Big Data: What Small Businesses Don’t Understand

Originally Published by by Sara Angeles, BusinessNewsDaily Staff Writer   |   July 28, 2014 11:06am ET
Confused about Big Data? You’re not the only one. For most small business owners, Big Data is one big mystery. And if you don’t understand BigData, you probably also how no clue how this type of intelligence gathering works or how to start extracting valuable information from data sources you already have — which means your business is missing out on big opportunities.
To help you make sense of what Big Data is all about and how it can aid you in making better business decisions, here are five of the most baffling things about Big Data demystified.

1. What Big Data actually is

“Ask one hundred different executives and you’ll find one hundred different answers,” said Kevin Woo, president of digital analytics firm Pointmarc. “Big Data is a popular buzz word, but at the end of the day, data is simply data.” [Big Data ‘Escapes the Lab’: Tips for Small Businesses]
Big Data is also inherently confusing, as the term itself may be considered a misnomer. It’s not the size of the data that matters, but how it is used, Woo said. This often confuses many small business owners, particularly those who don’t think they have sizable data as compared to larger companies.
“The size of the data is less important than the integrity or ability to act upon it,” Woo said. “Companies, whether small or large, are collecting consumer data at an unprecedented rate, and the ability to integrate all of the different sources of data and shape it in a way that allows business leaders to make informed decisions is essentially at the heart of Big Data.”
Big Data benefits businesses in many ways, from supply chain logistics to financial forecasting. For the most part, however, Big Data is essentially a means to leverage whatever data sources are available to create a big-picture view of customer behaviors and preferences to personalize experiences, Woo explained.
“If you can gain a holistic view of your customer by connecting all of your different data capture points, you have the opportunity to vastly improve both the immediate user experience and the long-term perception of your brand,” he said. “In the age of the empowered consumer, the execution of Big Data strategies will prove to be one of the largest differentiators for everything from small business to Fortune 500 companies, particularly within retail and media industries.”

2. What Big Data is actually for

Just as many small business owners are confused by what Big Data is, it’s no surprise that many also don’t understand its purpose.
“Big Data is just a fancy way of saying you want to capture as much information about a person as you possibly can and figure out how to make money off of that information,” said April Wilson, president at analytics services provider Digital Analytics 101. “In retail, for example, they might want to know if you open emails, how often you purchase in-store versus online, how often you browse the website before purchasing, what you’re posting on your social media accounts, and if you open promotional emails.”
By not understanding what Big Data is actually for, businesses risk making the costly mistake of not having the right strategy and, as a result, potentially useless results.
“Often, companies stitch together data in a haphazard way, trying to stuff as much as possible in one place, and you get this kind of Business Frankenstein monster that’s out of control,” Wilson said.
To effectively mine and analyze Big Data — and get valuable results — what companies need is a strategy.
“Companies don’t have to invest millions and gather a lot of data to be successful with Big Data,” Wilson said. “They just have to start with a very concrete and focused question they’re trying to solve, think through what data they need to solve it, and go get that data. The end.”
For small businesses, this means figuring out where data can be found and what problems this data can solve.
“[Small businesses] should just focus on all the different data that they have on customers and marry that with their biggest pain point,” Wilson said.

3. How to actually approach Big Data

One of the most baffling things about Big Data is how to get started and how to get the most out of the investment.
“Data that is collected without a particular set of questions in mind is unlikely to be useful,” said Dr. Charles Noon, head of the University of Tennessee’s department of business analytics and statistics. “The mantra should be, ‘ask the right questions.’ The data strategy begins with defining the insights needed to find ways to grow profits. The implication here is that these questions, not the technology, should drive the data strategy.”
For example, consider a company with a customer loyalty program that was originally designed to be a rewards programs, not a strategic data collection initiative. The data that it provides likely answers many key questions, Noon said. These include: Which customers responded to a particular promotion? What other items did they buy when they shopped? What was their total spend? Did the promotion affect the frequency of their visits?
Asking the right questions can also help businesses use Big Data to avoid costly mistakes. One example is a grocery store whose product data indicates that certain products, like gluten-free kosher, organic, etc., are losers because of low sales. However, when such product data is integrated with customer data, it actually reveals that these “loser” products attract many of the most profitable customers, Noon said.
“Focus on the big picture,” Noon said. “This requires an integrated data strategy for collecting and analyzing data.”

4. How much Big Data actually costs

Many small businesses are often confused about how much of an investment Big Data actually requires. Not only are there a wide range of resources at various price points, but there is also the misconception that these tools and data scientists are too expensive for the small business budget.
“Even a small company can have Big Data,” said Mark Herschberg, chief technology officer at Madison Logic, an intent and lead generation data solutions provider. Even if your data isn’t big and you don’t have all the resources that big companies do, you can still benefit from Big Data techniques to get insights into your business, customers or key performance indicators (KPI), he said.
Although high end Big Data tools can be expensive, they aren’t the only solutions available, Herschberg said. “As more and more services move to the cloud you can use Big Data tools for as a little as a few hundred dollars a month,” he said.
Small business-friendly Big Data tools include Hadoop, InsightSquared and Canopy Labs. [Related: 5 Big Data Solutions for Small Businesses]
Another option is to hire a data scientist, but it’s often confusing whether a small business actually needs to invest in one.
“Yes and no,” Herschberg said. “Yes, you need an experienced professional to set up the scripts and/or to do the analysis. However, more and more you can find company and freelance contractors who can do this for you.”
Instead of hiring a full-time data scientist, Herschberg suggests spending a few thousand dollars setting up some analysis of data feeds and then having the consultant come in twice a month to review the findings with you.

5. How Big Data actually works

Big Data can give businesses extremely valuable information, but it doesn’t just exist in its own vacuum or act like a crystal ball that  magically unveils the secrets to success. Businesses need to first make sense of how Big Data works.
“Big Data confusion starts with the misperception that it is some sort of technology — it isn’t,” said Charles Caldwell, director of solutions engineering and principal solutions architect for business intelligence software provider Logi Analytics. “It’s really about using the ever-increasing amount of data to create value for your customers and your business.”
The technologies and analytical techniques used to create such value can be simple or complex, but knowing the right approach to Big Data can make all the difference in making the process less baffling. The secret is to first identify the problem that needs to be solved.
“What makes it all confusing is that many people try to start with the solution, rather than start with the problem,” Caldwell said. Big Data, however, won’t
provide business altering insights automagically, he added. “We’ve seen too many movies in which a computer becomes sentient and tells us what we should be doing. Big Data still requires a person to frame the question, identify the data that might be able to answer the question, and interpret the results to choose an action.”
To get started with Big Data, Caldwell advises businesses to not worry so much about the technology itself, but how it applies to and creates value for your particular business.
“Worry about what really matters in your business, and then ask how the technology might help you execute better around those things,” he said. “If you carry five products, as opposed to over 200 million products like Amazon, you might not benefit from a Product Recommendation Engine. But understanding how customers interact with your website might be critical. It all depends on your business model.”
Originally published on Business News Daily