While the buzz around big data seems relatively new, big data has actually been around for years. Decades, even. So why all the hype now? Although it has a long history, before we had computers, software, and the internet at our fingertips, collecting and managing big data—much less analyzing and implementing it—was a monumental manual chore.
Right about now, you’re probably thinking, “But how does this apply to me? I’m a small business owner focusing on the B2B customer. I don’t have any big data.” Chances are good that you’ve got amazing amounts of data, right at your fingertips, and could easily use it to power your growth in the coming year. Let’s take a look.
What the Heck is Big Data, Anyway?
The name couldn’t be more straightforward. It’s just that “big data” is a shorter and easier handle than “tons and tons of information,” which is exactly what big data is. To be a bit more technical, it’s “extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.”
Incidentally, that definition comes from Google Knowledge Graph, which is a collection of big data.
In addition to the data itself, big data can refer to, as Oracle explains, “a holistic information management strategy that includes and integrates many new types of data and data management alongside traditional data.” In other words, the tools you use to collect and manage data.
But how do you distinguish big data from traditional data? With the four Vs:
- Volume: The amount of data. Simple, right?
- Velocity: The rate at which the data is collected. The more data, the faster it comes in.
- Variety: The numerous types of data that can be collected, including sources such as text, audio, and video.
- Value: Here’s where it gets tricky. Not all data is valuable. Identifying the relevant information and pinpointing trends is what creates actionable insight.
How to Collect Big Data
Before you start burying yourself in all that data, you have to complete one crucial step: Identify the question the data will answer. This is particularly important for the small to midsize B2B businesses with limited resources. Before you spend more time or money than you have on collecting big data, make sure it’s going to be worthwhile.
Do you want to know who your customers are? You need to collect demographic information. Need to assess how many widgets you sold last year? That requires sales information. Interested in how your customers find you? Conduct a survey to create a collection of local search insights. Knowing the why first will allow you to focus your data collection efforts so there’s less to sift through, and what is collected is more likely to be valuable.
Once you know what data you want to collect and why, you’re in luck because you have numerous data collection and analysis options available to you. The great news is, many of those options are free. Twitter Analytics, Facebook Insights, Google Analytics—they each cost nothing, and all offer juicy bits of data you can use to grow your audience, and in turn, your business.
More great news for B2B business owners—some of this data collection and implementation can even be automated. For example, Facebook ad retargeting uses information collected when users visit websites to then serve up corresponding ads when that user visits Facebook. Big data helps put your products in front of a potential audience, and you didn’t have to lift a finger beyond setting up the retargeting campaign!
Put Big Data to Use
Congratulations! You just collected a ton of big data. What are you going to do now?! Well, provided you took the time to identify the questions you wanted answered, thereby collecting the relevant data, now it’s just a matter of organizing, analyzing, and implementing.
Data organization can be accomplished as simply as importing it all into a spreadsheet. If you’re a Microsoft Excel whiz, you can use that imported data to create pivot tables, which allow you to determine the significance of a large data set and then automatically summarize, analyze, and explore that data. Put more simply, a pivot tables helps you answer questions about your data.
For example, let’s say you’ve collected a large set of raw sales data that contains numerous bits of information, such as sale date, customer name, city, state, product, quantity, and price. Let’s also say you have about 5,000 entries. The last thing you want to do is manually scroll through all those entries to figure out what the data means and how to use it.
With just a few clicks, a pivot table can show you the sales data by date. Did sales pick up around a certain time of year? Maybe those sales coincided with a certain holiday or event. Now you can use this knowledge to market your business more aggressively in the time leading up to that event, potentially increasing your sales.
Is one product outperforming another, similar product? Perhaps you find the poorly performing product has a flaw. Now you can address the issue and inform your customers. They may be more likely to stick with you rather than switch to another product if they know you’re being proactive.
You don’t have to be Amazon.com or Coca-Cola to use big data to grow your company. But understanding its value, and knowing how to collect and use it will become immeasurably valuable for that future growth you’re building now. And if you don’t have the resources to do this internally, consider working with an outsourced marketing pro who can. I know just where you can find one…
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This post was first published on V3Broadsuite.