Artificial intelligence (AI) has become a crucial tool for meeting consumer expectations, particularly for customer service tasks. Between 2017 and 2021, the number of AI-powered customer service interactions worldwide grew by a massive 400%, estimates Gartner—culminating in a full 15% of these connections being fully automated. Real-world use cases often best illustrate the technology’s potential, so here are five examples of companies using AI for customer service. Keep reading to learn what AI can do for your business—and what it’s already doing for your competitors.
1. Hyperpersonalized Email Engagement: The Muse
The Muse is a major career site for younger job-seekers. While email outreach is a crucial marketing channel for the site, it also provides a key customer service function, delivering curated lists of job postings and training opportunities to users.
The site partnered with AI marketing platform Blueshift to make sure their emails spoke directly to individual needs. This “segment-of-one” automation uses predictive analytics to predict user preferences based on more than their expressed interests: location, previous behavior, and professed skills play into the AI algorithm as well. Customers responded positively, effectively doubling visits to pages recommended in the AI-driven emails and scoring an email-open rate of nearly 60%.
2. AI Customer Service Bots: 1-800-Flowers
Artificial intelligence allows companies to automate typical customer service tasks, including core revenue drivers like product orders. Online floral dealer 1-800-Flowers worked with IBM’s Watson AI system to develop a “digital concierge”—an AI customer service bot that takes customer orders through their website and mobile app.
Titled “GWYN” (“Gifts When You Need”), this chatbot uses natural language understanding (NLU) and natural language generation (NLG) to take customer orders in a more intuitive way than a traditional online order form. “Instead of a structured process of filling out a form on a website, you’ll be able to just type into GWYN, ‘I’m looking for a birthday gift,’ and GWYN will ask, ‘Is it for a male or female? Age 30 or 35?’” Chris McCann, president of 1-800-Flowers, told Campaign.
3. Branded Voice Assistants: Sensory Fitness
You’re probably already familiar with AI voice assistants; by 2024, analysts expect 8.4 billion of these digital servants to be in use globally. Apple Siri, Amazon Alexa, and Google Assistant are well-known examples, but some brands are creating their own digital voice assistants to handle customer service tasks as well.
One example is workout education outfit Sensory Fitness. The brand developed a voice-powered AI assistant called Sasha to handle customer service phone calls. Like 1-800-Flowers’ chatbot, Sasha uses NLU and NLG to carry on dynamic conversations—but with the addition of text-to-speech (TTS) technology that speaks to callers out loud. The AI developer who created Sasha, FrontdeskAI, says the branded virtual assistant saves Sensory Fitness $30,000 per year.
4. Conversational Interactive Voice Response (IVR) Systems: Yapi Kredi
The conversational AI that powers Sensory Fitness’ Sasha can be woven into IVR systems to improve user experience during customer service calls. Yapi Kredi is a Turkish private bank that operates a contact center with more than 1,000 agents. Before the advent of AI, this call center used a menu-based, push-button IVR system—with all the associated customer frustration.
The bank engaged conversational IVR provider Sestek, which uses AI technologies like NLU, NLG, and TTS to automate customer service interactions—without the menus. Callers can simply describe their needs in their own words, and the AI translates them into actionable requests, responding with dynamically generated speech. This intervention doubled the number of self-service transactions for the bank and boosted their customer satisfaction score by 10%.
5. Brand-Owned Voice Commerce Applications: bol.com
In 2021, Dutch e-commerce superstore bol.com launched into voice commerce and AI-powered customer service. Their Google Assistant integration is ahead of the curve: Not only does it answer questions, share daily deals, and update buyers on their orders, but it does so with a unique, branded TTS voice. This voice was itself constructed using deep neural networks (DNN), an advanced form of machine learning that is a subfield of AI.
“We launched [the voice interface], and we did not love the robot voice we had with Google Assistant,” Vera Rensink, strategy and business developer at bol.com, said in a webinar exploring the use of custom branded TTS voices. “That’s why we got in touch with ReadSpeaker.”
Artificial intelligence contributes to ReadSpeaker’s construction of custom TTS voices, too; their VoiceLab uses deep neural networks (DNN), an advanced form of machine learning, to construct all-original TTS voices for brands and creators. In the case of bol.com, that turned out to be a lifelike male voice that sounds trustworthy, kind, and helpful; core traits of bol.com’s brand. Learn more about this instance of AI-powered customer service here, or visit ReadSpeaker for details about custom branded voices in AI customer service.