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By using Big Data to better understand preference, prediction, personalization, and promotion, companies are finding a better way to customize their marketing.

Sometimes we get really impressed by how big Big Data is. After all, humans collectively generate an estimated 2.5 quintillion bytes of information daily. Google alone is estimated to store over 10 exabytes of data; Amazon is estimated to account for another exabyte and other industry giants are not far behind. By the way, an exabyte is one billion gigabytes of data. That’s a whole lot.

The problem starts when we get so interested in the immense size of Big Data that we forget to think small. Big Data strategy isn’t just about the gargantuan numbers; it can be used to connect with every customer in a personalized way.

No one will argue that there’s been a shift in how marketers interact with customers, and likewise there’s no dispute that Big Data is a factor in that shift. Customers are consuming information differently. They are expecting to be engaged and informed by content and offers— what and why they purchase is evolving, and nearly everything should be available online. To be successful, marketers had to adapt to meet these demands.

Getting Small with Big Data

Marketers used to rely on sample-based preference and usage measurements, and very often these were self-reported and prone to bias. However, since Big Data processes information at the individual level as well as in the aggregate, preference information is much more accurate and tailored now. Recommendations can be made based on purchase history. And they’re much better when you include browsing history, search history and even other people’s purchasing patterns.

The upshot is that not only do marketers get a clearer picture of the individual customer, they can also plan their reach outs for the best possible time.  If a customer appears to be wavering over an item left in a shopping cart, a properly-timed and expertly-crafted email or push notification can seal the deal.

In this environment, concepts that were longstanding pillars of the business are being restructured or even reconsidered. What about the fabled Four Ps of Marketing? What’s happening at the intersection of Big Data and this particular pillar?

The Ongoing Evolution of the 4Ps of Marketing

The Four Ps of Marketing — preference, prediction, personalization, and promotion — are still relevant today, but how they are being uncovered and applied is evolving:

Preference

Let’s focus on one aspect of Big Data technology here, Enhanced Social Listening. For those not familiar with social listening, these tools track your campaigns; scan for brand mentions, hashtags, and keywords; reveal customers’ complaints; and highlight potential influencers. We’re talking about more than just reporting here — when you combine this insight with advanced analytics and text mining, your brand becomes more responsive, almost intuitive in how it understands customer desires.

Prediction

Sometimes guessing what your customer will want to buy next is easy. A man with a new motorcycle will buy a helmet in the near future. However, getting a healthy mix of other information (beyond recent purchase history) can extend this insight in surprising ways. Not only can you refine the offers provided to your customer — offering him the most relevant helmet for his tastes and spending habits — you can predict the buying behavior of an entire area and order your stock accordingly. If a motorcycle movie was recently released, you might well see a surge of interest in the helmets worn in the film.

Personalization

Personalization in marketing is nothing new, but it’s been ramped up in a big way. We now have hyperpersonalization, or ultra-specific campaigns and interactions that are largely made possible by Big Data analytical processing. Not only is this a more effective sales tool, it fosters better customer loyalty and brand connections.

Promotion

The best campaign in the world falls flat if you don’t get it near the customer. But how will you do that? There are so many channels today that it is vital to know which one the customer prefers. This information can be used collectively in large-scale ways (targeting search engine keywords, developing a social media presence) or in the small scale (selecting what piece of content to send to an individual). This can help you identify the social influencers you need to reach, the content that might go viral if you promote it wisely and the keywords that will return the best search results.

In conclusion, we could say that even if the game is marketing, Big Data is changing how the game is played. Adopting these technologies isn’t about being in the forefront of progress — it’s about keeping up with the competition.

Authored by Titir Pal, Vice President: Head of Products and Solutions at Absolutdata Analytics and  LK Sharma , Associate Director – Head of Business Intelligence and Technology at Absolutdata Analytics