Empowering Growth Hackers with Big Data

Empowering Growth Hackers with Big Data

Empowering Growth Hackers with Big Data
To improve their growth rates, some up-and-coming companies are turning to a pursuit known as growth hacking. Growth hacking brings together the ideas of hacking big data and driving business growth. By one common definition, growth hacking is a process that drives rapid experimentation across marketing channels and product development to identify the most effective, efficient ways to grow a business.[1]

Growth hacking often leverages customer data in the experimentation process, in the form of A/B testing. The goal is to use big data to gain a better understand of the customer, via a complete view across every touch point of the organization, in order to enable an optimal customer experience. Growth hackers—who can be anyone from marketing professionals to product manager and engineers—are seeking insights to help optimize marketing campaigns across channels, increase customer loyalty and retention, and enhance the customer experience.

While it is a fairly new pursuit, growth hacking already has a lot of momentum. This momentum is apparent in a Google trends analysis, which shows growing interest in growth hacking and declining interest in marketing:

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Although they don’t necessarily use the term, many tech-savvy organizations are actively using the techniques of growth hacking to capitalize on cross-channel data and drive business growth.

Here are a few examples:

As these examples show, the requirements for capitalizing on multi-channel customer data begin with a data lake that brings together structured, unstructured, and semi-structured data for analysis. Hadoop is ideally suited for this role. An enterprise data hub (EDH) based on Hadoop provides a centralized platform for organizations that want to consolidate data to create the 360-degree customer profiles that are key to growth hacking.

The EDH also enables the growth hacker to analyze data and derive insights that can be put into production.

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