1. Self-service knowledgebases and chatbots.

Customers prefer to resolve their own issues. Self-service knowledgebase and chatbots are popular tools that empower customers. … These tools can scale and provide 24×7 customer support and save costs through call deflection.”

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2. Interactive Voice Response.

Interactive Voice Response (IVR) provides a menu-based option of self-service to callers.

The static decision tree approach in a traditional IVR, however, often frustrates customers.

As a result, they attempt to bypass it and talk to a human agent.

AI-driven IVR incorporates automated speech recognition and natural language processing throughout the call.

Instead of focusing on the answer, it attempts to determine the intent of customers’ requests and reorders recommendations intelligently, based on the expected flow.

Thus, customers’ inquiries are effectively resolved without having to talk to an agent.”

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3. Robotic Process Automation.

Some analysts believe Robotic Process Automation (RPA) is a gateway technology to AI but not really AI.

Arguably, most RPA solutions are rules-based systems requiring no AI capabilities.

Nevertheless, Chakraborty writes, “Robotic Process Automation for back office and customer service reduces manual, error-prone and repetitive efforts of data entry, interface navigation or process fulfillment.”

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4. Intelligent routing.

There are times when a customer needs to speak to a real person.

According to Chakraborty, that’s when intelligent routing comes into play.

She explains, “To optimize the customer satisfaction requires assigning the right task.

To the right agent at the right time.

AI-driven workflow leverages the customer data.

Transaction history to anticipate the intent behind the call.

And automatically assigns the ticket to the most capable agent.

Based on skill, training, track record and availability.”

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5. Automatic language translation.

Science fiction movies and television shows always get around presumptive language barriers by using some sort of universal translation system.

Global companies don’t have that luxury and face a real challenge when it comes to operating in markets using different languages. A

I can help. Chakraborty explains, “For businesses operating globally.

It is critical to break the language barriers.

Automatic language detection and translation can help to achieve that goal.”

6. Predictive analytics.

Customers want to be helped quickly and have problems resolved satisfactorily.

Being able to predict what they want can help improve customer experiences.

Chakraborty writes, “AI-driven predictive analytics generates exceptional insights into customers’ future behavior. … In this way, organizations can act on information ahead of time.”

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7. Personalized recommendations.

When customers are shopping rather than problem-solving, AI can also help.

AI-powered social listening and recommendation engines leverage ‘Big Data’.

To capture and digest customers’ demographic data, frequent browsing history.

Cart item selection, media sharing, and product reviews in real-time.

As a result, they recognize every customer’s unique preferences.”

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8. Cross-channel contextual engagement.

One challenge associated with the digital path to purchase is that there are many ways for consumers to start and end their journey.

AI can help companies assist customers through this omnichannel trip.

Customer journeys occur in multi stages.

They jump from channel to channel, device to device and yet expect a connected cross channel experience at every touchpoint.

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AI and Machine Learning techniques gather and analyze data from the entire eco-system and determine the intent and context.

The context becomes available across all the channels.

It proactively guides customers’ journeys, enabling them to switch from speech to chat or chat to live agent seamlessly, without repeating any details.”

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When it comes to providing the best customer experience possible within budget, expect to see more machines picking up the slack.

There will be more interactions between AI-driven interfaces, and fewer human contacts.

By phone, mobile and web, especially for routine questions and transactions.

AI will boost personalization on a mass scale.

And enable more profound product customization and tracking of orders.

Recommendations will get less klutzy and repetitive.”

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Don’t forget the human touch

Both customers and companies benefit when humans are available when necessary.

Think about an enjoyable support interaction you’ve had and the impact it made on your perception of that brand.

Did the representative listen to your concerns and respond in kind?

Did they weigh your circumstances and apply a discount or offer an exception to improve your experience?

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Did they make you laugh? Customers need human engagement for more complex issues.

Not only because resolution may be more complicated.

But also because empathy and de-escalation strategies may be required to alleviate customer stress.

Although it might seem Zingale is not a fan of AI-assisted customer experiences, that’s a false impression.

The right blend of automated and human interactions is crucial.

That’s a good thought to keep in mind if you want to keep your customers happy and coming back.