This week alone, analytics has been a hot topic. Call it what you want — Business Intelligence, Sentiment Analysis or Social Reporting — it can all tell you a lot about what’s going online, around your brand and your customers. Big Data isn’t just for information management. It also applies to marketing. This week also brought up Gartner’s Cool Vendors reports, one of which features those in the content analytics space. Let’s take a look at the companies that topped its list.
Variety, Velocity, Complexity
In its report, Gartner notes the “explosion of data volume” and the considerable shift in tactics that the enterprise has had to deploy to keep up with it. While simply managing and storing information was enough, many are now finding it necessary to mine it for insights that can help them better optimize customer experiences and “and exploit new opportunities for growth, efficiencies, differentiation and innovation.”
For its list, Gartner selected vendors that offer innovative approaches for discovering new patterns and insights and enable organizations to optimize new and existing applications. The four vendors Gartner chose may be cool, but they also have a few things in common — namely, they aim to make companies smarter and more productive.
With a powerful artificial intelligence engine, ai-one provides reusable user interfaces into the mechanics and results of the machine learning process. However, Gartner suggests that the enterprise may not yet be ready to embrace the AI term and suggests that ai-one market itself more for its “machine-learning” technologies. For those responsible for the strategies, architectures and solutions that can harness diverse data to deliver the next generation of intelligent applications, however, ai-one can help companies detect patterns, find high-order co-occurrences and identify latent relationships among data elements across systems.
Co-Decision Technology's Co-Mining decision tracker platform is a collaborative decision management environment, which can replicate the architecture and reasoning process of the human brain to analyze, synthesize and find patterns in vast amounts of structured and content data flows. That sounds pretty cool all by itself, but it can also automate complex reasoning for decisionmaking and the evolution of the decision process over time using algorithms, something they call CyberTracker techniques. Articulating this process to business poses a challenge in Gartner’s eyes, but may prove useful for risk management, homeland security, rail and air transportation security, and law enforcement applications, where many of its components can be used as-is, with little customization needed.
Mattersight builds unique behavioral models based on communications styles and patterns that detect personality and sentiment during a customer and employee interaction. Using proprietary algorithms for analyzing words and patterns of speech and text that each individual exhibits during an interaction, Mattersight finds new actionable insights and patterns by identifying emotion and sentiment in both speech and text interactions (in most languages) and relates this to other transaction history. As cool as speech analytics is, the perception of the enterprise is that it requires advanced skills and expertise to glean any real benefit.
ThoughtWeb is a collaborative decision management environment that reads, analyzes, relates and finds insights in structured and content data. Because it can capture implied knowledge and enable cognitive modeling using conceptual frameworks to support contextual reasoning, organizations can learn in context, while retaining corporate knowledge and share insights across communities to improve collaborative decision making and help prioritize actions. Gartner warns that an inability to articulate business value and overcome the culture bias are its biggest challenges.
Don't Just Mine Data, Learn From It
What is so fascinating about these vendors is how well they complement the insights shared this week at the Sentiment Analysis Symposium and J.Boye, specifically the need to learn from the data companies have worked so hard to manage and measure. Additionally, mining your data for trends that won’t come up from traditional market research can help everyone work smarter, not harder. Most companies know that they have more data than they know what do with and have little idea about how they can capture it, sift through it and learn from it. These four vendors are doing big things with big data in an effort to make it easier for companies to differentiate and innovate within their industry, while improving customer experiences.