Visualising Big Data: The Super Bowl 2012

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Visualising Big Data: The Super Bowl 2012

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We built a data viz to visualise conversation surrounding the Super Bowl and brands,. More: http://bit.ly/zpE1IW

We built a data viz to visualise conversation surrounding the Super Bowl and brands,. More: http://bit.ly/zpE1IW

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  • 1. The Brandwatch Super Bowl 2012:VISUALISING BIG SOCIAL MEDIA DATABackgroundThe Super Bowl is famously one of the most commercialised events in the world. TV advertising isnow a key feature of the game-day broadcast and generates a massive amount of publicity formost of the brands fortunate enough to win one of the prestigious spots.Of course, with prestige comes expense – companies paid an average of $3.5 million for a 30-second spot in the 2012 Super Bowl. With social media rapidly growing as a communicationschannel, and arguably overtaking TV, brands need to understand what impact their campaigns arehaving on their online presence.So were asking - is ad-spend directly reflected by online buzz? Or does it take something more?AimsWe chose this particular question, focused on an event with global interest, in order to support amarketing campaign we planned to run. The objectives of which were to: Showcase our expertise as a social media monitoring company with a creative and innovative approach to analysing and presenting ‘big data’ in an engaging way. Raise awareness of Brandwatch in our key target markets, specifically US, through a mechanism that would capture imagination and encourage people to share online. Specifically raise awareness of Brandwatch among high profile brand advertisers and agencies that we wanted to target.To achieve this we: Used the Brandwatch tool to analyse the social media buzz around the Super Bowl XLVI advertisers and sponsors to assess whether the amount of advertising spend directly correlates to the volume of buzz each advertiser attracts in the run up to, during and post the event. Presented the analysis in a visual and creative way in order to demonstrate how data can engage and capture the attention of an audience to promote a message (in this case, Brandwatch!).
  • 2. Methodology a. DataTwitter has become one of the key portals for public commentary on what is going on in the worldright now, be it sports, television, politics or other news. Therefore, for us to analyse live-eventresponse, Twitter would be best for getting timely, high quality and relevant data - the network’sopenness also meant we could be sure we were gathering the data comprehensively usingTwitter’s Firehose.First, we created our “mega” Super Bowl query in Brandwatch to return all tweets that included anymention of the event itself. Then we drew up a list of all the brands advertising during Super BowlXLVI and created topics within the main query that would match mentions of the brands or theproducts they were due to advertise.This approach meant that all the tweets we presented for each brand would have to mention boththe Super Bowl and the product or brand in question. b. Creative deliveryThe web is full of static infographics that are built to visualise a fixed set of data - perhaps someresearch or post-event analysis. However, we decided a live app would more accurately reflect thefluctuating reality of the social web.So our creative team built a beautiful Flash app hooked up to Brandwatch’s API to feed in the dataoutlined above. We hoped this would tick both the “interesting” and “fun” boxes, whilst staying trueto the fast-paced data-centric world of the web.The Brandwatch Super Bowl 2012:
  • 3. So how did we visualise the data?The players, the commentators and the cheerleader:Football-playing worms: Each of these represented a brand sponsor and the number under eachworm hole reflected how many tweets were made about that brand or their products over the last28 days - the brand with the most tweets about them at any one point would have the ball. Userscould roll their mouse over each advertiser worm hole to see how the last 20 tweets posted aboutthat brand.UK and US news worms: In addition to the branded worms showing tweets, we included wormsthat fed through the hottest Super Bowl stories from their nations news sites:#BWcheerleader: To add a more interactive element, we created a cheerleading worm who wouldchant any messages that people tweeted using the #BWcheerleader hashtag:Leader board: This shows the total number of Super Bowl tweets overall, along with all the brandsranked in order of the number of tweets about them. The line graph shows when the major spikesfor each brand occurred, and the pie chart shows how the sentiment worked out:
  • 4. Who got the most buzz for their buck? The results:We found that, according to our ad-spend estimates (advertisers were said to pay $3.5m per 30-second slot), H&M’s ad generated the most buzz for their money. They were the only advertiser toair just one 30-second spot in the top 10 most talked about, with other brands spendingsomewhere between $7m and $31.5m. Pepsi were second, closely following H&M in terms of costper mention, and they also generated the most overall buzz.We presented the results of the live data-viz in the below infographic:A data engagement campaignAs well as creating a visual data platform for our Super Bowl analysis, we used variouspromotional channels to encourage people interested in following Super Bowl brand chatter tofollow, engage and spread the word to help promote our social media monitoring and datavisualization capabilities.We planted the seed via:  PR – A press release was issued to our target media in the run up to the event.  Social media – Our Community Manager posted tweets and comments in relevant forums. A blog post also provided more information on how the data-viz was created.  Website – an ad was placed on our homepage with a link to the data-viz  On-going community engagement – The whole team helped to drive attention to the data- viz by posting to people they felt it would be of interest to across creative, sports, marketing, digital and tech forums and news sites, as well as to the brands and sponsors themselves.
  • 5.  A late night – Our Community Manager got through copious amounts of coffee to stay awake for the game in order to tweet live from the action as it happened.  Display and PPC – We commissioned a low spend display advertising campaign and ran relevant PPC ads to help raise awareness of the data-viz and Brandwatch.If you create a concept that is truly engaging to the right people, it can take on a life of its own andwork as an efficient marketing and data promotion channel.We are pleased to report that we weren’t the only ones to think it was interesting, fun andengaging! We set out to spread the word on Brandwatch and we achieved it. From launch onThursday 2nd February through to Tuesday 7 th our Super Bowl data visualisation received:  6,835 unique visitors to the data-viz  Online advertising generated 3 million impressions and over 1,500 clicks  Approximately 900 tweets from companies including: o Samsung USA o H&M USA o H&M Canada o Dolby  And influencers including: o Angel investor Peter Shankman o Editors at Huffington Post and The Guardian o Senior engineer at Apple o Interactive Marketing Manager at Coca-Cola o Director at TBWA  Press coverage was received on some of our target media sites, including: o The Next Web o MediaBistro o Digital Spy o Econsultancy o Pocket Lint o Infosthetics o Update or Die!Example tweets:
  • 6. ConclusionWhat it showed:So, which brand got the most buzz for their buck? One 30-second slot from H&M was enough forthe fashion brand to secure the cheapest cost per mention from their $3.5m advertisinginvestment. For this, they ranked as the 6th most talked about brand overall.It seems, then, that big-budget productions and clever creative isn’t necessarily the be all and endall of advertising; a sports star in underwear is enough to get TV viewers chattering.Other key factors in successfully generating buzz were: releasing teasers early on, using topcelebrities and expressing controversial opinions. Whilst these might not all have generatedpositive conversation around the brand, any publicity is good publicity, right?What we learned:It’s apparent that infographics and data visualisations are very much the online zeitgeist. With theweb so full of them it’s a challenge to get people to take notice. Building something live andinteractive like our Super Bowl app has various benefits: - People’s experiences with it are unique – the exact same data is never shown twice - More information can be packed into a working app than into a static image - It’s a showcase of technical expertise and innovationDone well, data visualisations can be an elegant solution to making big data digestible andengaging and, as a marketing or PR tool, can be an effective way to engage an audience and driveattention.We designed this campaign to raise awareness of Brandwatch within key target markets,specifically the US, and we are happy with the results: - Site traffic increased 558% year on year (from the date of the 2011 Super Bowl) and was up 64% against the previous week. This boost came from Super Bowl related traffic from social media channels in the main, demonstrating the viral effect our campaign achieved, nurtured by our community management approach to seeding the ‘story’. - Half of all geographic reach: 49% of all visits came from the US, a key target market for Brandwatch, which this campaign was designed to engage. - As highlighted earlier in this case study, we wanted to grab the attention of the brands that would be interested in following this campaign; Samsung, H&M and Dolby were a few of the brands that tweeted and commented on it.If you’d like to know more about Brandwatch and how we can help you create visuallycompelling ideas that communicate a message to your audience, please get in touch.