A worker in an office chair admiring the work being done via AI
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Within your organization, you have already accumulated and are continuing to amass a potential treasure trove of information about your customers. At the same time, you are building up a wide variety of content including images, text and videos, which you want to use to better target individual customers and to meet and/or anticipate their needs.

Your goal is to marry up these two worlds. You want to create a virtuous cycle of engagement where the content you serve up to customers is relevant, personalized and actionable and, which, in turn, drives greater customer loyalty and investment in your products and services.

How to Get There from Here?

What many organizations are currently struggling with is how to achieve that virtuous cycle of engagement with their current digital experience (DX) software. Typically, they lack a unified and centralized DX platform with the ability to intelligently tag content so it’s both easily searchable and retrievable. There’s also no intelligence coming into play to learn from prior DX engagements whether it’s all customers or the individual buyer in terms of their areas of interest to come up with patterns and insights relating to consumer behavior.

There’s also the issue of the vast amount of demographic information an organization has to handle, which may be a mix of its own customer data and external sources. Ken Krause, a worldwide digital experience evangelist for IBM Watson Customer Engagement, points out that demographic information used in isolation may often result in misleading conclusions about customers.

Krause gives the example of Prince Charles and rock singer Ozzy Osbourne who share much of the same demographic information – born in the same year, British, married and remarried with children – but they are clearly very, very different customers in terms of targeting. “Once you’ve gathered data, you need to apply intelligence to make the next-best recommendations,” Krause said.

It may also be the case that your DX platform isn’t fully automated, meaning that your content creators are spending way too much time on manual tasks such as content identification, tagging and cataloguing rather than being able to focus their attention on much more creative and collaborative endeavors. Your DXP may not be easily set up to meet your content creators’ need to quickly create and refine content, which in turn means that it’s almost impossible for them to publish content in real-time to give your customers the kind of personalized digital experiences they expect.

Complementary e-Book For Your Review: How the Right DX Platform Can Transform Your Business

Is AI the Answer?

The best way to think about artificial intelligence in relation to DX platforms is as a complementary or assistant technology to help your human content and experience creators. AI can help automate many content tasks which have traditionally been done manually and are very time consuming.

It’s important not to look at AI as a monolithic emerging technology suitable only for a handful of dedicated use cases or industries. Instead, view AI as a wide variety of sets of products and services which can be applied across any and all verticals and use cases.

For instance, take the example of cognitive tagging, where an AI-infused DXP can suggest categories and tags, which employees can then accept, customize or reject. This AI visual recognition service learns over time, increasing the accuracy of the tagging. This capability saves time when content is uploaded to the system and makes finding just the right content a lot more efficient in a quickly growing collection of assets.

Vivere.travel is using IBM Watson Content Hub as the basis for its online destination discovery platform. “To enable our customers to find exactly what they’re looking for, we wanted a way to aggregate, organize and tag a massive amount of visual and non-visual content as efficiently and intelligently as possible,” said Matteo De Santis, Head of Business Development at Vivere.travel.

By adopting automated AI for image tagging, Vivere.travel will be able to both free up its content team who have been manually tagging images and easily scale its platform without having to add additional headcount.

Adopt a Change in Mindset

“Everybody is dipping their toes in the [AI] water, with early adopters having dove right in,” said Barry Pellas, chief technology officer at IBM partner and digital transformation consultancy PointSource, a Globant company. His responsibilities include leading the AI practice within Globant.

Organizations realizing early success with AI are those who have included “a change in mindset” to focus on problem solving, according to Pellas. Those problems are typically ones where humans will take a long time to resolve the issue and/or where the scale of the problem in terms of the data crunching involved, is way beyond a human’s capability.

Organizations need to take the time to define the problem or problems they want to solve using AI.  Next, they should consider the data that is easily accessible around the problem and what additional information they may want to make available to the AI service. Then, create a hypothesis and start experimenting using the variety of AI services available. The focus shouldn’t always be on finding a single solution to a problem, but on improving a process for finding solutions in an ongoing way.

AI as Augmenter

Today, insurance companies are using chatbots to facilitate customers’ payment processes, while doctors’ office are using AI to improve low-quality document scans. Traditional computer vision modeling enhanced with AI is helping libraries reorder books and doctors’ offices learn more about providing optimal patient waiting rooms by observing patient behavior and how long the check-in process takes.

The current hype around AI translates to people expecting the technology to answer all their questions. “A true cognitive system needs to be trained and pointed to address specific needs,” IBM’s Krause said. Organizations should pinpoint interaction points along the customer experience journey and then use AI to augment that particular engagement to provide guidance. In some cases, that help might be to direct a customer to a more traditional channel. For instance, a chatbot may direct a customer to a human specialist. What’s important, he notes, is that the hand-off is seamless so the AI has matched the specialist to the current issue the customer is experiencing, included all the relevant context and even some potential recommendations for problem resolution.

Digital Experience (DX) as a 'Black Box'

Going forward, it’s helpful to think about the customer-facing part of the digital experience as more of a “black box,” PointSource’s Pellas said. “So, its role isn’t fixed, but could be anything depending on what the user is doing and how they are behaving.”

In other words, as the consumer is engaging with your company, your staff are working in tandem with AI services to build the experience for them. Once instance might involve assembling a highly personalized and relevant discount. The AI service might create the promos from a list of approved brand content. In that way, the organization retains its traditional checks and balances on what deals can be offered to a customer while at the same time offering a unique and personalized experience.

The idea is to set up the parameters so that a customer’s digital experience is very contextual and is based around their most recent history engaging with your company, via your website, social media interaction or other channels.

The Rise of Intelligent Platforms

There’s an added wrinkle coming for content creators — the rise of intelligent platforms, which use voice as the user interface to unlock digital experiences. This is another area where AI can help, for instance as more organizations look to use personalized recommendation engines rather than the traditional approach of drawing on an entire audience’s recommendations.

AI discovery services can look at the taxonomy of an organization’s content and pull out relevant content in real-time across channels to answer a customer’s question. For instance, say you’re engaging with a chatbot about the weather in reference to an upcoming sporting event. If rain is predicted, along with the weather forecast, the bot also may come back with a recommendation to purchase a waterproof jacket or an umbrella.

What will be key going forward is that companies make sure to work with conversational UI designers to ensure that human interactions with chatbots use natural language and are informative, as opposed to frustrating exchanges.

AI language services can also be used in tone analysis to provide advice on how marketers “can better phrase their messaging” so they’re delivering positive, not negative statements, IBM’s Krause said. Then, there’s proactive use of sentiment analysis where companies take immediate action based on what the AI has identified. “If there’s a negative comment, you can immediately start a chat and have someone reach out to the customer,” he added. “In the case of positive comments, you can encourage people to share their experiences.”  

AI Has the Power to Transform Digital Experiences

What’s coming next will be a much higher degree of personalization, according to Krause, where the move is from data-driven marketing to “almost a conversation-based marketing.” So, you’ll describe to an AI assistant the types of customers that you’re looking for and the service will help you to hone your search as well as identify the most appropriate groups to target. 

Clearly, the addition of AI services can and will continue to make a sizable difference to what organizations can provide in terms of the depth of their customer engagement and the empowerment of their content creators across all channels.

By choosing a DXP which can support and integrate AI services, you can achieve a keen competitive edge over your peers. You can hone that advantage as you continue to use AI services to help you gain more insight from your data and third-party information. You can then be more responsive and creative in adjusting and enhancing your brands’ customer experience so it’s both engaging and personalized.