Big Data and analytics are transforming how business leaders do business. As more and more companies are embracing the power of data and technology, there is a change in mindset from heuristic driven decision making to data driven decision making; from an expert based mindset to much more dynamic and learning mindset. Globally, it is marketers who are leading this change by adopting new tools and technologies.

Big Data and Marketing
CMOs would tell you marketing data has always been big. Even 20 years ago, business used to collect point of sale data, customer data, store feedbacks, direct mail campaign data etc. But big data doesn’t necessarily lead to better marketing campaigns. So what is new?

In the last 20 years, developments in technology have led prices of storage and compute to go down drastically. Which meant more data can be collected, stored and analyzed, and all this, in a matter of seconds. Some retailers armed with beacon technology can even capture data from your visits to brick and mortar retail stores.

Advent of real time technologies has meant, you can reach out to a customer right at the point of purchase and influence his decision making. You can get insights not only into generic consumer behaviour but what a specific customer wants, what has been his history and how can he be best influenced. The journey from awareness set to consideration set to decision set can be hyper-personalized.

Customer Engagement and Big Data
Retailers and brands can use data to identify who their customers really are, where they go, what they want, what are their social habits, where they work, how much they earn, how they like to be contacted and when. Predictive analytics technologies can pinpoint how you can engage with the right customer, at the right place and the right time. You can use techniques like data mining, statistical

modelling, machine learning and AI to analyze streaming data from customer touch points, websites and beacons, put it in historical context and predict customer’s willingness to make a purchase.

The journey from awareness set to consideration set to decision set can be hyper personalized

Next step will be to activate a contextual marketing campaign to convert this customer. The possible channels that marketers typically engage are search engine remarketing campaigns, display remarketing campaigns, targeted email campaigns, push notifications, and even offline text messages. By ensuring the right people are being targeted, the conversion rate is drastically improved.

Customer Retention and Loyalty
Marketers are today running advanced analytics on the data gleaned from customer interaction points to improve conversion, reduce churn, drive brand loyalty and increase revenue. Today’s omnichannel world is proving to be a boon and a bane at the same time. Due to multiple online and offline customer touch points, there are huge amounts of data which needs to be quickly analyzed and acted upon. At the same time, a marketer can analyze this data, to offer every customer a consistent and personalized buying experience, to win the loyalty of the customer.

Customer loyalty programs are not new. However marketers are now able to leverage the transaction history associated with your membership card, to collect data from offline stores and use it to trigger marketing campaigns. It is difficult to retain a customer in the online world where visiting a new store is as easy as opening a new tab on the browser. Hence marketers need to come up with personalized marketing campaigns to reactivate a customer or risk losing him. Companies like Netflix and recently Amazon have used big data extensively not only to run marketing campaigns but also to come up with ideas for new titles and storylines.

Marketers can start with high level problems like: which channel has highest ROI, what messaging attract high value customers, which customer segments have higher will ingness to pay and what campaigns have worked the best for the brand.

You can convert these questions to hypothesis like, Face¬book helps reach new age customers better, dissonance between advertising messaging and website messaging, or people with higher incomes will have higher lifetime value. Once these hypotheses are formalized, marketers can use data gleaned from different sources to run A/B tests, track campaign roll outs, track feature launches and stop fraudulent activities.

Big data requires sophisticated tools for warehousing, management, integration and analytics to empower marketers with business insights into their customer’s behaviour, preferences and buying patterns. Big data is transforming the way companies market their products and improve customer relationships. Customer analytics can not only be used to validate marketing approaches, but also to come up with products and services which align better with your customers.