Debunking the Data Myths: Three Truths About Big Social Data

debunking data myths - 3 truths about big data

Credit: LooseKeys –

Let’s talk data. Big Data. Data, not traditionally the sexiest of topics, was hot in 2013.Why? Businesses are anticipating that big data has the potential to yield valuable insights that will drive the bottom line. In this post, we’re going to talk about one spoke in the wheel of big data, big social data, and some of the common myths that can keep companies from being satisfied with their investment in social analytics.

Myth 1:  Bigger is better.

Big social data is not hard to get; API technologies can easily acquire masses of Facebook and Twitter data to be quickly packaged and resold. Facebook and Twitter data may reveal how people engage with brands through the brand sponsored FB pages or Twitter handles, but should be viewed as a sounding board that indicates how people are reacting to your social media efforts.

Good to know, but you may miss the conversations where people candidly talk to each other about what they want and need. Those conversations happen in forums and blogs and they are harder to get because these venues don’t have APIs. Nonetheless, analysis of these human-to-human conversations is more likely to yield the consumer insights and white space opportunities with the greatest potential impact.  So when thinking about social data, keep in mind it’s not the size of the data so much as what you can do with it.

MYTH 2: Big Data Should Be Fast

Immediate access to information may be appealing in concept. But to make the most of big social data, you may have to slow down.  Real time data is like taking the hose off the hydrant. You gain access to a huge volume of data but it’s difficult to leverage toward business solutions. Immediate and constant exposure to big data encourages reactive tactics to spikes in brand mentions or social media activity, but offers little or no strategic insight into your category or consumers.

Real time data is like measuring the volume of someone’s voice without hearing what they have to say.  Also, real time data requires automation to the highest degree, which comes at the cost of data quality. Any content, regardless of its source, is entered into the data stream, including thousands of unwanted spam. So when looking at big social data, start with a clear definition of the business problem you are trying to address, slow down, and take the time to get the strategic answers you need.

MYTH 3: Big Data Should Be Pretty.

Visualization has been a focus for purveyors of big data, and dashboards and applications can do a great job of reorganizing data into a graph or chart. However, a graph or chart is not an insight in itself. It doesn’t matter how well you can present the data if you are not gathering any new insights from it. Data needs to be interpreted and not just visualized. To unveil true marketing insights, data requires tools designed for analytics and human strategists (not robots) to interpret the trends in consumer conversation.

In hopes of helping those wrestling with big data, we have debunked a few myths to unveil the true strengths of data done right. It’s essential to shift the focus to useful, relevant data, structured and strategic, and analyzed by humans, and not just present yet another fancy graph. Until this is understood, there is a risk that businesses not taking the best approach and may be disappointed when social analytics are not meeting their expectations. We need to understand the truth about big social data in order to glean anything useful from it.