What is the real ROI associated with big data for marketers, and what marketing metrics does it impact and why?
Marketers are always looking for an edge in their ability to increase targeting precision and improve the relevance of their messages. There is a lot of buzz in the industry about the promise of "big data" technologies and how they can help provide that edge. Big data platforms provide the ability to incorporate and analyze marketing data across multiple audience touch points - be it email responses, site activity, search or display click-throughs, social engagement, location preferences, or behavior across a diverse set of channels. Using larger volumes of cross-channel data assembled in real time dramatically improves the output of analytical models. For example, predictions of propensities would be much better and that has a direct impact on conversion and marketing ROI.
Previously, marketers found this type of cross-channel analysis against large and diverse data sets to be either impossible or too cumbersome to achieve at scale. However, like with any new technology, big data brings with it its own challenges - the costs associated with deployment, lack of available skills in the marketplace, governance, etc. So that begs the question as to what is the real ROI associated with big data for marketers? And what marketing metrics does it impact and why?
We now have practical examples from the first wave of marketers who have successfully leveraged the benefits offered by big data. One thing is becoming clear from their experiences. They are now able to do more with less. For example:
These early results are astounding. They clearly spell out the tangible benefits associated with big data adoption for marketers. They are now able to incorporate more data in their analytics and increase speed of execution with fewer resources than before.
Delivering relevant and personalized messages using digital channels involves a sophisticated ad targeting system. In the below video clip, we explore some of the common misconceptions associated with data-driven ad targeting. We also explore the underlying challenges involved in integrating diverse data sources and running complex analytics in real time and how all of that relates to big data.
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Krishnan Parasuraman is responsible for driving revenue growth across IBM's digital media clients through the use of big data technologies. In his role, he works very closely with some of the largest marketing service providers and digital ad networks in an advisory capacity, driving big data solution architectures and best practices for management of Internet scale analytics. Krishnan drives the technology strategy for IBM's big data product portfolio and is an authority on the use of technologies, such as Hadoop and massively parallel data warehousing technologies, towards solving analytical problems in the online digital advertising, customer intelligence, and real-time marketing space. He speaks regularly at industry events, writes for trade publications, and is the author of the book, Harness the Power of Big Data.
Prior to his current role, Krishnan has worked in research, product development, consulting, and technology marketing roles across multiple disciplines within information management. He has enabled marketing and customer analytics solutions for large media and consumer-focused organizations like Apple, AOL, Yahoo, Microsoft. and Motorola. He holds an M.S. degree in computer science from the University of Georgia.
Hong Kong, May 5-6, 2015
This Magic Quadrant examines leading digital commerce platforms that enable organizations to build digital commerce sites. These commerce platforms facilitate purchasing transactions over the Web, and support the creation and continuing development of an online relationship with a consumer.
Google reports that paid search ads are currently driving 40+ million calls per month. Cost per click is increasing, paid search budgets are growing, and mobile continues to dominate. It's time to revamp old search strategies, reimagine stale best practices, and add new layers data to your analytics.
May 6, 2015
12:00pm ET/9:00am PT