A Social Stream in an Ocean of Big Data
Hello big data!
The buzz is getting louder around the legal water coolers these days. There’s a lot more talk about big data regulations, compliance, and privacy—the legal stuff, of course. But there are also an increasing number of conversations around concepts such as “disparate records” stored in “unstructured” ways on network drives, PCs, mobile devices, and even flash drives, followed by a discussion on how they will be integrated, analyzed and made useful for the law firm. Depending upon which silo you’re grazing from, you might hear talk about data produced by transaction-based processes, billing invoices, and resource allocation to be used to improve decision making and reduce operational costs. See also Forbes June 26, 2012 and Inside Counsel February 19, 2013.
Meanwhile, a killer set of data is quietly flowing through the social stream.
Hello Super Bowl Ad Fans!
Did you know that Super Bowl advertisers paid $4 million for a 30 second spot? For 60 seconds of air time they paid $8 million during the big game this year. Quantitatively speaking, that same $4 million could have bought roughly eight spots on Sunday Night Football during the regular season. It would seem that the latter reach and repetition would equal greater exposure. Nope. Advertisers pay the big bucks on the big day because they know that it’s the only time people actually watch and talk about ads. Today, that’s even more valuable than ever. They talk about those ads on social media.
Social media chatter not only increases exposure across mediums, it increases the ad’s shelf-life—keeping their brand in the national conversation before, during, and after the event. More importantly perhaps, advertisers capture meaningful social data—data that provides important and actionable insights, especially when it is integrated with more traditional, structured data from finance, sales, and etc.—thanks to new open source code.
To illustrate, social media data reported by tracx.com revealed that the 77.1 percent of people posting to social about the Budweiser Clydesdales were female compared to 54 percent for all Super Bowl activity on social. Some 18.5 percent of posts referenced some term related to crying, which indicated that the ad reached people on a very emotional level. A total 14.5 percent of conversation surrounding the commercial involved what they would name the new foal. The most popular suggestion was “Raven.” Let’s leave it to the ad execs to make the connections here, but admittedly that’s more insight than what you’d get trying to pinpoint the moment that millions of very different people watching a TV ad make up their mind to buy something. (Raven Beer, anyone?)
Social media activity for the Samsung commercials indicated that the Paul Rudd, Seth Rogen, Lebron James spot benefited from its pre-game day release on the Internet. It also revealed that although James was arguably the biggest star in the spot (and likely the most expensive), his cameo presence in the two-minute ad did not produce a social lift. Rudd (an actor) was the most mentioned (11,694), followed by comedian Rogen (9,395), leaving NBA star James (635) to trail the pack, receiving only 4.5 percent of Samsung Super Bowl ad mentions on social media. (Can anyone say “buyer’s remorse?”)
More than for any other brand, people on social media chose the Taco Bell commercial using the Spanish version of “We Are Young” as their favorite. A light-hearted take on the theme of older people acting young, some 12.9 percent of social interactions about the Taco Bell ad used some form of LOL (laugh out loud) in their post to show they found the ads funny. (Funny is good. Funny is the Taco Bell brand. Funny is favorite. Let’s be funny.)
All of this data, when integrated and analyzed against other data sources, gives executives valid information upon which to act moving forward, and which can dramatically affect consumer choice and behavior…(Hint: REVENUE)
Hello Digital Social Data Mashers!
Open source code such as Apache™ Hadoop® is making it possible for any organization, brand, or yes, even law firms to collect and distribute unstructured social data along side other disparate data stored in an assortment of databases such as those that run on Java, Pig, Hive, Flume, Fuse, Oozie, and Sqoop with Informix, DB2, and MySQL. (Source: IBM.com)
This mash up of data can give executives across the enterprise, not just marketing executives, some pretty juicy insight for forward-looking actions.
Hello Comparative Analysis!
If you’ve ever looked at your website statistics and wondered, “Am I supposed to do something with those?” you’ll appreciate social data. Web analytics are great, but they are raw data and no match for human scale. Terms like “Visit,” “Page view,” “Referrer,” or “Clickstream” have no industry standards. They mean different things to different software and typically mean nothing to most people who look at them. However, together, Web analytics (including mobile), social data, and the right analyst in the driver seat, with the right questions to answer, can produce insights that actually tell you something useful.
Social experimentation, comparative analysis, and integration with traditional business intelligence research and other enterprise records can go along way in making your big data sing a tune on a human scale.
I’ll leave you with that thought, and welcome your comments.