The resilience brands have shown over the past two years has been remarkable. Given an unpredictable commercial landscape, brands had to adapt their offerings in a hurry, spearheading digital initiatives that may have been years in the making and collapsing timelines down to weeks or months. Now, as consumers have also adapted, brands need to maintain momentum on their digitization efforts to improve and optimize customer experience and support.
One key avenue for brands to explore in these efforts is chatbot design and usage. Once thought of as an inefficient hindrance to personalized customer support, breakthroughs in AI and ML have transformed chatbots into a vital tool in modern ecommerce.
The cost savings alone make enhanced chatbot design an important initiative. According to a Juniper Research study, “retail sales resulting from chatbot-based interactions will reach $112 billion by 2023, up from $7.3 billion in 2019, representing an annual growth rate of 98%.”
By leveraging AI-driven chatbots, brands have the power to increase productivity, reduce customer wait times, expedite paths to human agents and receive improved data analytics and reporting, all while providing customers an always-on mode of contact to get the answers they need, when they need them.
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How Chatbots Increase Employee Productivity
Early iterations of chatbots tended to cause more frustration than answers for customers. A simple query into a chatbot or virtual assistant might be no better than a basic search on the company website. Rather than being delivered an actual answer, a customer would be given a link to an FAQ page, or some other redirect link surmised from keywords in the question.
With their question still left unanswered, the customer often sought an escalation to a human agent, even if the query was a simple shipment status update or a return request.
Advances in conversational AI and natural language processing have made chatbots far more discerning in their results. With a next-gen chatbot engine, a company’s entire information architecture, including CRM systems, order management systems, intranet, content management systems and more can be integrated and usable in a way that didn’t exist before.
Now, a customer with a top-level customer service inquiry can be given a direct response in context. With the majority of customer support engagements revolving around common questions — store hours, order statuses, gift card balances et. al. — customers can get the answers they need without involving a human agent. When recalls or store issues arise, the system can be equipped to provide appropriate automated support. As a result, agents are freed up to focus on escalations and high-value interactions with customers.
Even when a human agent is needed, an AI-powered chatbot can first diagnose the issue type. After gathering all preliminary information, the automated system can connect the customer (and pass along the data gathered) to the team best suited to assist. When the conversation ends, the AI system can handle the interaction reporting and summary so that the agent can return their focus to what they do best — supporting and delighting customers.
Reducing Customer Wait Times and Points of Friction
As the workforce has become more remote, work hours have become less predictable. With a more digitally connected customer base, brands can no longer anticipate when support inquiries will spike. Staffing human agents in a traditional 9-to-5 support window may not work for the schedules of a remote workforce.
In the past, customer support engagements that occurred on off hours would either be met with a lack of response (or a suggestion that they reach out during hours of operation), or there would be lengthy wait times as the minimal off hours staff responded to customers in order.
Presenting self-service options along with a chatbot that addresses topline customer service inquiries not only eliminates the burden from agents answering repetitive questions with answers customers can find themselves, but it shortens the path of escalation for customers with more complicated queries. It’s estimated that 80% of standard questions can be answered through chatbots. Allowing human agents to focus on the more challenging 20% reduces friction across the entire support journey, enabling a more agile customer experience.
Building a System That Continually Improves
One reason chatbots are emerging as an essential tool in the digital transformation of ecommerce is their scalability. In a human-led system, there is a limit to how many customer inquiries agents can manage at a given time. In an AI- and ML-driven support engine, it doesn’t matter if there are 500 or 5,000 inquiries — the system can handle it.
What’s more, the system learns from its history. Older, manual support systems lack the data analytics and reporting to improve over time. Modern chatbots can assess everything from inquiry types to volume spikes to customer demographics, which can all help identify where customers struggle in their journey.
If a brand knows where customers are reaching out for support in the purchasing process, or which products are receiving more post-sale support questions, they’re better able to adapt messaging or informational content to anticipate customer points of friction before they occur.
Through machine learning and natural language processing, today’s chatbots can also learn from the conversations human agents have with customers, so that the chatbots, over time, can answer a wider range of questions with more thorough information.
The demand for digital offerings will continue to rise as more consumers get comfortable with technology and digital natives increase their share of the market. Luckily, the improved sophistication of chatbots, aided by AI and ML, is occurring alongside this transforming consumer base. Brands that adapt to the times will find major cost savings while enhancing customer support across the board.
Tracey Zimmerman is the President and CEO of Robots & Pencils, a digital innovation firm focused on transforming business with mobile, web and frontier technologies. With over 20 years of experience in marketing, technology, and process innovation she has been a major growth driver for Robots and Pencils, championing strategic partnerships with Slack and Salesforce and expanding the Executive Leadership Team. Previously, Zimmerman was a software developer, analyst and consultant for multinational companies across the financial, education and medical sectors, including Bank of America and Siemens Healthcare.
