Big Data Provides Big Insight for the SMB
by Kate Smith, Director, Sales & Marketing
Big data is a marketer’s and business decision maker’s dream. With all of the talk about the Internet of Things and the vast stores of data created and available it should be a snap to use the data in a meaningful way to make intelligent business decisions and to understand and predict your customers’ buying behaviors.
Before we delve into the big data conversation, let’s first start by understanding what big data is. According to Lisa Arthur from Forbes.com, “Big data is a collection of data from traditional and digital sources inside and outside your company that represents a source for ongoing discovery and analysis.” (Arthur, 2013) Thinking more about that definition, what sort of data and information actually represents big data? Gartner describes big data in terms of volume, variety and velocity (or the 3Vs), but I prefer the simpler explanation Arthur offers stating that big data is comprised of both unstructured and multi-structured data. According to Arthur, “Unstructured data comes from information that is not organized or easily interpreted by traditional databases or data models, and typically, it’s text-heavy.” (Arthur, 2013) Examples of unstructured data include social media posts, such as Twitter tweets, Facebook posts, and or LinkedIn updates. The other type of data that Arthur references is, “Multi-structure data which refers to a variety of data formats and types and can be derived from interactions between people and machines, such as web applications or social networks.
A great example is web log data, which includes a combination of text and visual images along with structured data like form or transactional information.” (Arthur, 2013)
Understanding where the data comes from is all well and good, but how do you actually harness that data into usable information? A great article from Forbes.com likens big data analysis to that of a factory; the data goes in as raw materials and useful information emerges as the final product. Let’s delve more deeply into this idea. According to Meyer, McGuire, Masri and Wahab Shaikh there are four steps required to generate usable data, “Decide what to produce, source the raw materials, produce insights with speed and deliver the goods and act.” (Meyer, McGuire, Masri, & Wahab Shaikh, 2013)
Before starting any project, it’s important to determine what you are actually looking to accomplish. According to Meyer et al., “Decide what discrete questions your business needs to answer and the actions you want those answers to enable.” (Meyer, McGuire, Masri, & Wahab Shaikh, 2013) After you have made those determinations you can shape your business to yield those insights. “One retailer, for example, discovered that 90 percent of its year over year sales decline was concentrated in 12 percent of its customers in specific markets.
It focused questions, accordingly, on understanding the root cause and quickly reversed the trend with targeted local market merchandising tactics.” (Meyer, McGuire, Masri, & Wahab Shaikh, 2013)
It’s easy to get overwhelmed by the vast amounts of data available for analysis, but a better, more practical approach is to start simply and use the best data that is immediately available to your organization. Meyer et al. states, “Chasing after the ‘perfect dataset’ is time-consuming (and often fruitless) and reduces the ability to act quickly. Instead, start with ‘small data.’ A comprehensive ‘data warehouse’ is a great asset over the long term, but a smaller, more selective ‘data mart’ makes it easier to produce insights fast, preventing you from getting mired in complexity. Over time, you can then layer on additional data sets.” (Meyer, McGuire, Masri, & Wahab Shaikh, 2013) The easiest place to start is with your own customer data and buying history. By reviewing and analyzing buying behaviors it becomes easy to identify trends and predict future buying behaviors.
Once the dataset has been defined it’s crucial not to be consumed by analysis paralysis. When acting on data that has been analyzed, “Productive action is a product of speed. We recommend acting like a start-up. Start-ups are driven by an inherent need for speed that doesn’t let perfect get in the way of good enough. Create small, nimble teams combining strategic, analytical, and technical skills to address specific topic areas rather than single, generalized, and usually slow-moving committees.” (Meyer, McGuire, Masri, & Wahab Shaikh, 2013)
Once usable information has been uncovered and understood, it’s time to act on that data. The goal is to define that now that can be used now to make business decisions. “Making sure that insights drive action requires a clear understanding of what front-line managers can actually use.
Too often, marketers or sales people are provided with data analysis they subsequently ignore. In many cases, the analysis isn’t practical, isn’t clear, isn’t trusted, or isn’t perceived as relevant.” (Meyer, McGuire, Masri, & Wahab Shaikh, 2013) If it is determined that two of your products are often purchased together or within a defined amount of time, create a program around that insight which makes it easy for customers to purchase multiple product lines from you initially.
Once you identify a goal, define the data to be used, produce usable information and then act on that data, it’s important to create a culture where this can continue to happen over time while fine tuning the process and or adding additional data insights into the process. Big data can be an incredibly powerful tool if leveraged correctly. As with anything, seek out a trusted advisor to get your big data analysis program up and running.
Arthur, L. (2013, August 15). What is big data? Retrieved from Forbes.com: http://www.forbes.com/sites/lisaarthur/2013/08/15/what-is-big-data/
Meyer, C., McGuire, T., Masri, M., & Wahab Shaikh, A. (2013, October 22). Four Steps To Turn Big Data Into Action. Retrieved from Forbes.com: http://www.forbes.com/sites/mckinsey/2013/10/22/four-steps-to-turn-big-data-into-action/
About the Author
Kate Smith, SecurElement’s Director, Sales & Marketing is responsible for SecurElement’s overall sales and marketing strategy as well as ongoing partner relationships with organizations such as Microsoft, Cisco, Barracuda and many others.