This is the continuation of the transcript of a podcast hosted by InetSoft on the topic of "Big Data Analytics." The speaker is Mark Flaherty, CMO at InetSoft.
So when you talk about what is the opportunity for big data technologies to improve a company’s performance, and what we don’t see organizations doing much of, yet, what you might call the next frontier, is not just analyze the transactions that happen from those interactions online but get a better sense of customer behavior and customer interactions that precede a transaction. The state of the art for most marketing teams today is looking at last click attribution.
Whatever Web page you were on right before making a product purchase, that Web page gets a hundred percent of the credit for the marketing campaign measurement for driving that transaction. We know that is just not true. Most consumers, no matter what they’re buying, whether they’re buying a pair of shows, a new pair of pants, it’s going to take them six to eight different touches from an organization before they make a purchasing decision.
So getting smarter about how we not only get visibility into consumer behavior, but how we actually quantify what impact interactions have had with the consumer before is really important to bringing the science of data into the art of marketing.
How does a MapReduce platform address the business challenges of online marketing optimization? I think the great news for enterprises that want to adopt a big data platform is now it’s easier for business people to gain access to these analytic techniques, and make it easy from the perspective of not only allowing them to use the business intelligence tool they are already familiar with to access these analytics, but also prepackaging a lot of the logic around easy analytics into SQL MapReduce modules.
So for digital marketing optimization, there are suites of many different analytic modules that work together to deliver everything from taking raw Apache Web logs into a data warehouse and parsing those on the fly in a very agile way, to performing analysis on click stream logs, to looking at the pattern analysis that gives you deep insights into consumer behavior through those interactions on a Web site or even across channels.
There are also modules that deal with marketing attribution so being able to cross that last mile and do some ROI calculations for the marketing department so you know how to change their budget. Those are just some out of the box analytic solutions. If you think about what can be built by skilled data analysts and BI developers, it’s quite amazing.
To talk for a second applying big data analytics in a specific industry, think about telecommunications with the trillions of call detail records to data mine. It’s not just voice calls, right? You’re looking at the entire expanse of what is coming across the mobile data platform, how people are using their iPhones or other devices, what are they purchasing with them. It makes a great way to make some of the ideas that marketing professional have possible with the big data technology that is available today.
It’s really executing on the vision of a customer-centric approach to marketing, and we’ve been talking about that for a very long time now, but we’re finally getting access, not just to the data sources, but also the analytics. And last but not least the ease-of-use of the analytic BI tools has improved to the point of making these amazing marketing intelligence applications possible.
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