Every organization captures data -- social media analytics, customer interactions, website traffic and other metrics, the list goes on. That the amount of data collected is growing exponentially is no surprise, that technologies are emerging every day to help us capture and analyze this data is also no surprise. But how are these analytics and data support tools changing to help better support the customer experience and what can we expect from these technologies in the next few years? That's the question we asked our esteemed panel in today's Discussion Point.
Cathy McKnight -- Digital Clarity Group
Until quite recently, "analytics" in the context of WCM was almost exclusively about what was happening with the website itself: How many visitors arrived? What pages were viewed? For how long? This data was rarely available immediately nor did it need to be, since it influenced decisions and changes that would be implemented over days, weeks, or months. With the shift to CXM/WEM, analytics need to deliver insights -- rapid and actionable insights -- into the profiles and behavior of the visitors to the web and the performance of the content assets. So, in the first instance, it is very important for end users to understand this significant transformation in the way vendors talk about "analytics."
That said, collecting large amounts of data on behavior and performance is relatively easy. And analyzing that data, with the right tool, shouldn’t be difficult. Mining the insight and value from the data is the hard part. CXM/WEM data is now largely a real-time commodity and real-time data must be analyzed with extraordinary speed to create maximum value. The analytics and decision support tools have to become better at finding and identifying the useful nuggets almost a quickly as the data is being generated and captured, and then being able to integrate and merge that real-time data with historical and supplemental data from across the organization to provide the full value it has to offer.
Different emerging channels require different types of analysis, so analytics tools will have to adapt to accommodate, understand and integrate new channels as they evolve, appear and are adopted by the consumer. As the value of analytics ultimately lies in its ability to inform correct decisions that produce business value, feedback and verification features will become increasingly important. For example, the ability to define key performance indicators (KPIs) within the tools and base both real time content deployment decisions as well as strategic customer engagement strategies on the measurements across various channels and audience segments, will be an important functional feature.
David Aponovich -- Forrester
The challenge marketers face in having an abundance of analytics data about their digital initiatives is dealing with an abundance of analytics data. There’s too much of it. Marketers are great at leveraging Customer Experience Management solutions like web content management and related analytics tools to generate data on how their websites and campaigns are performing, because it’s now relatively easy to do so. This opportunity has been conquered.
The next frontier that needs to be addressed relates to how marketers make sense of all that data, extract the information that’s most relevant and important to their business, and then take actions on the data in ways that allow them to move the needle in the right direction. I like the idea of systems being able to change content and information in real time, on the fly, to respond to what’s working and what’s not, as well as making it easier to update and tweak customer experience based on data flowing into the system. Those are just a few examples.