5 Ways for Small Business to Jump on the Big Data Train

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The idea of something that’s being called “Big Data” has definitely reached the trend tipping point. Tech firms like are all about it. PR firms are forming teams to promote it and consulting firms have their business technology teams all over it.

So, what is it and what does it mean for small business.

tsuda via Flickr CC

The “what is it” part is pretty easy to explain in textbook terms, but the hype that’s currently surrounding the idea makes it much harder to bring down to practical application.

Initially the idea of Big Data applied to organizations that had such large data sets they could no longer work with them internally to analyze things like customer buying patterns.

The broader sense of this term and the one that is gaining steam of late is the ability to mine and analyze public data as a business opportunity. Google for example has been able to analyze the rise in the number of searches for flu related phrases to help the CDC pinpoint where to supply flu vaccine in near real time.

Companies are creating new tools such as Affectiva to help measure customer emotion and identify trends and opportunities based on social signals.

In many ways we’ve become a society of data producers – every email, tweet, blog post, status update, link, purchase, listen, download and review is generating data about what we think, how we act and maybe even what we want for breakfast.

The rush to make sense and profit from this information is driving a lot of the buzz surrounding Big Data.

But, here’s what I think this means for small business. While a great deal of the talk is centered on enterprise solutions there’s a great opportunity for small business to benefit from the coming set of tools and appliances aimed at helping us tap into the minds and data of the market.

1) More cloud integration – The adoption of cloud based tools for things like CRM, project management, file storage, backup, email, customer service and accounting means that integration of all of these various data set, even for the smallest of businesses, will become much easier.

The idea that everyone in the organization can have access to files that may live on a coworkers laptop or see customer history from inside an inbox is stuff that used to cost hundreds of thousands of dollars in hardware, software and consulting time. Now this kind of access is becoming a cloud based solution that people tackling big data will make available to small organizations for very little investment.

2) Culture of measurement – Before access to more data will serve any purpose there needs to be a culture of measurement and analysis. Most small businesses don’t measure or lead based on objectives, goals and metrics.

Until a business of any size gets serious about listening to their customers, talking to their customers, and measuring every possible data and touch point, the promise of more data will only serve to distract.

Unless you get hooked on small data – things like routinely asking your customers what they think – big data is just more noise. In fact, what I call small data, actually talking to your customers, is a real advantage that small business have. I think some of the appeal of Big Data for large organization is that it shields them from actually having to interact with their customers.

The real value for the small business that builds a culture based on data will come when services like those from ClearStory that aim to help organizations integrate their own data with existing large public databases, become commonplace.

3) Know what you need answers to – Actually, we’ve always had access to reams of data, the real trick, and this will prove so for enterprise as well, is knowing what to make of the data. Proper analysis is more important than more data.

The trick for the small business is knowing what it is your trying to find out or knowing what answers you’re trying to find. One of the best ways to analyze data for a small business is to go into it looking for something.

Spend time up front asking your customers and your sales team about things they don’t have, things that don’t make sense, things that always bug the customer, and things that they are seeing and hearing more and more. This is how you make sense of trends that might come from research in public data sets like Google Insights and Google Public Data.

4) Walk before run – The first place you need to start is internally. Until you get a handle on your own data, you shouldn’t concern yourself with the cool new tools that might help you make sense of more data.

So, for most small businesses this is going to mean creating a dashboard of key metrics and installing tools that give you real time access to the data that would allow you to measure simple things like, leads generation, ad conversion, and cost to acquire a new customer.

Starting with some of the more robust website analytics tools such SpringMetrics (a client) and KissMetrics is how you gain insight into this craft. Learning how to test and measure your ads, headlines and offers is an essential data collection starting point.

Like so many things about business, until you build a strong foundation based on real customer interaction, you can’t build on top of it with the latest and greatest.

5) Hire a numbers nerd – data mining and analysis is essentially math and, well, some people excel at math and some at art.

Every business needs a numbers person – the one that can look at what seems like a pile of unintelligible digits, charts and graphs and sees music. Look for a proliferation of data marketplaces like Infochimps to crop up and offer access to data integration in a candy store kind of way for your numbers person.

From a practical sense this person probably needs to also know how to install and write a little code, read a P/L and create processes that allow you to build, track and measure a sales pipeline, but find the right one and your business will change forever.

Hint: If you’re college right now think about data analysis as a major!


Tags

Affectiva, Big Data, ClearStory, Google Public Data, Infochimps


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