From digital marketing and mobile commerce to websites and social media, marketers today are inundated by data amassed from consumers via searches, purchase histories, price-scanning apps on mobile phones, and comments on Twitter. Combine that with data about in-store traffic, conversations with call centers, and updates from suppliers, and today’s marketers confront a daily flood of information waiting to be sifted for nuggets of intelligence.
Because of big data however, marketing no longer means targeting a big demographic group. Companies need to understand each individual so they can tailor real-time campaigns, pricing, and promotions across thousands of offers that are individualized for millions of customers. With data analytics, marketing is becoming more appealing, less intrusive – more like a service.
This presents a big opportunity for technology firms like IBM that can help marketers tap the huge potential of big data, yet manage its complexity. IDC estimates the market for big data technology and services will grow at an annual rate of nearly 40 percent to reach $16.9 billion by 2015. Last year alone, IBM committed $100 million in R&D on new technologies to help clients analyze massive amounts of data over the next five years.
From a customer perspective, big data can provide a key competitive advantage and allow companies to better understand their operations and their clients. Integrating big data and applying context, patterns, and intelligence can drive new business efficiencies and deliver a better view of the customer. This data-driven marketing is still in its infancy, but there are some industries ahead of the pack.
Vestas Wind Systems, for instance, is a Danish company that sells wind turbines. It uses analytics on big data to determine weather conditions. Turbines are multi-million dollar investments, and Vestas’ customers want to know what kind of return they’re getting. The company looks at a wide variety of structured and unstructured data ranging from its own massive databases to public weather data repositories on the web, and from sensors attached to its wind turbines. The company can analyze as many weather or weather-related factors as it can dream up including wind speed, temperature, humidity, atmospheric pressure, precipitation, and even turbine blade performance. This process used to take several weeks, but using big data analytics, it now takes under an hour. Vestas expects its data sets will grow to 20-plus petabytes over the next four years.
XO Communications is a leading provider of advanced broadband communications services and solutions. It has reduced its customer churn rates by 60 percent through the use of analytics. The software has saved XO millions of dollars by uncovering deeper insights into customer behaviors, spotting trends, identifying those likely to defect, and taking proactive actions to keep its most valuable customers. The challenge is to identify customers who are at the highest risk of churn before they switch to another service provider. The company compiled more than 500 data variables on its customers, and used the software to identify specific trends and correlations in those variables that were the most predictive to voluntary churn. By applying those results to its current customer base, XO can accurately predict and proactively engage with the most valuable and profitable customers who carried the highest churn scores.
Making sense of big data to uncover the right information is a key challenge for all industries, but it also brings great opportunity. The winners in the era of big data will be companies who unlock their information assets to drive innovation, make real-time decisions, and gain actionable insights to be more competitive.
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