Here at Adobe, we’re gearing up for our annual Adobe Summit. Many of our past attendees may be wondering what’s going to be new at Summit this year. One of the things I’m most excited about sharing is how we’re looking at the future for Adobe Analytics.

The digital marketplace has changed dramatically in the past several years, and that rate of change isn’t going to stop any time soon. Marketers need increasing agility and speed in terms of their understanding of customer interactions in order to make their customers’ experiences with their brand awesome.

Not that long ago the term Big Data wasn’t overused (ah, the old days) and a page views as a metric was pretty meaningful on its own.  There were folks in the depths of the IT department who held the keys to the kingdom as it related to data and, for whatever reason, just couldn’t seem to get it into the hands of the people who actually interacted with customers. SaaS was burgeoning (some would say it still is), and tools were starting to become available to the folks who needed them most: the people interacting directly with the customer.

Fast forward a few years. The 50+ Web analytics vendors are now three or four. There are plenty of challenges still, but the most important change is that there’s much less stopping the marketing organization from getting the insights they need. The overall digital model is starting to expand into new types of analysis. Touch points aren’t just what we think of as digital; we’re incorporating call center, CRM, and point of sale data. The next wave of marketers who are benefitting from this dramatic increase in the understanding of their customer is starting to see the ROI of doing so as well as much higher customer retention rates, optimized digital experiences to divert traffic from expensive call center interactions, hyper-relevant offers made to customers based on their buying habits, both online and offline. We’re only seeing the beginning of this trend.

Another thing we’re seeing is that digital analysts are getting way smarter. They’ve gotten their arms well around the digital aspect of their worlds, and they’re starting to apply much more processing power to their data. Over the last 18 months, we’ve seen customers who in the past would have required help from a PhD to apply statistical models to their data starting to do it on their own. We’re starting to see new analysts getting value out of statistical tools in their first few minutes with the tool. Our machine learning tools in Adobe Analytics became the second most used features last year. That’s the fastest adoption of a new feature we’ve ever seen, by a wide margin. Needless to say, we’re investing heavily to expand that capability set, building out tools for the quant and for the non-quant in analytics, with the aim of enabling a digital analyst to make the leap to providing true data science outputs for the business.

The future of analytics is moving toward a model that is easy for the average analyst—and company—to use. The goal is for you to get usable, real-time, easy-to-understand insights from your valuable customer data and to expose it throughout the enterprise in order to make the whole place smarter.

We’ll be addressing this in detail at the “Future of Analytics” breakout at the Adobe Marketing Summit next week in Salt Lake City and in London later this spring. Join us to learn more and take part in the conversation around the future of analytics.