Not long ago, getting a feel for the customer was more a matter of art than science. Today, with the proliferation of technologies that inform, connect and empower people, companies have turned to Big Data analytics to get to know their customers better. Through data-driven marketing, vast pools of rich multi-structured data can yield new information and insights into customer wants, needs, attitudes and behaviors—insights that can help companies direct their products and services toward enhancing the customer experience.
While a data-driven customer approach is primarily scientific, the art is in the application. And that’s where CIO’s, CMO’s and CEO’s, come in. Here’s a look at the main types of customer Big Data that C-level execs want to know—or at least know that their IT departments know—in order to create more meaningful and personalized interactions and gain competitive advantage.
Sentiment Analysis Data
With the explosion of social media, customers have gained a voice and a platform to communicate their likes, dislikes, feelings and attitudes about anything and everything—products and services included. This sentiment or opinion data is critical for C-level execs to know, as it can provide valuable insights to inform new, better and safer products and services. In addition, unstructured sentiment data gives corporate execs a clearer picture of how consumers perceive the brand, allowing them to make better decisions to promote and maintain a solid image.
The analysis of rich customer data stores provides critical insights corporate execs need to make better decisions. However, with the democratization of Big Data, true competitive advantage lies in the ability to capture, process and analyze data in real-time as it streams into the system. Real-time data analysis means faster time to insight, which in turn means faster decisions and reaction times. Knowing that the company is leveraging real time data to gain fast insights into customer experiences and behaviors is critical for C-level execs, as real time analysis offers the speed and flexibility that key decision-makers need to take quick action to optimize the customer experience and stay ahead of the competition.
The mobile explosion has created a huge opportunity for companies to get to know their customers better by using Big Data analytics to gain insights from the massive amounts of data that customers are generating on mobile devices. By adding location data to the mix—through the use of geo-location technologies—companies gain a greater advantage by observing customer activities and behaviors at a granular level—in real time. And by using Big Data analytics to instantly combine social sentiment data insights with location data, companies can engage consumers like never before through hyper-localized, personalized and meaningful interactions that take place in real-time and in context. Recognizing this game-changing advantage, C-Level execs will want to know that their organizations are utilizing location data.
Is All Relevant Customer Data Being Utilized?
That’s a question that all CMO’s should be asking. After all, underutilized data can hinder a company’s efforts to truly know their customers and better meet their needs. Of all data collected, 20% is structured and easily analyzed by traditional means. The other 80% is unstructured content, such as photos, videos, and social media posts—content containing a treasure trove of information about what consumers are doing, where they’re going, what they’re saying and where their true interests lie.
The ability to use Big Data tools to gain new insights by fully leveraging all unstructured data is a major advantage that savvy CIO’s and CMO’s will want to take advantage of. Big Data solutions, such as Qubole Data Service, will allow organizations to extract maximum value from all data in an easy, cost-effective manner.