Leveraging big data for audience insights

Understanding the principles of big data is key to using it to gain a deeper understanding your audience

12Feb

Big data seems like a marketing buzzword because of all the attention it's been getting in the press. Oracle defines big data as complex data sets that are so huge that regular processing methodology is insufficient to deal with it. Big data represents a substantial amount of unprocessed, collected facts and figures that can be used to determine a wide range of behaviors. However, before we can even begin to think about leveraging big data to figure out what we want to know about our customers, we must first understand the underlying principles of big data.

The skeleton underneath big data

Based on what Science Direct says, many business jump into the big data pond before actually know ing what it entails, and the resulting poor implementation makes them spend lots of money on tools that they may not actually need. Big data is usually defined with an acronym known as the "Four V's", which are:

Volume: The total amount of data available for processing

Velocity: A reference to how current or relevant the collected data is

Variety: What kinds of data are available

Veracity: The accuracy of the data and how it can be applied to a particular usage

Of the Four V's of big data, the one we're most concerned with when looking at audience insight is veracity. Determining the veracity of a piece of data allows for an adaptive strategy as far as content creation and marketing is concerned. However, it's a difficult process to wade through the noise and bring out the viable data hidden within the massive, tangled web of the data sets.

Why is data veracity so important?

In short, data veracity allows us to tell whether the facts and figures we've gathered stand up to scrutiny or whether they just aren't realistic. Most times, it's not the actual facts and figures that have to be questioned, but the source of that data and how it was processed before being added to the big data pool. The accuracy of a piece of data can be massively improved if things like inconsistencies, duplication and bias are dealt with prior to it being accepted into the data pool. The volatility of the data (sometimes referred to as the fifth V of big data) refers to how fast that data becomes irrelevant. Highly volatile data would include things like social media trends. This volatility presents the first hurdle that big data must cross in order to be considered useful for developing audience insights.

In addition to volatility, veracity of a collection of data rests heavily on creation of sensible data sets. Big data is the best descriptor for this sort of unsorted, uncategorized facts and figures, since according to Sisense, it's estimated that big data generates as much as 2.3 trillion gigabytes per day. Even using the processing of a powerful computer, we would need to figure out sensible links between our data sets and the onus lies on the initial processing to create those links. Getting that processing done in both a sensible and efficient manner ensures that the data volatility isn't violated while still allowing for insights to be drawn from the data set.

Using big data to develop market insights

The central idea behind integrating big data with marketing methodology is to provide a more complete picture of the customer and their wants and needs. According to Cleverism, this particular trait of identifying the needs of the customer forms the basis of most of marketing, and with this in mind we can see how big data can come to the aid of marketing professionals looking to distribute content optimized for audiences. By using survey information coupled with big data, we can start to figure out one of the most complex and elusive ideas in modern marketing – consumer behavior.

Humans are an enigma in how they act for the most part. In recent years, marketers have realized that people in the modern era don't particularly like being "sold to". Big data alongside collected survey data has the potential to help marketers figure out what consumers want and need so that there's no reason to "sell" to them - they pretty much sell to themselves. It's almost like realizing the dream of every marketing department in the world.

Working out the hiccups

While the idea of using big data to seamlessly create marketing plans and products that sell, we're a long way off from bringing that dream to fruition. There are a number of issues in integrating big data into the organizational structure and even with combining survey data with big data to improve veracity, but through time these will be ironed out. There's a very good likelihood that within our lifetimes we may see big data's impact on modern marketing change the entire face of the industry for the better.

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