Data from and about consumers is growing exponentially. Some estimates place growth at 2.5 quintillion bytes of data per day. A key factor in this growth is the popularity and widespread consumer adoption of technologies such as social media, cloud computing, wearables, and the Internet of Things (IoT). Consumers connect their homes, entertainment devices, vehicles, smartphones, smartwatches, and more to the internet and to their friends and families. All those connections create a stunningly detailed data set that captures what consumers do every minute of every day.

Businesses are looking to data analytics to turn these vast amounts of data into actionable customer insights. This process entails choosing a suitable analytics solution. However, the umbrella of data analytics covers many solutions. Each works best with data from particular sources, and each delivers specific types of insight. It is no surprise, therefore, that 40% of businesses are turning to partners to meet their analytics needs.

Terrence Tyler, Paradigm Technology’s Practice Director for Enterprise Information Management comments, “There will be no shortage of data in the future, in fact, it will be quite the opposite. Along with the potential explosion for sources of content, organizations are increasingly at the risk of becoming data rich but information poor.”

Matching the right analytics solutions
to the right data set can yield actionable and accurate insights. Businesses that glean those insights will gain a competitive advantage.

“The need to capture relevant information, predict what events or behaviors are likely to occur, as well as prescribe solutions to capitalize on that information will be critical for any organization to survive in the competitive growing data landscape,” adds Tyler.

To see why data analysis today is especially challenging, let’s look at social media.

Technologies That Drive Social Media Insights

Data analytics is an inherently challenging discipline. Even when the data you want to analyze is in a consistent format and easily accessible, identifying meaningful patterns requires a high level of expertise. When data is not in a consistent format, finding patterns becomes even more difficult.

Whatever your opinion of various social media platforms, we can all agree that the content users generate on them is far from consistent. Facebook content includes text, images, videos, and audio clips. Even if you focus on just textual content, you will likely find tremendous variations in writing styles and the use of informal language.

Can a Machine, Like, Figure Out, Like, What I’m Saying, and Stuff?

Can social media content be fodder for your analytics tool? The short answer is: yes. Analytics solutions today Cognitive, Cognitive Computing, Analytics, Data Analyticscan make sense of what people write in casual online conversations and turn it into useful data. The data is useful because buyers make purchasing decisions based on what they read in social media. In fact, more than 70% of consumers take social media comments into account in making their buying decisions.

If you want to know the real reason your product or service is (or isn’t) selling, you can often get a good idea of the reasons why by analyzing social media content. To analyze social media, you need an analytics tool that incorporates natural language processing. With that solution in hand, you will see the benefits of hearing about your product directly from the consumer.

Cognitive Analytics Enable Deeper Customer Insights

We know that having natural language in your data set can be a barrier to analysis. We also know that you can overcome that barrier using a tool that understands natural language. That same ability to decipher natural language is also a key capability in cognitive analytics tools.

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Cognitive analytics incorporates natural language processing along with the ability to analyze data in formats such as video, audio, and images. Most importantly, cognitive analytics incorporates machine learning, which is the ability for a machine to learn on its own. A cognitive analytics tool can make useful predictions about the items customers are likely to buy, specific features they are likely to want in a new product, how much they would be willing to pay for specific features, and so forth.

The predictions do not rely solely on analysis of the past behavior of similar customers. Instead, the predictions also take into account previously inaccessible data, such as a customer’s personality and emotions. This creates recommendations that resonate with customers.

Position Your Business for Success with Analytics

Today, data analytics are an essential component of business growth.

Paradigm understands that businesses are considering a potentially bewildering array of analytics tools. At the same time, the types of data available to analyze and the number of sources of consumer and market data are growing faster than at any time in history. Selecting the right data analytics partner can give you confidence that you will use the best possible solution to deliver the specific outcomes your business requires.

Is your business tapping the full potential of today’s data analytics? Reach out to Paradigm for analytics solutions that help your teams maximize the value of your information for your business.