Does Big Data Make You Fat?


[YouTube 11:51]

Probably not, it does make you complacent. How? By thinking that the data you have is not helpful. Nothing could be farther from the truth. Helping us demystify the distance between data and business intelligence is Robert J. Moore, CEO of RJMetrics.

After talking about how to start a company by replacing your own job, how Fab.com raised $40 million with data, and where is the line between relevant and spooky? For the final installation of our series of videos on utilizing data, Moore talks about the pass along value of brand marketing.

We keep taking about how everyone is connected online, and thinking about family members and circles of friends helps you make good use of resources.

Going beyond targeted messages helps brands develop affinity and potentially get pull through of its products via evangelists. It's something to think about as you develop your digital strategy.

My second question in this segment is how do I buy smart when it comes to data services? What kind of things do I need to think about as a CMO or VP of marketing when I'm looking into investing in a service provider?

Starting with the low hanging fruit is a good approach. Think about the data you already have and the opportunity you have to take a look at the categories of information you have: Who your customers are, what they're buying, etc. For RJMetrics, $500/month buys you a pretty good deal.

Understanding what is already there allows you to vet your assumptions and figure out a direction where you go deeper.

Doing your due diligence is critical with all your buying, and this is no exception. The first thing you need to look at when selecting providers of business intelligence packages is whether the company is experienced with your particularly industry segment. Do they know where to look and how to think about similar processes to yours?

This is not just about best practices. RJMetrics works with eCommerce companies, especially startups, and those have specific information needs. How you go about making intelligence decisions in such a company is quite different from an auto manufacturer, for example.

Domain expertise and the newness and degree to which the company you're evaluating is taking advantage of technology advancements that have come in the last few years. Are they leveraging the cloud? Are they leveraging distributed computing? Is there a data requirement that will dictate people flying in and working on site on your huge data warehouse?

It's very easy to get wrapped in a very large project that would take a year before you get the first answer. Where business intelligence is going is much lower time-to-value. Because what you need to do to be smart with data is iterate. Have we asked the right questions?

If so, we now have answers we want to keep an eye on and be adapting to the interest we're getting, or maybe we haven't asked the right question. In that case, we want to completely reorient what we've been doing and ask different questions. You don't want to wait another year to do that.

The agility of the software and the team you're working with is very important.

At the workshop, Moore will be addressing how you can utilize what you have. Forget big data, are you doing small data? Are answering questions from the data available today?

There is tremendous opportunity to disrupt entrenched assumptions and come out ahead through business intelligence and data. We think workshop attendees are among the people energized by the possibility of handling massive amounts of data at a very low cost.

RJMetrics works with massive retailers and with pre-revenue generating companies that only have the first couple dozen customers and the same analytics, the same caliber business intelligence can be delivered. This was not the case even five years ago.

If you're a very big retailer, you should be paying attention to the fact that the people who may be disrupting your space are doing very sophisticated data analysis. And you should be thinking about asking the right questions and iterating and not getting bogged down in long processes.

The speed at which data analysis can become business intelligence today is allowing more companies to get a jump start in an industry and become serious contenders quickly.


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