How Can My Business Leverage Twitter/Facebook Data?

As a BI consultant, I get asked this question (or some version of it) a lot: How Can My Business Leverage Twitter/Facebook Data?


The conversation typically goes something like this:

CIO/IT Director: I read an article in <insert CIO magazine>-weekly that claimed so-and-so used Twitter/Facebook data to do such-and-such and is now crushing the competition.  How can I use Twitter/Facebook data to blah blah something awesome blah?

On one hand, its exciting to see that this company is starting to think about tapping into external sources of data.  It shows they aren’t complacent and are open to making moves…two great qualities in leadership. On the other hand, there are a few problems with the underlying thought process…primarily in the form of application and scope.

Below is my typical response:

Me: that’s a very interesting application of Facebook/Twitter data.  Do you have any specific business problems, questions, analysis that you think Facebook/Twitter data will help with?

Why is it always Twitter/Facebook?

Twitter/Facebook data, I’d argue, are the two most common sources that come to mind for most CIOs and IT Directors when they think of big data. Name recognition leads to publicity which leads to name recognition which leads to publicity, ad infinitum.  But not all businesses are structured in a way to take advantage of social media data. Consider the  B2B (business to business) widget supplier whose clients are other business…not people who spend time on Facebook. How is this company going to increase revenue/reduce costs with facebook/twitter data?

The point is that instead of forcing a big data play using social media sources hoping for a super thin ROI, consider expanding the scope of your big data play by using a number of other external sources…especially ones more relevant and beneficial to the specific business problems you’re trying to solve. For example, in the case of our B2B widget supplier, a better approach might be to focus on distribution efficiency or demand forecast optimizations making use of sensor data from the delivery trucks and/or point of sale transaction history from their customers.

One person’s junk is another person’s treasure…

Another point is that a big data play doesn’t necessarily need to be based on “consumption”.  Similar to the robot-like desire to use Facebook/Twitter data, I think many CIOs and IT Directors think in terms of consumption-plays because that’s the typical use case in most of the published big data success stories.  But whether you’re aware of it or not, there’s a growing market for “producers” of big data.

For example, consider a local utility company that collects data every few seconds (or less) describing the power consumption of customers within the service area. The utility company uses this data to more efficiently allocate power throughout the smart grid which saves them money – perhaps enough money to justify the cost of changing out power meters at every residential customer as well as justifying the cost of the IT infrastructure (i.e. hadoop clusters, devs, etc). What if they could expand the value of this data (which is now an asset) by selling access to these data sets to other businesses?  Sounds cool, but who would be willing to buy it?

How about the big-box appliance retailer. Don’t you think they would be interested to know who might be close to pulling the trigger on a new set of high-efficiency appliances? Imagine if this local appliance retailer had access to the data collected by the utility company and was able to mash it up with demographic data in order to identify high value leads for a marketing campaign. Wouldn’t you be interested if one of your neighbors, living in a similar size home with similar size family, was spending 50% less than you on their annual power bill? I would 😉 And it would definitely be a great piece of information to include in the marketing material sent out by the big-box appliance retailer to entice a sale.

Wrap Up

Hopefully this has peaked your interest a bit and helped to break the narrow-minded association of Facebook/Twitter data consumption being the only big-data play. There are plenty of other sources out there and its important to find one that enhances your competitive advantage.

The other main point in this piece is that “consumption” isn’t the only play to make. Perhaps you are sitting on a pile of data that isn’t very helpful to your business. From an internal value perspective it hardly makes sense to capture and store this data. However, this data could be a pile of gold to some other business (perhaps your customers, suppliers, or any other cog in the value-chain). Data as a service is a real thing and only going to get bigger. For those interested in exploring this further, I urge you to head over to Microsoft Azure Marketplace to get an idea of how one my go about selling access to data.

What are some other ways you’ve see companies successfully use big data?

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