Automated customer engagement solutions aren’t popular with consumers, as many of them are simply poorly designed.
With most customer interactions moving online almost overnight, brands have leaned a lot since the start of the pandemic to define what their online experience should look like and, most importantly, how they could bring a touch of freshness to the customer experience in a digitally saturated world.
Making a lasting impression on offline consumers was already a challenge, and the equation most businesses now had to solve was to answer a large number of customer queries and differentiate their online experience from the competition, to engage. consumers who were bombarded with brand signals, and couldn’t bear to stare at a screen for a minute longer after days spent on Zoom.
Among the technologies that brands have favored to transform the customer journey, there are chatbots. Unfortunately, their implementation is often short-sighted and counterproductive, driving visitors away rather than engaging them effectively.
The human touch
As the world stalled, customer services and call centers were quickly saturated with calls from worried customers who weren’t answered because contact centers were closed. Chatbots have been added to the company’s ranks to take some of the load and take the pressure off these teams. But there was an equally important goal of offering visitors something different and more innovative than any other FAQ. When done right, chatbots are supposed to provide customers with an interactive experience that resembles a conversation and is as close as possible to interacting with a human being.
Indeed, despite years of increasing their digital know-how, consumers, especially in Australia, are still in dire need of a human touch. We recently conducted a study looking at consumers’ preferences when interacting with brands, and half of respondents said they always favor face-to-face or phone interactions. The other half who mentioned digital channels, still want a human being on the other end, prioritizing emails or live web chats with agents.
Unfortunately, consumer experiences that a large number of inadequate chatbots mean that they are unconvinced that our chatbot friends are successful in creating an engagement medium that resolves their issues or queries quickly and effectively. Only 2% of Australians said chatbots were their preferred method of communicating with brands, showing how poor chatbot implementations are.
Where is the love?
A plethora of organizations claim to provide clever bots and assistants, but customer feedback shows that many lack the simplest conversational and behavioral design, giving customers a disappointing and frustrating experience with the brand and keeping them from leaving. engage more in these channels.
A typical example is when chatbots consistently pop up as soon as visitors browse a website and only provide a very small set of pre-scripted options for the survey. Do we want a salesperson to jump on us every time we walk into a store and only allow 3 choices of questions? I do not think so.
Unfortunately, many businesses are drawn to cheap chatbot solutions and the promise that it will modernize their customer experience, when it only damages it. The industry needs to improve its standards if it doesn’t want chatbots to become a nuisance that customers want to avoid at all costs. Organizations need to view chatbots as real business applications, not just âscience experimentsâ.
Who is a good chatbot?
So why don’t most chatbots meet our expectations? And what should businesses look for in a good chatbot?
1. AI is too basic to handle human language.
Most chatbots are very limited to what they allow customers to request. All questions outside of the scripted options (if allowed) are often answered with an “I don’t understand your question, please select one of the 3 options …”. Few of them are a step higher on the maturity curve and are able to recognize certain keywords and customer intentions, and provide scripted responses. But for anything more complex than that, like conversational and transactional self-service experiences (which means allowing customers to ask their questions however they want), the quality of the AI ââand conversational design that underlying the solution is essential and usually requires an advanced engine of natural language understanding, with deep neural networks and a complex dialogue engine that can converse with the customer depending on the questions they ask and the amount of input. information it provides. In other words, an AI who is properly trained to understand natural language and human conversation and who can tailor their responses according to the flow of the conversation.
2. There is no clear business goal behind the chatbot.
There are still too many companies that don’t clarify exactly what they want their chatbots to accomplish before deploying them. What does success look like? Whether it’s cutting customer service costs or generating more leads, the answer to that question should be a chatbot’s design blueprint. In addition, what data and measurement systems have they put in place to measure this chatbot’s success or not? How these feedback mechanisms influence the optimization of the chatbot and its future capabilities. What is the optimization strategy and how quickly can your chatbot adapt?
3. Customer preferences are not taken into account in the design.
How customers interact with a brand is an ongoing source of information that should guide the design and capacity of chatbots before and after they are deployed. This ongoing analysis allows us to identify obstacles and weaknesses in the experience and make the necessary changes to the bot design. For example, if customers are constantly viewing a chatbot with needs it wasn’t designed for, how do you quickly assess and adapt to meet that customer need?
4. The chatbot is not adapted to the user journey, the channel or the platform.
Interacting with customers on a website, through a smart speaker, or on WhatsApp is different, and replicating self-service interfaces from one channel to another is complex. That it works on a website, for example, doesn’t translate to a voice channel. Consider the possibility for the customer to share a photo to help solve their problem. Not all channels allow this. Effective chatbots have custom designs for each channel that take into account the specifics of each platform and how customers engage with it.
5. The chatbot is not designed for authenticated use cases and fraud prevention.
Online fraud and scams have increased dramatically since the start of the pandemic, and it is the responsibility of every brand to give their customers the assurance that they take their privacy and security seriously when interacting with them. them. Smart chatbots, digital or voice, now incorporate automated authentication features that allow them to automatically identify a customer based on their voice, the way they type, slide or hold their device when interacting with them. This âzero effortâ authentication based on behavioral biometrics ensures customer protection while preserving the customer experience.
A properly trained chatbot can do wonders for customer service and the experience. An example of a chatbot that checks all of the above is the Commonwealth Bank of Australia premium The Ceba virtual assistant, which has evolved instantly, understands and responds to 450 types of customer requests, i.e. 90% of customer requests, and approximately 70,000 different questions since its deployment in 2018.
The necessary strategic thinking and intricacies of building a successful chatbot or virtual assistant should not be underestimated. If this is the case, organizations will end up with dumb chatbots that cannot solve the simplest customer queries or engage them effectively, and in the worst case, frustrate them and negatively impact the brand. After customers have had a bad chatbot experience, it takes a long time for them to try again.
Great digital experiences are now more common and as consumers experience them, their expectations of other brands increase. Their tolerance for bad customer experiences fades to the same extent.