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Agile Computing Authors: Liz McMillan, Lori MacVittie, Darren Anstee, Peter Silva, Roger Strukhoff

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How effective is your Big Data strategy

No doubt you’ve seen the stats and heard about the rapid advance of Big Data, how data doubles every two years, and the ginormous amounts of data that will be tracked as more and more physical objects get connected to the Internet. We all get that Big Data is huge and that it’s a key market differentiator today.

 

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But what does all this mean on the ground, in the day to day activities of the small business trying to survive? How effective is your Big Data strategy? Your initial response may be that your data is not that “Big.” Okay, that’s well and good, but how effectively are you leveraging the information you DO have? Are you capturing 360 degree customer insights and what people are saying about your products, brands, and services? Do you even have a strategy in place to begin with?

 

If any of the answers here are “Don’t know” or “No” or “Not very” then your business is at risk of being left in the dust. Stakes are too high in this economy to skimp on this critical market. Your organization needs to organize a Big Data strategy, and fast!

 

The first obvious step is to take an inventory of your Big Data efforts. Be honest and ask if there’s a substantive effort to capture and use your in-house data. If not, then where do you fall short and where can you improve? To help assess your current Big Data initiative, we’ve included a set of guidelines that can serve as a reality check on your efforts (or lack thereof!).

 

Big Data IS for small business: Get over the myth that Big Data is only for enterprises. As one analyst has well stated, “Big data is a relative term. Every organization has a tipping point, and most organizations – regardless of size – will eventually reach a point where the volume, variety and velocity of their data will be something that they have to address.”

 

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Formulate your business problem: Define exactly what your business proposition is or what hypothesis you want to prove or disprove? Look across the organization at your KPIs and ask stakeholders to weigh in to address where to cut costs and improve revenue. For example, you may start with something as simple as increasing engagements on Facebook? In that case, you’ll want to see what kinds of posts are getting the most likes. How about posts containing images?

 

Identify your data: Figure out what types of data are required to answer your business question. Some basic things you’ll need to explore are the variety and types of data available to address your business question? You will also need to know if there’s enough data and enough history and granularity in the data to support your analysis. For example, if you want to know the best day and time of the week to kickoff your email marketing campaign, then you’ll need to look at your email open rates.

 

Kickoff your analysis: This may be as straightforward as using Google Analytics to get insights on where your web traffic is coming from, what pages visitors are looking at, on what devices, and what the general traffic patterns are looking like. If you’re doing email marketing with a tool like MailChimp, then start by reviewing your email open rate statistics. How about leveraging the growing numbers of predictive analytics tools on the market today. Whatever approach you take to analysis the best advice is to start small, gather some results, and scale up. There’s no need to boil the ocean to find what you’re looking for.

 

Act on your findings: What action is your analysis driving at? If your data shows more email open rates on Wednesday, then try starting your next few email marketing campaigns on a Wednesday to see if your results match the initial findings. If you’re finding that a good number of visitors are using mobile devices to access your website, then take measures to ensure that your business is mobile friendly. Is your website responsive web enabled for different devices? Your initial actions may not lead to the results you expected, and that’s okay. Just keep trying and don’t give up! Also, be sure to get commitment up front from other business stakeholders to ensure that the final results are appropriately applied within the organization.

 

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Be ready for the Internet of Things: IoT will radically change your Big Data strategy. Many companies are already jumping on the Internet of Things bandwagon and for good reasons. McKinsey Global Institute reports that the IoT business has the potential to deliver between $2.7 and $6.2 trillion of revenue by 2025.

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Hovhannes Avoyan is the CEO of PicsArt, Inc.,

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