing of paid, earned, and owned initiatives. Do you start with a contest launched with an online video (owned) and then follow up with advertising? Or do you launch with a conversation-starting paid ad, ride the earned lift… and then introduce owned assets into that conversation?

In addition, social data can help find those places where the audience gathers outside of a “premium” ad market like the Super Bowl ad (eg, those buys on YouTube and ESPN mobile that Volkswagen is making, mentioned in the Ad Age article). That allows a brand to reach that premium audience at a non-premium price. In this case, they are smart, repeat impressions building on the TV ad. But it also enables a brand to “steal the cheese” by grabbing that Super Bowl audience without buying a Super Bowl ad.

The huge cost of a Super Bowl ad highlights the need to create these media buying efficiencies. But the same dynamics can be brought to bear on buys throughout the year — and media planners and buyers can benefit from these savings year round. The rapidly approaching upfront season is a key time to use social data for big efficiencies.

If you’d like to get our take on how Super Bowl advertisers fared this year, come back to this blog on Tuesday, after the game. This will be our third annual report on Super Bowl advertising (which makes us veterans in the explosive new world of social media insights). This year’s post-game report will reveal which brands got the most social lift and ROI based on their spend.

In the meantime… Go, Pack, Go!

1. Buy shows with high social engagement and low TRPs. Nielsen sets the value based on their metrics. Why not buy based on metrics from social media data? Since the TRPs don’t recognize the value of a highly engaged audience — but you do, or should — you can get that value for a bargain.
2. Benefit from the “social lift” that occurs when a highly engaged audience talks about a show online. Your brand can get talked about in the online conversation about a show simply because you advertise on that show. But a smart branded integration play can set that social lift on fire. Get clever and knit your brand into the show — and into the hearts of its most passionate viewers.
3. Get repeat impressions against your targets through multiple channels by understanding where the conversation is taking place. The biggest opportunity after the TV ad is in the digital space. We have pulled insights from  conversation on a number of sites where fans of a particular show, in a specific category, and using a brand name come to discuss. We typically advise on the best sites to place digital ads that will reinforce the TV ads or branded integrations viewers just saw on the show.

If you’d like to know more, sign up for our webinar “The Walking Dead: A Media Buying Guide for Brands.” On 1/19/2011, We’ll give in-depth examples, many drawn from AMC’s new hit show, to illustrate the points above.

Here are five ways that social data gives you an edge:

1. Finds “Diamonds in the Rough”
   Let’s start with the essential value. We look for shows with low Target Rating Points (TRPs), according to Nielsen,  and high social engagement. We call those shows Diamonds in the Rough, because Nielsen sets the price according to their TRPs. And we find value in shows featuring large amounts of social conversation. We measure engagement to track real-time fan interest. Engagement offers depth because each post represents a viewer reacting directly to a show’s content. In the delta between Nielsen’s low pricing of a show and our high valuation, there are tremendous efficiencies to be gained in a buy.
2. Finds promising new shows even before they air
   Nielsen provides ratings for shows after they air. Social conversation can take off well before the first episode airs. And that points the way to a smart buy before the market has had a chance to put a high price on it.
3. Hyper-segments audiences to maneuver around media lockouts
   When a brand is locked out of advertising around an event — for instance, when a competitor is the primary sponsor of a major sporting event — social data can find that same premium audience at non-premium prices. Where are those desirable fans gathering before the game, or at halftime, or after? Social conversation points the way.
4. Coordinates paid, earned, and owned assets for optimum efficiency
   How do you make a $100 million dollar media spend act like $110 million? Or $150 million? Place your spend so that the ads are a catalyst to leverage owned assets and drive earned engagement on top of the spend. When your media spend is optimized in this way, we see “social lift.” For instance, social conversation can help find and shape opportunities for smart, creative branded integration plays. That’s how those efficiencies of 10% or more really take off.
5. Provides a new source of data your competition doesn’t have
   If everyone is dealt the same hand, it’s hard to win. We track 450 million users and over 2 billion interactions per month. Insights from that social conversation are quickly becoming the key differentiators to help brands and agencies get ahead.

If you’d like to know more, sign up for our webinar “The Walking Dead: A Media Buying Guide for Brands.” On 1/19/2011, I’ll give in-depth examples, many drawn from AMC’s new hit show, to illustrate the points above.

Vuvuzelas are one of the top trending topics on Twitter (and has so early on established itself as the foremost Internet meme of the 2010 World Cup). We do have a new angle on this well-known irritant, but first we’ll block out the noise to focus on the players. We measured the relative online buzz for the top players and also noted their ESPN skill ranking. See the “Top 10 World Cup Buzzing Players,” below.

General Trends and Analysis

• Skill and popularity don’t always go hand in hand. Fernando Torres is the leader in Social Rank, but ranked 8th by ESPN in Skill. Chris Dempsey has a Social Rank of 6 but didn’t make ESPN’s Top 25 for Skill.
• There’s a new rooster in the yard: Fernando Torres beats out heartthrob Cristiano Ronaldo in percentage of women buzzing about him. Overall, it’s not surprising that 62% of the online conversation is generated by men. But Torres and Ronaldo both attract more women than men (See chart below, “World Cup Players — Buzz by Gender”).
• The World Cup is so low scoring so far, anyone who scores can become a country’s — and the internet’s — hero. Clint Dempsey ranks primarily because of the one goal he scored in the England vs. USA match.
• The strikers are the most buzzed about players — despite the lull in scoring so far. In fact the only two in our Top 10 list that do not typically play a forward position (Frank Lampard and Dani Alves) are both involved in negatively trending discussions.

Trending Themes Around Top 3 Players
1. Fernando Torres, Spain: Conversation trending POSITIVE
The buzz…

• Torres has been coming off the bench. Fans can’t wait to see him start and increase his playing time. (We’ll watch to see if his already substantial buzz increases as his minutes increase.)
• Including Torres, Spain possesses a bench filled with players that are better than most World Cup teams
• He’s talked about as part of the Spanish dream team, with Xavi, David Villa, David Silva, and Fabregas
• Spain will garner more supporters because Torres is a fan favorite from the Liverpool FC, his regular-season team
• Torres is the hottest/best looking footballer

Sample post…
“I just got an email from a coworker & all it says is “I love Fernando Torres. The End.” Hahahaha”

2. Lionel Messi, Argentina: Conversation trending POSITIVE
The buzz…

• Best player, best moves, best save so far this World Cup (he is ESPN’s #1 ranked player)
• Argentina relies upon him more than Barcelona does.
• He’s been playing great; it’s the team’s fault he’s not scoring more.

Sample post…
“Vamos Messi Vamos Argentina !!!”

3. David Villa, Spain: Conversation trending POSITIVE
The buzz…

• Great for Spain
• 3rd best striker in the world
• Good player

Sample post…
“The hairstyle gods really don’t like Villa today”

We’ve got similar data for the other players in the Top 10 of online buzz. Just contact me and I’m happy to share.

Fans can be fickle and fortunes change with the bounce of a ball. Watch for our weekly updates of the buzz around key players.

And to bring it full circle…
It all comes back to vuvuzelas… Using our discovery-based insights to uncover emerging conversations, we found that Coca-Cola might have “blown it” with their campaign graphics for the World Cup. Last month when Coke’s vuvuzela-inspired designs were released, they were praised for their sleek appropriation of a cultural artifact dear to South African football. However this association became a liability as soon as the first vuvuzela was blown, because frustrated World Cup fans are doing whatever they can to lower the noise level on the pitch. Many fans are publicly protesting on Coke’s Facebook Page to stop purchasing Coke products until Coke helps ban vuvuzelas!

See the discussion topic “Pepsi until vuvuzela is banned” for more.

The disparity between shows high in viewership and shows high in engagement is reflected in the fact that more than half the shows in the SocialSenseTV Top 20 don’t appear in Nielsen’s top 20. The Hollywood Reporter covered the report and noted how ratings and fan-base don’t always match up. (digiday:DAILY also wrote about the report and our new SocialSenseTV offering.)

So how does this help a media buyer or a network? What can social engagement tell us that matters to the bottom line of those engaged in this spring rite of traditional media?

This is the time of year when networks, agencies, and brands all try to assess what a TV show is worth — and what it’s likely to be worth months later — so they can buy inventory now, at upfront prices. “Scatters,” or ads bought closer to air date, can cost 20 to 30% more than upfront buys. Shrewd, informed buying now saves agencies and brands a lot of money. Bad, misinformed choices will stick them with ads on shows that are dogs.

Social media provides a rich vein of conversation to mine that can measure engagement and passion around a show, an actor, or any other topic you care to explore. We can listen to the social conversation to discover why a show is popular, which shows are a good match for a brand, and ultimately, where to buy or sell TV inventory.

We can even analyze and “rate” shows that haven’t aired yet, by listening in on the early buzz about new shows and their stars.

Advertisers are seeking highly engaged audiences with the idea that they are more likely to watch live, see commercials, and appreciate the connection of brands to their favorite shows. Social media listening provides the perfect platform to find those engaged audiences and then discover what they are talking about.

For networks, the same dynamics are at play. If a network is cultivating shows with highly engaged fans, they’ll want to measure that and capitalize on it. They can use the data to prove value and legitimately increase the cost of TV ads. They can also find good matches between brands and shows by finding those shows with fans that care about a given product or category. Note (in the chart below) how network ranking changes when measured by social media ranking or Nielsen ranking of shows.

In a time when advertisers are worried about viewers skipping over commercials, branded content is a hot topic. We looked at two instances. It’s well known that Subway rescued “Chuck” from cancellation. And the fans seem grateful. They’re still talking about Subway when they talk about the show.

We also looked at the “Modern Family” iPad brand integration episode. Though iPad brought a lot more equity to the partnership (word is Apple didn’t pay cash for the deal, but their buzz is much higher online than that of the show), they did get a substantial lift: $516K in earned media.

These are just examples of the kind of campaign evaluation that social media analytics can provide. It’s a powerful new way to measure the impact of a campaign or tv event, because it aggregates effects from multiple channels: if you saw it live or delayed, on TV or on Hulu, in a bar or on a plane, the buzz registers the same online.

The full report includes more analysis of the uses of social media in informing upfront buying and selling, and more insights around specific shows. Please download it and let us know what you think. And if you are ready to enlist social media in your media buying or selling, check out SocialSenseTV, our new listening platform and custom reports services tailored to television.

Activities that are more strategic and proactive are best informed by an analytical listening platform like Networked Insights’ SocialSense. We cover the orange section of the chart. Those activities in the gray section are typically associated with monitoring solutions. Sure, there’s some value in the gray area. But with all the interest in quantifying and evaluating ROI from social media, the orange activities are worth noting for their high ROI value.

Being smart and informed early in the process (regarding Market Research, for example) pays greater dividends than being smart later (Crisis Management, for example).

Still, a marketer’s first thought about using social-media data is often found at the bottom left of the chart around PR activities. I hope this chart encourages marketers to think more broadly. As you begin to track patterns over mentions, moving rightward and upward across the landscape of the Analytics chart, you’ll reap greater rewards and realize significant, measurable ROI from your social-media listening efforts.

Where do you fit on the continuum? Are you operating in the orange area? I’d love to hear your feedback. And please share this chart, either by linking here or passing it along.

From our point of view, the situation is an excellent example of how listening to social media is a critical part of a holistic approach to campaign design, helping to fill in the gaps left by traditional methods. The auto industry has long known that, while men purchase more than half of all cars, women exert influence over more than 80% of purchases. Beyond that, the February sales figures show Toyota declining 8% while Ford sales increased 43%!

So while traditional research and metrics let marketers know that they should be focusing on women, they fall short in understanding how to talk to those women. Our data showed that while men seem to be willing to give Toyota a bit more leeway — talking about fixing and loving, women use harsher words like failure and damage. In addition, Ford comes up a lot in these conversations, furthering bolstering the argument about the importance of speaking to women.

So what does this mean for the marketers designing Toyota’s post-recall campaign? Just as Roehm pointed out, they need to talk to women; they should focus on quality and reliability; and they should probably go head-to-head with Ford.

The 2010 Winter Olympics were a laboratory for testing how events and advertising play on the second screen. Most of the “experiments,” the way we interpret social media data, were focused on how consumers behave in social media. But what we can learn from 300 million people interacting online should inform all aspects of marketing.

Networked Insights conducted a study to help agencies and brands find the best athletes to sign celebrity endorsement deals. We measured online engagement around particular athletes and combined those results with demographic data from the sites where the posts appeared to find out not only who is most popular — but with whom.

The study was picked up by Adweek, Wired, and Digiday.

The full results are included. Here are a few items of note:

• Sidney Crosby is the hands-down winner in engagement. At his level, he’s still pulling in more women than any other athlete, even though his audience is predominantly male. He’s clearly a good candidate for sponsorship for many types of campaigns.

• For a company wanting to get women’s attention, Apolo Anton Ohno is a great pick. The former Dancing with the Stars champ is particularly appealing to women ages 25 to 44.

• To capture the coveted 18 to 24 market, consider Bode Miller.

• For high-end products, Evan Lysacek brings home the gold with the $100K+ income crowd. Not surprisingly, these wealthier fans skew slightly older with a big group at 35 to 54. There are slightly more males in the audience.

This data can fuel insights to solve a real marketing problem: Whom should we choose to be a celebrity endorser for our product? Like any important decision around marketing strategy or tactics, it should be compared with other data and expertise. Agencies and brands will certainly consider the nature of the product and the celebrity personality, for instance.

This Networked Insights study combines engagement metrics with demographic data, which was averaged from sites with highest engagement for specific athletes.

Now, you’re probably wondering why I italicized the little quote about highly regarded sources, and if you are the foreshadowing type, you may already be able to guess where I’m going with this. First, let me say that most of the effective algorithms for extracting entities, and almost all of NLP, rely on fairly well formatted, “predictable” text. By “predictable” I mean that it follows formal grammar rules, etc. So, in selecting highly regarded sources (say, CNN?) you are constraining your statistical frame to sites that you can processes. There isn’t anything terribly wrong with doing what you’re good at, but I would like to argue that, at least at Networked Insights, we fight to keep away from this restriction. In part, formal writing carries a bias. It carries a message motivated by some latent motivations. Keeping a high reputation, for instance. It is an immensely more difficult task to harvest information from the drips-and-drabs of informal writing such as is found in twitter and forums (or even blogs).

It’s because of this that, while the thought of Evri is exciting, I don’t think it will tell you anything that you didn’t already know. Now, my goal isn’t to pick on Evri, but I think it is fascinating to realize that the reason that analyzing more formal and easily analyzed text on the web is a bit of a losing battle is because the formalism comes in part from the author knowing that we are watching. Fox or CNN write with a specific audience in mind, and that audience is the same audience that TV seeks to entertain, and on, and on, and on. What is so powerful about the social web is that it’s text produced with only an audience of two or three people being expected.

I say this is powerful in two ways. First, biases equal out by the sheer volume and diversity of publishers. If someone is trying to catch the attention of a particular audience and tailors their text to fit, then that intentional word-smithing is likely reduced by countless other authors with similar overall ideas to express, but different spins to put on the text. Second, since most of this text is being generated quickly, and admittedly not always that well thought out, the raw feelings of people tend to leak into the text. It’s the living room conversations had without thinking. It’s the reflexive “boo” at the stadium. This rawness, if you will, if far more valuable because it’s never what you were expecting.