By Jennifer Henderson

This blog post is our third Question and Answer (Q&A) session (see the previous two here and here). In this Q&A, Dr. Garcia discusses “big data” and its importance to business. Dr. Garcia also recently wrote an article on big data for The Free Lance-Star. In addition to working at the University of Mary Washington in Fredericksburg, VA, Dr. Garcia is a partner at Blueshift Analytics LLC, a small company that specializes in providing advanced analytics consulting and technology development.

What is big data?

Big data refers to the vast quantities of data that are constantly being produced from myriads of different sources, such as social media, blogs, sensors, satellites, and transaction records. Big data is often characterized by the so-called “three Vs”: big volume, big variety, and big velocity. Here, volume refers to the sheer quantity of data. Variety refers to the many different data formats and lack of structure, which is in contrast to traditional enterprise data warehouses where all the data is cleanly formatted in database tables. Velocity refers to the rapid rate at which the data is produced, as much of big data is constantly coming in near real-time (think Twitter). The data itself is important, but the real task is to discover important insights in the data, which is no small task. So much of what falls under the term “big data” has to do with analytics, the application of advanced statistical and algorithmic methods to extract useful and non-obvious insights from the data.

What is the connection between social media and big data?

Nearly everyone is on some form of social media, and people do it not out of compulsion but because they like it. And because social media is all digital, it constantly produces tons of useful data containing information on peoples’ attitudes, shopping habits, political views, and many other personal tastes. Social media has become one of the richest sources of useful insights and interactions with customers, so organizations are constantly applying big data analytics to social media data to gain new insights into their customers and improve their business strategy.

Can small businesses use big data; and, if so, how?

Yes. However, small businesses typically don’t need “big” data or sophisticated analytics, they really just need to become savvy in using data to make better decisions. It starts with defining and tracking a few clear metrics that accurately reflect how well the business is performing on important dimensions. These can then be used to gauge the impact of different strategies and lead to better results. For instance, many companies track website hits, but another important metric often not tracked is conversion rate (the percent of customers who visit the website and eventually purchase/sign up). Another important metric might even be to look at average conversion time. After tracking metrics like these, the business can start analyzing how the metrics relate to revenues, and from there figure out what the business needs to do to improve these numbers. Another way small businesses can apply big data approaches is in measuring social media impact and responding accordingly. This entails tracking hits and response rates to social media promotions, along with the different interests and demographics of those who respond and don’t respond. This will enable discerning many different customer segments and figuring out which segments will respond to which types of promotions.

Can non-profits use big data; and if so, how?

Yes, in much the same way as a small business might. Nonprofits often rely on volunteers and donors. A strategy to recruit volunteers using social media would be functionally very similar to a social media-based product promotion campaign, where hit and response rates are tracked and correlated to demographic and other segmenting attributes. This can be used to tailor recruiting to appeal to individuals’ tastes and preferences and result in increased numbers of volunteers. Donors are also very important, and nonprofits can track detailed data on their donors—how often they have been contacted and by whom, how much they gave and how often, in response to what, demographics such as age/gender/political affiliation, special interests or memberships, etc. Predictive analytics can then be applied to determine the best approaches and frequencies to request donations from each donor to maximize the expected yield. A similar approach could also be applied to tracking and analyzing volunteer data to improve their retention, just like keeping customers happy. There are really a lot of ways nonprofits can improve performance through data-driven approaches.

What technologies exist to help small businesses and non-profits extract data for use in targeted marketing?

There are a lot of excellent low-cost or free tools out there. For social media, HootSuite is a great tool that has a basic version for free. It allows you to schedule social media posts simultaneously on multiple platforms (such as Facebook, Twitter, etc.) and track the click rates. It will also perform some basic analytics for you, including determining the best times to post in each media platform to maximize hit rates. For doing data summarization and visualization, MicroStrategy is a great choice. There is a free desktop version that is easy to use and provides a lot of functionality. MicroStrategy can produce some amazing data visualizations. It also allows sophisticated dashboards to easily be created and shared on the web. If more advanced analytics are needed, Weka is a great platform that is also free. It is essentially a data mining and machine learning toolbox, and also supports data fusion through intuitive drag-and-drop data flows. Weka does not require programming, but it does require a little knowledge of what different machine learning methods do, and how they should be applied. So, a novice will probably have a little learning to do first.