How to Make Big Data Less Scary for Marketers

By: Clarabridge Team

October 28, 2014

Big data

By: Tim Lau

Ghosts, witches, and vampires might be the traditional figures of fright in October, but in recent years, “big data” has been the specter haunting many marketers. The number of customer feedback channels – and consequently, data sources – has increased exponentially. Each source, in turn, can provide millions of pieces of individual data that companies can analyze.  At Clarabridge alone, we have processed more than 4.8 billion records on behalf of our customers.

The sheer scale and complexity of big data can be scary for marketers – and rightly so, as the variety, volume and velocity of data will only continue to grow. According to an estimate by Digital Universe, there will be 5,200 gigabytes of data for every human on Earth by 2020.

However, big data also presents a great opportunity for marketing professionals, particularly those involved in customer experience. When aggregated, customer data can unmask the consumer, revealing  who customers are, what they are interested in, and how they engage on various channels.

Consider the following steps to make big data for customer experience less intimidating:

  • Establish goals. Align your customer experience and big data program with broader organizational goals. This will help you evaluate how well different technology options will align specifically with your team or organization.
  • Identify and implement technology. Determine which sources of data are most relevant to company operations, and use this information to identify the technology with the most relevant capabilities. When doing so, account for the fact that the number of data sources will only continue to increase. As such, consider options that generate insights by aggregating the largest possible number of available sources.
  • Measure progress. It’s important to tie big data analysis to actual business outcomes. A great example is Clorox, who has increased customer engagement by over 300% by using text analytics and Natural Language Processing (NLP). Regularly measuring your progress will help you refine your goals and to adapt your programs accordingly.

With the right techniques in place, you can reduce the tricks and increase the treats provided by Big Data. You don’t have to be afraid of it.

What questions should you consider when considering a text analytics provider? To learn more, download our cheat sheet, Eight Questions to Ask your Text Analytics Vendor.

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