AI is no longer future vision for communication. It’s here and we should all be looking at ways of leveraging its power to improve current processes and the overall customer communication experience.

In my blog last week, I spoke about how AI and ML are the current industry trends – the buzzwords and talking points within organizations and at conferences. However, it’s time to start thinking about how to use AI processes and systems to enhance digital initiatives and provide a better customer experience.

Here are four areas that you can focus on to transform digital customer communication and optimize your processes using AI and ML:

  1. Dealing with data

In the Customer Communication Management (CCM) and digital communications space, data has always played a pivotal role. However, to really use the data optimally has involved a lot of manual intervention and working around siloes, which will no longer be sustainable, as technology continues to grow.

Data is essential for AI to function and to ensure the best possible customer experience. Without it, there will always be a fractured customer experience involving digital interactions.

The data strategy is imperative now more than ever. This includes everything from standardization of data labels, getting data in and out of a central repository, to moving toward a single customer view.

2. Integrating with voice tech

The growth of voice technology has exploded with the likes of Alexa, Siri and Google Assistant, however, having our device do calculations, play music and read the news are the basics.

As voice technology becomes far more entrenched in our daily lives, integrating with this technology, when it comes to customer communication, becomes all the more important. There is no use working toward digital transformation and forgetting to add voice tech at each step along the way.

And when it comes to integrating with voice technology, think about the documents sent out by your organization and how to incorporate them in the voice customer experience.

Voice Assistance For Billing

As an example, why not get a consumer to ask their voice assistant how much they owe on their bill and give the instruction to pay it? This integration isn’t what lies in the future, it’s what is possible today (we know, we’ve made it happen).

3. Content & Document creation

AI opens up opportunities for automation of content composition and creation, as well as testing scenarios to provide content that works.

In the world of marketing, content marketing tops the list for AI use cases by far, according to a recent report by the Marketing AI Institute.

But, not all content is about marketing to customers. Documents are also made up of data and content, so tech being used in the marketing space can and should be used in the document creation space too. It’s always good to see how tech is being used in other areas of digital communication and specifically how we can apply it to documents for a better user experience.

4. Hyper-personalization

As an industry we’ve spoken about 1-to-1 communication for many years, but only with AI is it truly within reach. With the combination of data and decisioning engines, the age of hyper-personalization is upon us, allowing us to provide the next best offer or action to each customer, based on their unique data criteria.

We move from personalization to hyper-personalization and from segmentation to micro-segmentation – this is what moves the needle in not only creating a loyal customer, but by providing the next best action or offer, we are providing the opportunity for a far more profitable customer.

In a recent white paper, IDC states that AI is the key technology that will drive organizations through Digital Transformation (DX), asserting that 40% of all DX initiatives through the end of 2019 will be related to AI. Now is the time to start with those AI projects.

As we digitally transform, it is imperative that our communications also evolve and become more relevant to the consumer if they are to be effective.

What we’ve imagined is now possible and can be achieved with AI and machine learning tools.