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Marketing Technology

Gartner, the IT research company, published its 2016 list of predictions for marketing technology a few weeks ago. As I was reading it, I was struck with how easily the list could be aligned with the user experience of the typical purchase process. Not the complete buyer’s journey; but at least the transactions steps in the middle.

In less than three years, advances in marketing technology will move beyond human intervention to streamlining and scaling activities that currently require manual interactions with audiences. Intelligent technologies will do more than automate repetitive operations — they will investigate, evaluate and make decisions on behalf of both marketers and customers.Marketing technology will soon become so intelligent that it will perform tasks that have always required direct human involvement.

My Take

They list five predictions, but of course we always feel obligated to add value to the articles we share on EID. So I added one step and separated one of Gartner’s five steps into two pieces. Here are seven total predictions that we ended up with – ordered along with the transactional user experience.

The step I added was at the very beginning. Before doing any kind of marketing, it is critical for companies to understand the customer and his or her needs, behaviors, and context. So my prediction is that there will be some advances in marketing technology that helps us with our ethnographic research. Since so much of our lives are online, it seems like a natural fit that we can supplement embedded ethnography with field intercept systems through mobile devices and perhaps Internet of Things in the near future.

The second step (Gartner’s first) is what I refer to as the Big Data step. We are being overwhelmed with a torrent of data about our customers, but this data is useless without good modeling algorithms that can create a few somewhat generalizable persona categories that can be used as target audiences for marketing.

The third step is the one I divided in half. Step 3a) is to model contexts in real time during the buyer’s journey so that the marketing can be customized to the buyer’s context. Where is the customer? What time is it? Is the pitch being made on a mobile device, in a store, or at home?

Then step 3b) is to model the customer, also in real time, along attributes such as the customer’s activity and emotional state. I have seen some great technologies being developed to assist at this step, including Emotiv and Affectiva.

The fourth step is to fit marketing approaches to each of the personas. I can see this being a combination of algorithmic and human approaches, similar to what we talked about here a few weeks ago (trackback to Probably along with longitudinal A/B testing to adjust the approaches along the way.

The fifth step is to deliver the pitch. This is where technology is constantly changing. I suspect that by the end of the year marketers will be developing ads designing for headsets like the Oculus Rift. There will also be software innovations such as the creepy retargeting ads that follow us around – but with the new ones hopefully a little smarter and more subtle about it. There will be lots of research to get this right, including some basic research we are conducting here at Bentley as well as A/B testing in the field by the marketers themselves.

Then the last step is the one Gartner makes that I think is better integrated into the others. This is customizing the pitch for mobile. As I have described in the earlier steps, there are mobile implications throughout the buyer’s journey. So maybe we are back to six predictions.

Your Turn

Are you involved in designing or testing the user experiences of marketing technology? There are so many applications for this it is hard to scope out the domain. There are interfaces for the marketers. There are interfaces for the customer. There are invisible modeling systems running in the background. There are research systems for the early stages such as ethnography and intercept journaling studies. And on and on.

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