How to Understand your Customers Better with Hadoop

by   |   May 13, 2016 5:30 am   |   0 Comments

We live in an era when the customer reigns supreme. Empowered by technology – mobile devices, the Internet, social media – today’s customers are driving business decisions and literally redefining sales and marketing. The game has clearly changed, which makes it more important than ever for online businesses to gain a deeper understanding of how their customers think and behave.

Fortunately, technology is empowering businesses as well as customers. Armed with vast stores of rich customer information and tools such as Hadoop, businesses can gain critical behavioral insights that they can then use to better meet customer needs and expectations.

Today’s organizations are being bombarded by massive volumes of customer data streaming in from multiple channels. One of Hadoop’s greatest strengths over a traditional database management system is its ability to store large volumes of unstructured and semi-structured data from disparate data sources. The data sources most businesses tend to focus on include social media, texts, emails, photos, sensors embedded within items, and financial transactions. Within these vast stores of unstructured data is information about customer preferences, habits, and buying behaviors, information to which businesses previously had limited access. The result is a detailed, 360-degree view of who their customers are.

Hadoop is part of a larger collection of open-source tools that can be used together to meet business objectives. This easy integration keeps organizations agile and versatile, able to adapt to changing data types quickly. Many organizations use Hadoop for initial capture and storage of these disparate data sources. These vast data stores, frequently referred to as data lakes, are then parsed by analytics engines such as Apache Spark or Apache Hive. The exact infrastructure and engine used should be determined by the business’ use case. For example, Apache Spark is built to run real-time queries, while Hive or Hadoop’s MapReduce are better suited to batch jobs.

Developing the Full Picture

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Using Hadoop, today’s online marketers can capture customer data from all customer interactions, whether customers interact with their website or web application from a smartphone or other mobile device or from a personal computer. One example of this is clickstream data, a trail of “digital breadcrumbs” that customers leave behind as they navigate a website. It allows organizations to see what exactly a customer does when they are visiting a site. Companies can enrich this data by correlating it with data found in different data stores to connect all of the dots and develop a more complete picture of what the customer is all about. Hadoop’s very architecture enables this ability, drawing from various data repositories simultaneously. These are then fed into whatever applications the organization needs, whether they are business analytics or custom applications. With these capabilities and a detailed picture of the customer, marketers can create messages that are more relevant and targeted to each individual customer.

Going Granular

Aggregated data can reveal important insights. But it also can hide insights that are even more valuable and critical. The ability to perform big data analytics on a granular level with Hadoop allows marketers to gain the deeper behavioral and experience insights they need to continuously improve marketing strategies and provide a more optimized customer experience. Indeed, it is Hadoop that allows marketers to unlock value within new types of data, sources which couldn’t be properly utilized without Hadoop. These types include clickstream and social (as mentioned above), along with historical logs and unstructured data sources. Without Hadoop, the value found in texts, video, website behavioral patterns, and online archived information would remain untapped.

Realizing Real-Time Insights

In the past, marketers primarily relied on historical data to get a better understanding of customer behaviors after they happened, in order to do better the next time. But in an era of the empowered customers and mounting competition, there may not be a next time. Using today’s analytics tools, marketers can gain insights into their customers’ behaviors and experiences in real time by mining streaming data with Hadoop. This is a huge benefit, as it allows marketers to understand what is happening, as it’s happening. Armed with real-time insights, businesses can take immediate and appropriate actions to help ensure an optimal user experience. Hadoop allows companies to scale their analytics efforts efficiently, providing broad insight with simultaneous data access.

Delivering Hyper-Localized Advertising

As touched on above, big data analytics performed through Hadoop allows marketers to gain insights needed to create personalized and targeted ads for their customers. The explosion of smartphones, tablets, and other wearable devices allows marketers to do what they have always dreamed of doing – to deliver the right message to the right customers at the right time and in the right place.

The ability of businesses in the vicinity of potential customers to deliver, through the combination of social data and geo-location data, mobile ads with various incentives directly to the shopper’s mobile device and current location in real time has been shown in numerous studies to increase customer engagement and conversion rates substantially.

The era of customer empowerment is here to stay. And those businesses that are proactive in adopting big data analytics strategies to gain a better understanding of their customers – thus providing better products and services – stand to gain a significant advantage over their competitors going forward.

Rick Delgado is a technology commentator and freelance writer.

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