How Big Data Boosts CRM and Marketing

Loraine Lawson
Slide Show

Seven Ways to Get Started With Big Data

Jill Dyché (@jilldyche), vice president of Thought Leadership at SAS, explains to IT Business Edge’s Loraine Lawson how Big Data can help marketing and customer relations reap more value from their CRM tools.

Lawson: You wrote the column, “Big Data’s Three-Legged Stool,” about meeting a marketing person with the iPad at the Strata conference. I was surprised that she was attending a Big Data technology event.

Dyché: The industry buzz is that Big Data is a business problem and so that message gets distilled and business people are like, “I should know about this.” Somebody hears something about unstructured social media data or call logs and thinks we need that data and we need sentiment analysis.

It’s fascinating to see the reality versus the hype. Business people are in the middle saying, “Wow, I should be doing this stuff, I should know this stuff, but here I am.  Listening to all this messaging around why SQL is dead.”

Lawson: So what should business people know in terms of what we can actually accomplish with Big Data; what can be done to deal with business problems?

Dyché: There's just been a bunch of business problems that we have not been able to address cost effectively before. And now SAS — and SAS isn't by any means the only vendor that's saying this message — but now we've got the hardware and the software solutions, as well as the partnerships. SAS is partnering with Greenplum and Teradata.

We can now do the complex processing of super large amounts of data, and different types of data — new unstructured types of data — with superior price performance compared to traditional RDMS technologies. This can save you time, money and skills. So between SAS' new platform and processing capabilities and SAS’ new data visualization capabilities, the cost to enter is cheaper.

Then, it’s easier to get up and running. SAS has been traditionally seen as a very heavy-weight-engine kind of solution for a range of business functions. SAS excels at risk, it excels at fraud, it excels at predicting customer behavior, but now SAS can excel at anything you can imagine and you can get the data for.

Lawson: What does that mean from a business use case perspective?

Dyché: From a marketing perspective, and really from a customer relation’s perspective, it’s the data that they haven't been able to get until now.

It's no longer just about customer names, address and purchase history; it's about what customers are doing on social media, who the influencers are, how to take the company's brand more viral and use customers as raving fans, to expand out and enrich those relationships through new data, and then modify. The companies that are doing this very well are modifying their outreach accordingly.

So my message to my key influencers on Twitter may be completely different from a marketing and branding perspective than my message to customers that have been around, in the case of an insurance company, for 20 years, right?

Lawson: Does anyone use the data with the CRM tool -- to enrich or correct CRM?

Dyché: CRM systems are great data sources for the core data about customers, and so I may load my CRM data into a Hadoop cluster and then very, very quickly and efficiently match it to the social data or the Facebook data or other types of data — the call detail record, usage data in teleco. So data that may not be linked yet, Hadoop is optimized for processing that kind of data, where I can do a lot of very, very quick and efficient customer matching records with more master data type records.

That whole sentiment analysis, being able to see which demographic segments like us best, and drilling down into micro-segments: This stuff can be really compelling to marketers.

Lawson: And that’s possible now?

Dyché: It's possible to get it down to micro-segments. Do I want to actually identify individual customers and link them to all that other transaction history? Maybe, maybe not.

But what it is possible to do is to have more segments of fewer customers to make the conversation that much more relevant. The whole drama around CRM 15 years ago was about at the end of the day my CRM system is just automating my phone book. It's not necessarily helping me drive insight into specific segments of customers and their specific purchase behaviors and preferences. Now with Big Data, we can not only do that, but we can drill down on even more behavioral detail very, very quickly.

The thing BI and data warehousing market in particular tends to miss is we're always going back to customer and product data. That's just because it’s what we're used to, and, frankly, when Big Data is talked about in the context of customer data that's normally because that's what executives are interested in.

But the applications of Big Data really do transcend customer and product. We're looking at things like human genomes now and the division of cancer cells and DNA sequencing, sensors in oil wells, and all that stuff. I think that from an adoption standpoint, the use cases for Big Data are really only limited to our imaginations for our business.

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