Big data. There’s no agreement on what it is, yet companies are spending hundreds of millions of dollars on it and claiming good returns. In 2012, big data was the star in the business intelligence and analytic’s industry. This year analysts say that businesses will spend time figuring out what it is and isn’t what challenges it presents, where the real value is, and how they’ll need to evolve – architecturally and culturally – to tap into that value.
So what exactly is big data? Loosely defined, it is the collection and analysis of a myriad of unrelated data sources with the aim of drawing meaningful business insights. The much-hyped term has inspired a slew of definitions, many of which involve the concepts of massive volume, velocity and variety of information. In other words, what turn data into Big Data is the amount of information, and the speed at which it can be created, collected and analyzed.
Experts agree that big data exists, but they still question its significance and lack of focus. While vendors, educators and analysts all have a point of view and a vested interest in the topic, marketers and media people are working tirelessly trying to optimize their relationships with customers by collecting and mining data to better understand the consumer.
According to Todd Nash, a founding principal at CBIG Consulting, a professional services firm in Rosemont, IL, starting a big data analytics initiative without a clear framework is wasting valuable energy, time and money. A well-defined big data framework strategy should, according to Nash, clearly identify and outline all of the goals, business processes and people involved in accomplishing those objectives, including:
• Identifying opportunities
• Building the business use case
• Determining governance and ownership
• Determining the solution architecture
• Developing a big data roadmap
This framework, according to Nash, stresses achieving qualitative and quantitative solutions that will help your organization make more informed strategic decisions. It’s one thing to measure a business based on a snapshot transactional metric, such as “How many widgets did I sell last month at this location?” The real business value of your big data program becomes obvious when your firm can draw pragmatic, actionable insight as to why your firm sold so many widgets at a particular location.
For many firms, the first step in the big data journey is an effective social media analytics initiative. For the first time since the invention of the internet, hundreds of millions of consumers are consistently congregating in a single place. At the same time, consumer behavior is rapidly shifting toward a more permissive model of sharing and privacy. Individuals want to share their lives online – look at the millions of members on Facebook, Twitter, LinkedIn and other social media websites.
Social media analytics provides a measurable means of gathering, processing, analyzing and delivering business intelligence from social media channels. The social media landscape will continue to emerge and evolve due to consumer shifts, channel shifts, brand shifts and new entrants in the space. The landscape includes countless data resources, including social sites like Facebook, Twitter, LinkedIn and Google+; review sites like Angie’s List, Yelp, Urbanspoon and TripAdvisor; blogs and news sites that include and encourage comments; video and photo sharing sites like YouTube and Flickr; and search engines like Yahoo!, Google and Bing.
According to Nash, all of these unstructured data points can yield critical perceptions about a particular brand and/or product, where these items are purchased, who is using them and how they feel about them. This helps clients leverage their data assets through big data analytics to produce timely, effective business strategies and tactical decisions. But to get accurate answers to these issues, an effective social media analytics consulting approach should be based on four components, or layers, that build on one another:
Awareness. It stands to reason that if you don’t know where you are, you won’t know which way to go. The starting point is to understand consumer awareness of products and services. Measurable, disparate data is taken from the following sources: social media channels, search activity and regions/location (today, almost everything can be associated to a location). To gather this data, use a combination of web crawlers and application programming interfaces to extract social media data. Typical graphics used to illustrate awareness may include charts depicting year-over-year brand mentions by region, conversations by social media channel per day and trending hashtags.
Analysis. The next step involves understanding what’s being said about products and services. Commonly referred to as “sentiment analysis,” this information is positive, negative or neutral. To determine this, use a rules-based engine that filters through all types of unstructured data and then calculates a quantifiable value to it. This analysis can show a breakdown of sentiment by channel, top trending social media channels in relation to number of opinions and whether these channels are trending up or down relative to positive/negative sentiment, for example.
Influence. This component helps business understand which social media contributors are significant and which are not. For instance, if someone has many friends or followers, their sentiment will have a greater impact than someone who does not. This information can lead to intelligence showing which regions have the highest and lowest concentrations of influencers, as well as number of mentions vs. actual users in a given region. Enterprises can effectively benefit from these details by pinpointing trouble spots of negative influence, or by improving market penetration and product placement geographically, for example.
Evaluation. A key result of an effective SMA strategy is the capacity to measure and evaluate a PR campaign or marketing promotion that has been deployed. Say a business tries to convince a negative influencer to retry a product or service, or incent a positive influencer to “talk” more about a product or service. This promotion will ask for a response on the part of the targeted influencer, such as clicking a “like” button or offering a coupon in exchange for a “like.” Customer response rates in relation to a product or series of products, as well as the sentiment attached to these response rates, can then be measured and mapped out by social media channel and region. And then the whole process circles back to the beginning to see if the promotion is having an impact.
Information culled from online social media can be beneficial to every business. As marketing and media professionals continue to reach consumers through social media, analysts will be able to continue to conceive, implement and deliver the right information that allows companies to better understand who their consumer is and how to reach and keep them.