How to use Technology Drivers to Create Engagements that are Successful and Stick


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Will we see immersive advertisements like they are in all plasticity shown in the 2002 movie Minority report (yeah, it is that old)? Will our social media status be used for ‘appropriate’ customer engagement like in the Black Mirror episode Nosedive?

How will customer engagement look like in 2020?

Just to be sure – many scenarios that are depicted in these examples are already reality.

But it doesn’t need to be that dystopic.

The Customer Engagement Management Objective

Why does engagement change?

The blunt answer is: Because the customer expectations change.

And customer expectations are changing fast.

But that is no news to you.

In an operationalized adaptation of a definition given by Paul Greenberg:

“Customer engagement is the ongoing interaction between company and customer, using contact points that are offered by the company and chosen by the customer.”

Engagement is a necessity precondition to create an experience, or the journey towards experience. There is no experience without engagement. I have written about this before and the statement still holds true. The ultimate goal of customer engagement, of course, is making business, and successfully so.

Successful customer engagement relies on both, an outside-in strategy – and on technology.

The Technology Drivers

What are the forces driving customer engagement technology ahead in the foreseeable future, therefore enabling the creation of the improved engagement strategies and tactics that customers demand and require?

There are basically four technologies that already do and will continue to drive change.

  • Internet of Things
  • Applied (Narrow) AI, especially machine learning and deep learning
  • Conversational user interfaces
  • Augmented, Mixed, and Virtual Reality

If you now expected to see blockchain in this list I need to disappoint you.

Although concepts like smart contracts are appealing, there already is a blockchain martech landscape and there is the promise/idea of removing friction out of (inter-)company processes I do not necessarily see blockchain as a driving force of how will shape out in the next years.

Blockchain has its uses but they are less likely to be on the engagement frontier. And, looking at the dichotomy between scalability and trust, it will take some more years.

Having said that, it is more than worthwhile to have a look at the technology already now – to be prepared when it is ready to come, and to be able to use possible efficiency gains beyond the hype. Gartner Group actually lists blockchain in their Top 10 Strategic Technology Trends for 2018.

Top 10 Strategic Technology Trends for 2018 by Gartner Group, Oct. 2017, highlighting by TW

On the other hand, Gartner Group also places blockchain technology in the 5 to 10 years bracket of their Hype Cycle for Emerging Technologies.

I have written earlier that AI and IoT are poised to join forces. At that time I focused on the enabling of real-time experiences. But, being able to do something in real-time is not enough. There is more to it, when it comes to engagement. This is where conversational user interfaces and AR, MR, VR come into the picture.

While AI and IoT enable the real-time nature of meaningful interactions, engagement is a bi-directional process that requires more customer (and user) interfaces than many sensors offer. For humans, speech is the most natural way of interacting. Still, true to the proverb that ‘a picture tells more than 1,000 words’, the ability to offer immersive engagements that involve visualization of artificial objects, allowing people to interact with them, up to immersing persons into an environment, offer will become more important.

However, neither user interface will win out. Instead they will augment each other.

This begs the question of how is it possible to use the technology drivers to create engagements that are successful and stick.

How To Get There in Four Simple Steps

Yes, four. Not three and not five, the usual suspect numbers.

Resources are limited, so it is impossible to do everything at once. Therefore it is important to balance tactical needs that bring value quickly with strategic needs that provide a frame of reference for the relevance of tactical implementations.

In other words, one needs to think big while acting small, always keeping the strategy in mind.

Once the strategy is in place and made part of a continuous review and adaptation circle it is time to look at improvement potentials in the three areas

  • data collection (aka Internet of Things)
  • advanced data analysis (aka AI and machine learning)
  • advanced user interfaces

One might argue that IoT devices can serve as user interfaces, too, but in the context of customer engagement the majority of devices (things) in an IoT context is rather a sensor with a very simple interface – think of the AWS IoT button vs. the Alexa type of devices, which are representatives of devices with conversational interfaces.

The foundation for both, IoT and advanced user interfaces is AI, specifically machine learning. So, collecting exposure to and experience with machine learning scenarios is the first step.

Implement machine learning using a scenario that currently works sub-optimal and that can benefit from machine learning.

In a second step, which may very well be executed in parallel to the first one, perform a thorough white space analysis answering the question “Where is my biggest pain point or possible improvement of strengths: On the data collection side or on the user interface side?”

Based upon the result, implement one or more IoT scenarios or user interface scenarios.

Odds are, that on the user interface scenario side chatbots, conversational interfaces, are closer to current needs than AR/MR/VR scenarios, although this may differ from industry to industry – how about a smart mirror that renders clothing on someone’s body, modeling the flow of the garment without the person actually wearing it? Or placing some furniture in a living room?

In the fourth step then implement top scenarios of the other technology side – advanced UIs or IoT, respectively. This is important to gain experience on all three of these interrelated technologies.

So, in summary, the four crucial steps to prepare your company for customer engagement management 2020 are

  1. Go AI and gain machine learning experience based upon existing data
  2. Decide where your bigger pain point, or chance of improving on strengths, is. Is it on the IoT side of the house or on the advanced user interface side?
  3. Based on that answer implement the one or the other, building a new capability or improving on an existing one.
  4. Finally implement a scenario for the other type of technology in order to gain experience and improve on all relevant frontiers

Is this the end, then? No, it isn’t. But in combination with a continuous strategy review and a think big, act small mindset you are well prepared for what the future may throw at you.

Thomas Wieberneit

Thomas helps organisations of different industries and sizes to unlock their potential through digital transformation initiatives using a Think Big - Act Small approach. He is a long standing CRM practitioner, covering sales, marketing, service, collaboration, customer engagement and -experience. Coming from the technology side Thomas has the ability to translate business needs into technology solutions that add value. In his successful leadership positions and consulting engagements he has initiated, designed and implemented transformational change and delivered mission critical systems.


  1. Thanks, Thomas for sharing the informative resource. Use of technology to drive customer engagement will bring in a host of advantages for the business organisations

  2. thanks, David. We also shouldn’t forget that technology is an enabler. People and process are equally important, if not more – although I concentrate on the technology aspects here.


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