Capterra | How and When AI Will Impact Customer Experience

In 2016, Swedbank debuted “Nina.” By early this year, Nina was having 45,000 or so conversations with customer per month, WIRED reports. As Swedbank’s first customer service chatbot, Nina successfully answers eight out of 10 inquiries without human intervention.

According to research, excellent customer experience (CX) is:

  • Personalized
  • Always on
  • Real-time
  • Consistent
  • Omni-channel

Because artificial intelligence (AI) can help with each of these targets, part two of my “What is Customer Service in 2017?” series was Bots for Customer Service.

This is how and when AI will impact CX.

What is Nina?

Nina is a bot.

“A bot, at its most basic, is a piece of software that performs an automated task, be it finding an awesome GIF, ordering toilet paper, or downloading a file,” according to WIRED. Bots have been around for decades, but combining their automated workflows with Natural Language Processing and machine learning algorithms makes them “chatbots.”

Apple’s Siri, Microsoft’s Cortana, and Amazon’s Alexa are examples of these newer, smarter bots.

“Bots are great at making sense out of lots of different types of information and making all of that data more useful by allowing people to interact with it like they would in a conversation with a person,” April Underwood, a head of platform at Slack told WIRED.

Bots are also good at decision-making, including automatically classifying, appropriately routing, and escalating tickets. Nina routes the 20% of questions she can’t answer on her own to the right human representatives using machine learning-powered predictive analytics.

Gartner calls machine learning a technology to watch over the next three years. Machine learning is one category in the overall field of Artificial Intelligence (AI). According to Salesforce research, 92% percent of senior executives believe that customer experience is a key competitive differentiator and they view customer service as the primary vehicle for improving the customer experience.

“More people use messaging apps than social media, so bots are a huge opportunity to engage with your customers and audience where they already are,” Octane AI Head of Product Megan Berry told Allison Grinberg-Funes. The venture-backed startup makes it easier to create your own bot. “I think in the next year or two we’ll see that bots became an essential part of a company’s marketing arsenal, just like newsletters.”

Is my competition using AI?

If they’re not already, they will be soon. Airbnb has a chatbot that owners can use to answer guest’s common questions. Twitter has added chatbot functionality to direct messages. Sephora and American Express use chatbots to prevent phone calls.

In early 2017, Gartner surveyed (not online) 165 knowledgeable Gartner Research Circle IT and IT/Business Members Members about the specifics of their company’s CX activities in 2016.

More than half (55%) of respondents said they expect their organizations to implement some kind of machine learning in the next three years. Nearly half (44%) said they’d be implementing Virtual Customer Assistants. One in ten respondents already have a chatbot implemented, and another 14% of respondents plan to launch one in the next 12 months.

“The line-of-business that is most likely to embrace AI first will be the customer service – typically the most process oriented and technology savvy organization within most companies,” writes Vala Afshar, Chief Digital Evangelist for Salesforce.

How AI is impacting CX now

AI is improving enterprise software

Nina, Siri, Cortana, and Alexa all have something in common: They’re aimed primarily at the B2C (business-to-consumer) market. Chatbots Magazine’s Sar Haribhakt predicted in 2016 that chatbots would make a splash in the B2B (business-to-business) space before B2C. I find Haribhakt’s argument persuasive. Essentially, B2C software is elegant and easy-to-use compared with B2B. Which means the need for AI is less intense there.

After flogging enterprise software as a category, Haribhakt praises communication-based workplace products like SlackQuip, and Figma as “user-centric” and “big steps in the direction of consumerization of enterprise software.”

Haribhakt writes:

“These tools help employees do their jobs faster and better. Bots, which fundamentally stand for automation, will supplement and enhance the collaborative and communication-centric tools to increase productivity at workplaces by orders of magnitude.”

Bots are currently automating these tasks in business software:

  • Finding information
  • Answering questions
  • Doing research
  • Locating files
  • Scheduling meetings
  • Coordinating with colleagues
  • Managing workflow

But that’s not even the start of what AI is doing for CX.

AI is creating data where there was none

Many bots, including Nina, automatically transcribe their voice conversations into text. InterActiveTel records conversations with customers at car dealerships and translates that speech to text. Salesforce uses open-source APIs to convert conversations to text in real time.

Other companies, including Pinterest and Google, are trying to replace text with images. Specifically, they’re encouraging users to start snapping photos instead of typing queries, or use the camera to “kill the keyboard” as WIRED put it. Instead of typing keywords to try to find recipes to recreate a particularly delicious meal you’re enjoying at a restaurant, you can snap a picture of it and upload it to Pinterest.

New amounts and forms of data might not sound like a big deal on their own. But it’s all vital for training machine learning algorithms. When you start with reams of human-corrected data, the possibilities are profound.

AI is analyzing data to predict future behavior

It’s when companies begin to use machines to analyze their troves of data that they start seeing real benefits.

For example, Salesforce’s machine learning algorithms analyze conversations between salespeople and prospects as they happen. The algorithm looks for sales opportunities and alerts managers in real time. Machine learning means that over time the algorithm will learn from its successes and it’s failures, what an opportunity looks like, and how to best capture it.

Salesforce’s artificial intelligence technology is called Einstein. Einstein is available to the more than 150,000 companies that use Salesforce. “Marketers using AI have seen an average 25% lift in click through and opens,” Afshar wrote. “Sales professionals using AI predictive lead scoring have a 300% increase in lead to opportunity conversions. Commerce teams using AI have 7-15% increase in revenue per site visitor.”

Infer offers predictive analytics for sales and marketing, putting them in direct competition with Salesforce. In a detailed article about the current AI hype, CEO Vik Singh claims that big companies like Salesforce are “making machine learning feel like AWS infrastructure” which “won’t result in sticky adoption.” Singh adds that “machine learning is not like AWS, which you can just spin up and magically connect to some system.”

AI is turning missed opportunities into just plain opportunities

While most smaller companies won’t be launching their own predictive analytics capabilities anytime soon, AI isn’t just changing business at the enterprise level. For example, small brick-and-mortar retailers can take advantage of a chatbot named Bo. When customers call your company and get voicemail, Bo will text customers, asking them how he can help them out. If the customer texts back that she wants to come into your salon for a blowout today, Bo will set the appointment. “And the rest is hairstory( 😂),” writes Ron Fisher, CEO & Co-Founder of Bowtie.ai.

What’s next in AI for customer experience

For example, instead of routing tickets based on who’s available or the subject matter or both, intelligent routing could automatically escalate tickets created by high-value customers and those created by customers whose business you’re most in danger of losing.

In fact, the process of segmentation may soon be automated by AI. “If you have three segments, you’re doing three times the work, but you can’t get three times the return,” Lucinda Duncalfe, CEO at Monetate, told VentureBeat. Human effort means segmentation quickly reaches the point of diminishing returns. And having humans design bespoke experiences for each individual is not cost-effective either. Monetate seeks to leverage machine learning to offer the best experience to each individual at scale.

“AI will become the new digital spokesperson for leading companies,” Nicola Morini, managing director of artificial intelligence at Accenture, told WIRED. “Customers will experience a company’s brand through personalized, 100 percent consistent and natural interactions with AI service agents—and even engage with the brand through other companies’ AI interfaces.”

Companies will be able to minimize costs, sell more products, and make customers happier with just “a minimum of AI and a maximum of common sense and excellent focus on end-to-end process design,” according to Gartner Analyst Michael Moaz. He sees AI and empathetic process design as a great pairing. “AI alone leaves us back in the ’80s when Lisp was a popular tool for AI. The same AI that languished for another 30 years.”

“AI is becoming the new user interface (UI), underpinning the way we transact and interact with systems. Seventy-nine percent of business leaders agree that AI will revolutionize the way they gain information from and interact with customers. As AI takes over more of the user experience, it grows beyond just an intelligent interface. With each customer interaction becoming more personalized, powerful, and natural, AI moves into an even more prominent position: your digital spokesperson,” —Accenture Technology Vision 2017

Last thoughts on AI and CX

CX covers every aspect of a business. AI is improving and will improve every aspect of the organization as well. Already Salesforce’s Einstein adds AI capabilities to customers’ sales, services, marketing, IT, and community organizations.

Already, your competitors are using AI to automate tasks including finding information and files, scheduling meetings, and managing workflow. They’re transcribing voice conversations into text to be analyzed and learned from. They’re using human-corrected data to accurately predict the future. And they’re using these predictions to make sales they would have otherwise missed.

In the near future, brands will use machine intelligence to route tickets based on smart segments, create those segments, and personalize customer interactions.

To learn more about CX, check out 9 Customer Experience Influencers to Start Following Now and How to Measure Customer Experience.

Capterra | June 2017

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