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Some of the leading digital businesses are already securing significant advances in their use of AI for everyday dealings with the consumer, and more will surely follow.

There’s no doubt that customer experience is absolutely essential for brand survival. AI and analytics will increasingly be deployed to support the customer experience, as well as being the principal means to deliver it.

That makes trust and transparency every bit as important as technology in achieving success.

So what are the components of customer experience? Personalisation is one key element. But there’s been a tendency to see personalisation in terms of the value and advantage brands accrue from exploiting ever-more granular customer data in real time.

Instead, the focus needs to be on what personalisation means for the consumer.

And some more forward-thinking brands are starting to do just that. They’re looking at their relationships with customers and their data in a new way.

Mindful of the need to earn and retain digital trust, these brands are being more open and transparent with consumers. For example, some organisations are enabling their customers to see all the data they held on them. This allows them to modify and control how their interactions with the brand happen in the future.

Fair value exchange

A more open and transparent relationship with the customer and the concept of fair value exchange sit at the heart of the customer experience in the digital era. When this is done properly, consumers are willing to share more because they recognise the value that they receive and have a degree of control over how brand interactions take place.

Many of these interactions are now managed by artificial intelligence, machine learning, chatbots and virtual assistants. As more of the consumer experience of a brand is driven by AI, the emphasis on fair value becomes even more important. And it’s a crucial component underpinning the ability to build ‘living brands’ that adapt and evolve with every consumer interaction. As such, this becomes a powerful potential source of competitive differentiation.

AI becomes the face of the brand

Some of the leading digital businesses are already securing significant advances in their use of AI for everyday dealings with the consumer.

In only a few years, it’s likely that most interactions won’t require a keyboard. Instead, they will be based on voice, gesture and augmented or virtual-reality interactions. And as screen time declines, the ability to ‘own’ an interface will become a critical goal and a potential source of disruption.

Of course, using AI interfaces as the primary source of interaction and a key source of data needs to strike a balance between offering ‘cool’ features consumers value and safeguarding against ‘creepy’ intrusions that turn customers off.

This reinforces the need to give consumers a degree of control that goes beyond simply setting channel preferences to provide a deeper understanding of how and when communications take place. It means that the ‘right time’ rather than ‘real time’ becomes the key attribute consumers appreciate and respond to.

Moving forward

So what do organisations need to think about when integrating AI as their spokesperson and first point of contact with the customer?

The right operating model and governance:

Pervasive use of AI to support the customer experience requires a radically different approach to operating models, processes and governance. Entrusting customer data to analytics, machine learning and AI requires the right kind of robust capabilities and controls.

Evolving the data supply chain:

Having AI, machine learning and analytics as the drivers of the customer experience relies on collecting enormous amounts of data. This data can be internal, external, structured and unstructured from right across the value chain, as well as being augmented from other sources. In addition, overlaid on this is ‘derived data’ and consumer insight. Making all this work together depends on a sophisticated and evolving data supply chain to feed the AI.

Keeping pace with changes in technology:

The sophistication of analytics, AI and machine learning is increasing exponentially. Techniques are in play today that didn’t exist a few months ago. So it is essential to make the right choices regarding technology, and have solutions that can keep pace with a rapid rate of change.

People and machines working in tandem:

Tools and techniques need to be augmented with people. Human intervention and control must support AI and its adoption within these enterprises as it becomes the foundation for the customer experience. It’s critical to test, learn and develop technology in ways that keep in step with the lightning-fast pace of change.

By: Conor McGovern, Managing Director, Accenture Analytics

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