AI-enabled Personalization: How to Get Started

In the early 1980s, a global takeover by intelligent robots seems like an inevitability. Today, artificial intelligence (AI) is indeed taking over — but in a much more friendly way.

In fact, Gartner says that 85 percent of business to customer interactions will take place without human interaction by 2020. Additionally, Servion has forecasted that AI will power 95 percent of all customer interactions by 2025. By then, AI-driven technologies will have evolved to such an extent that customers will not able to distinguish if they are speaking to a bot or a human.

How AI Improves the Customer Experience

It all comes down to this:

With enough data, AI, and ML (machine learning) technology can predict consumer behavior and make personal recommendations in real-time.

Amazon has already taken advantage of AI technologies where they provide their customers with personalized recommendations based on items their customers have searched for and purchased. Their AI-system even suggests products that other people have bought too.

But the biggest challenge that companies are facing right now is that recent advances in AI technologies are rapidly outpacing marketers ability to harness them. So the reality is, AI-powered personalization is not just a challenge for some companies, it’s a challenge for most. And for those forward-thinking marketing professionals who are ready to embrace AI, they stand a better chance of improving their competitive advantage.

Step One: Identify, Understand, and Segment Your Customers

As with any personalization campaign, you need to identify and understand your customer base — particularly those who are regularly using your website and app.

Your analytics platform and content management system should do most of the heavy lifting here, although enterprises need to go a step further to burst their customer experience bubble. That includes collecting voice of the customer data and pairing that with the data found inside analytics systems.

Once you know who your customers are, what they want, and what makes them convert, you can begin to feed AI-driven technologies with the right data. Now, you just have to choose which AI technology you’re going to adopt first.

Step Two: Choose Your AI Platform

There are a number of AI systems that can be implemented. It is best to start with one AI system and then incorporate another. The following three AI technologies are tried-and-tested and have helped numerous companies to deliver a more personalized service.

1. Chatbots

Chatbots have proven to be a very popular route into AI. In a survey conducted by PwC, 34 percent of executives have noticed how chatbots have freed up more time to focus on deep thinking and innovation. Customers have also grown accustomed to dealing with chatbots with 95 percent of consumers (according to survey by Mindblower) saying that a company’s customer service department would be the main beneficiary from using chatbots.

Indeed, chatbots are mainly used to aid frontline workers. Chatbots have helped to decrease training times required for service reps and the time needed to handle highly repetitive queries.

Before investing in chatbot implementation, it would be wise to consider developing a set of customer journey maps and identify any repetitive tasks. Most chatbots are text-based systems, so investing in a sentiment analysis software — or opting for a chatbot with AI built in — will help to determine the emotion and intent of the text the customer has written.

2. Voice-enabled Conversational AI

Juniper Research has predicted that 55 percent of US households will have a voice-enabled smart speaker (such as Google Home or Amazon Alexa) by 2022. Despite this adoption of the voice-enabled smart speaker, Juniper Research has also stated that a large majority of these consumer conversations will occur via smartphones through a voice-assistant app.

From this, it is quite clear that conversational commerce is going to be the next evolutionary step in marketing. Platforms like Amazon Alexa have allowed developers to create and implement their own set of “skills” to meet rising Content-as-a-Service (CaaS) demands.

The development of this type of AI technology requires as much human involvement as possible along with having regular reviews and updates. Service representatives can play a key role in tagging keywords and provide that all-important feedback to improve the voice-based AI system.

Also, using augmented natural language processing will enable the voice-based AI system to understand the emotional tone of the customer as well as the customer’s dialect.

3. AI Augmented Contextual Analysis

Analytically generated recommendations like product offers and next best actions are moving beyond simply recommendation engines in favor of machine-learning and AI.

Besides our aforementioned Amazon example, Spotify’s intelligent playlist is another great example using augmented contextual analysis. It generates a customer’s playlist based on the listener’s previously played tracks and albums, their past likes, and what others with a similar taste in music have also listened to. This AI-driven activity helps to build loyalty, trust, and satisfaction as it is truly offering a very personal experience.

The development of this type of AI technology does require an IT infrastructure that supports a comprehensive customer decision hub.

Marketers, it’s Time to Embrace AI

Humans, and marketers specifically, have no need to fear AI technology. Not only are they not harmful to us physically, but they pose no threat to actual jobs, either. That because AI intends to replace tasks, not jobs.

To give you a recent example, Accenture successfully implemented AI chatbots to replace repetitive tasks whilst managing to re-skill their staff. Accenture have noted that their staff were more productive and could invest more time in attending pressing matters.  

The bottom line is, AI is here to stay — and it is only going to continue to evolve over time. Choosing to resist AI technologies will only result in competitive disadvantages. On the flip side, brands who invest in AI today will reap the benefits tomorrow, especially when it comes to delivering personalized customer experiences at scale.

April 18, 2018

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