– but they don’t necessary have to be human. Increasingly, businesses have found successful ways to improve customer interactions with chatbots, sometimes also known as interactive agents or Artificial Conversational Entities. While consumers have already grown accustomed to peppering Siri with questions or barking orders at Alexa, an organization doesn’t have to be a tech giant in the realm of Google or consumer goods behemoth like Amazon to benefit from using chatbots for business.
How can businesses use chatbots?
An application of AI and natural language processing, businesses often use chatbots for customer support, boosting productivity for human employees and reducing overhead by cutting down on labor costs for menial tasks.
Business can use chatbots for many functions, including:
- Monitoring, routing, and managing inbound customer calls or messages
- Connecting customers to human customer service agents
- Managing customer support through instant messaging, including in-app, on websites, or through Facebook messenger
- Generating text messages
- Hosting scripts
- Importing customer history in real time to fuel interactions
- Search functions
- Offering guidance or recommendations to customers
- Scanning big data
- Customizing alerts
- Alerting customers when an order is ready
In some cases, chatbots can do more than just tackle tasks, they can help build rapport with customers. For example, online mattress company Casper offers its Insomnobot-3000 from 11 p.m. to 5 a.m. for its insomniac customers to chat with. And while it may throw in plugs for the product itself, the main goal is simply to chat with late-night customers about casual topics ranging from pizza to the latest developments on Stranger Things.
Recommendations made through a chatbot can also be more data-driven, after the bot interacts with the customer. For example, cosmetic company Sephora allows customers to upload a photo and then work with their Color Match bot to find the perfect lipstick shade.
Cutting-edge chatbot applications
Developers at X.ai are fine-tuning their AI, Andrew Ingram, an innovation aimed at making scheduling a meeting less of a headache. Why? Because busy professionals can simply ask the bot to schedule the meeting, and he’ll do the rest. While on the surface that may seem like a small task, Americans are estimated to schedule 25 million meetings per day. And at an organization level, the ability to offload the chore of shuffling schedules can not only represent less payroll for administrative tasks, but can also mean more productivity for specialized professionals. X.ai’s competitors, Clara Labs, use their chatbot as a go-between, skimming the most simple tasks (for example: schedule a meeting at 5 p.m. at our 23rd. avenue office) off the top, but diverting more complex requests to a human assistant.
Some companies, like Luka, aim to go much deeper. Luka’s AI chatbot Replika is designed to ask profound questions and offer emotional support – without introducing any judgment. Although most of the current users think of Replika as the kind of friend who helps them understand themselves, business could benefit from this introspection sans emotion in the form a career coach or to offer support for employees going through a difficult time. The human propensity to open up to AI was apparent even in its inception in the 1960s, when MIT professor Joseph Wizenbaum built ELIZA as an experiment. ELIZA was programmed to reframe statements provided in psychotherapy as a question, and users often formed deep affections for ELIZA. (Wizenbaum himself was so distributed by this he later became an outspoken opponent of the technology.)
Similarly, an AI system developed in 2011, Ellie, assists doctors at military hospitals in detecting post-traumatic stress disorder (PTSD), depression, and other mental illnesses by conducting interviews with soldiers. In this case, Ellie is a supplement to human work.
Developing chatbots for customer support
Even if the chatbot is going to be tackling more routine tasks, to develop a functional chatbot, organizations have to plan, program, and implement carefully, as the little details can often sway the experience between natural and bizarre one for customers.
- The tone the chatbot should use, whether formal or casual.
- Designing an algorithm that allows the machines to respond to normal, or natural, human language, which doesn’t usually sound like computer code.
- Allowing chatbots to respond to off-topic responses or small talk that may seem normal for humans but can derail a bot from its scripted options.
- Training the AI will require testing the algorithm with substantial amounts of data. Organizations needs a plan for how they will obtain or input this data.
While the ability to offload menial tasks to an endlessly patient machine may be appealing, it also raises some considerations. For example, after Google’s demonstration in May 2018 of a virtual assistant scheduling a haircut, audience members at Google’s I/O conference were perhaps most impressed by the sense that the person receiving the call was unaware they were speaking with a robot. The question raised: should they have been made aware?
Organizations and users alike should also be mindful that no matter how convincing the exchange, the interaction agent, or chatbot, is still programmatically designed, which means its ability to react is restricted by what is has been programmed to do or what it has experienced. While it may improve over time, unusual, or critical, situations will likely require some human help as well.
The same is true for organizations looking to implement or improve sophisticated AI chat bots in their businesses. While the technology is important, the humans designing and maintaining it are critical. Find out more about how adding a Genie to your tech team can support your chatbots or help address any other IT challenges by visiting https://www.techgenies.com/techgenies-advantages/.