What can ‘big data’ tell you about your customers: a marketer’s view

Big data, a hot buzzword, has had several effects on various businesses such as manufacturing, retail, communications, entertainment and many others. It has a larger-than life role in establishing strong relationships with customers and the time to join this party is now. The overarching trend is that data is growing rapidly and so much so that, 90% of the data existing in the world today, has been created in the last 2 years.
The subject of prediction has always been a matter looked at as, possibly guesswork, possibly mathematics. Consider the debate over population predictions as part of UN population estimates or any other. Reading the future is not left to mystical exercise of the soothsayers alone. It is now part of hardcore business reality. Whatever be the discipline, there is a wealth of messy, unstructured, real-time data from customers, competitors, and marketers that can be used and analyzed to find what’s coming up next. So wherein lies the true edge? When one is able to complete the data analysis and predict the future even before competition can. The possible areas where big data can be used are also several.

A Case Study
A good case study is that of the New York Police Department (NYPD) fighting crime and identifying likely ‘hot spots’ or even the Blackberry Waze that is susceptible to network effect. The more people use this app, the more data is collected and fed back to drivers, which in turn encourages existing users to stick with it and new ones to join ensuring better connect and visibility. Big data applications process structured and unstructured data, logs, social data, digital images, and online videos as well. Social media channels have a large role to play in them.
Organizations also mine intelligence from data-intensive channels such as blogs, chat forums, Twitter trends, or Facebook commentaries. While traditional market research generally involves surveys, mall-intercept interviews, and focus groups, big data examines what people say about what they have done or will do. It identifies where or what a large chunk of the population is moving towards, or trending as we call it. That’s in addition to tracking what people are actually doing about everything, from crime to weather to shopping to brands. Thanks to big data’s capacity for dealing with vast quantities of real-time unstructured data, productive gleaning is a strong possibility.
For example, Wal-Mart and Kohl’s, known retail giants, are making use of sales, pricing, and economic data, combined with demographic to fine-tune merchandising store by store and anticipate appropriate timing of store sales, volume of items that will possibly be picked up, requirement for more salespeople at the store front. eHarmony and Match.com, popular online dating channels, help optimize their matching algorithms to predict who will hit it off and with whom…this means it tracks who has a larger chance of saying ‘yes’ considering there are several, common, factors amongst them bringing them together-caste, creed, education, financial criteria, social requirements, etc. Take for example in the networking space too, Linkedin’s ‘People you may know’ on the right-hand side bar achieved a click-through a rate of 30% higher than any other prompts used on that page making it a hit-service. The number of Google queries about housing and real estate from one quarter to the next turns out to predict more accurately what’s going to happen in the housing market than any team of real-estate forecasters, this especially monitored closely over the last few years. Similarly, Google search queries on flu symptoms and treatments reveal weeks in advance what hospitals can expect flu-related volumes in their emergency departments.
Much of the data that organizations are crunching is human-generated. But machine sensors-are creating a second tsunami of data. Digital sensors on industrial hardware like aircraft engines, electric turbines, automobiles, can sense or figure out “location, movement, vibration, temperature, humidity, and even chemical changes in the air. India’s Unique Identification Authority of India (UIDAI) project has set up a public data portal in enabling transparency for improving its operations. Using data to enhance decision-making capabilities and informed decision-making is at the core of the rationale for the public portal.

The Know-how

Will the net of all this be a cold quantitative world? Rather, as marketers and machine systems learn more about our attitudes and behaviors, they’re likely to achieve greater intimacy with consumers than ever before. Yes, there is the risk of an Orwellian nightmare, if the inferences from big data become too intimate and too intrusive and are misused. But there is also the opportunity to deliver services and marketing with unprecedented precision and accuracy, meeting and exceeding customer expectations in better ways, at every turn. Knowing the how to deliver the right message (or action) in the right place before the time has come will ensure extraordinary power to those who use such intelligence, with intelligence. ‘Use the art of prediction wisely’, and big data has the potential to make the world small again. This is every marketer’s dream: getting closer to customers.

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Emerging Trends on Big Data:
Some of the emerging trends on big data are: Prognostics and Warranty management to reduce downtimes, warranty costs and improve customer satisfaction, Device Health Analytics solution pack to utilize big data to analyze device health for Hi-Tech industries, Vehicle Sales Analytics to help an OEM leader effectively forecast demand for its vehicles at various locations, vehicle add-ons, plan marketing campaigns etc, Customer Sentiment Analysis, Supply Chain Optimization based on SAP HANA to enable organizations to take a top-down view of key supply chain metrics and analyze their interdependencies.

Supply Chain Risk Management: It provides a geo visualization tool for understanding the risks associated with the failure of supply chain node(s) within an organization, Asset Utilization meant for asset-intensive manufacturing industries for tracking and analyzing key performance indicators related to maintainability, financials, inventory utilization and sustainability, and lastly, RFID Tracking: A visual analytics tool based on SAP HANA to provide real-time tracking of RFID-enabled shipments and analysis of discrepancies/counterfeit.

Some of the upcoming initiatives across the industry include Big Data in Industrial Automation, Big Data Beta in Oracle 12c, Machine Health for Heavy Manufacturing Industries, Supply Chain Analytics, Big Data Visualization, Big Data (Hadoop) and SAP HANA Solutions, etc.

 

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