MarTech in 2017: Five Predictions and Expectations

), 2017 will really be the year of augmented reality (AR). Meanwhile, vendors can already deliver terrific and affordable AR user experiences with today's technology. And we will see more and more of them affordably delivered in the coming year. Over the next year, developers and analysts will start testing algorithms against each other to determine what works for a given use case, and then continue to experiment with the algorithms over time. Customers can now add modules à la carte and receive real-time service and feature updates. Time-to-value will drive the next competitive wave in many industries, and the vendors that are able to deliver it will do well. For example, with the explosion of marketing technology vendors, it is becoming overwhelming for customers themselves to stitch together 15 or 16 point solutions into a single marketing platform. As a result, they are hesitating to move forward with initiatives and demanding more comprehensive, integrated solutions. The result is a huge opportunity for vendors that understand how to properly integrate the solutions they acquire. Say sayonara to the chief digital officer As companies make the technology and cultural shifts necessary to becoming digital businesses, we will see the continued rise—but then the disappearance—of the chief digital officer (CDO).

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2016 has been a big year for everyone, especially marketers trying to reach their audience in the midst of life’s daily distractions. With the year coming to a close, here are my thoughts on what’s to come in the martech industry in 2017.

1. 2017 will be the year of augmented reality

Although virtual reality (VR) is once again a hot topic (remember the VR hype in the early 1990s?), 2017 will really be the year of augmented reality (AR).

The barriers to entry for delivering a quality AR user experience are much lower than they are for VR, which still suffers from a variety of issues, including stutter and motion sickness. As a result, VR will remain a toy for high-end gaming, especially given the current price-point and hardware requirements.

Meanwhile, vendors can already deliver terrific and affordable AR user experiences with today’s technology. The potential use cases for these capabilities for manufacturing (access to manuals), healthcare (patient information and resource location), communication (real-time translations), and other industries and uses is unlimited. And we will see more and more of them affordably delivered in the coming year.

2. Forget about fixed algorithm solutions; experimentation through machine-learning will be key to driving results

Machine-learning has gotten good enough to spot trends and make predictions that could not have been otherwise spotted or made. As a result, machine-learning will become tables takes for analytics and marketing technology solutions. But the real opportunity in this area lies in experimenting with the underlying algorithms.

In a typical Big Data use case, an algorithm is developed and becomes a fixed aspect of the solution, always looking at the data the same way. Over the next year, developers and analysts will start testing algorithms against each other to determine what works for a given use case, and then continue to experiment with the algorithms over time.

Companies that will be successful at doing that will need to go through a two-phase culture shift:

  • First, they will embrace the idea of…

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