When we used to hear the word “chatbots,” pain often comes to mind. Frustration with the novel was the norm. With chatbots that were mostly able to receive a question and reply, “I am sorry, I can’t answer that. However, I will contact someone that can help you with it. You should receive a reply in 24 hours.”
Yet, chatbots have come a long way, and the next-generation bots, like the new Chat GPT and those under development by Google, are excellent. They will become a vital part of the customer experience and take the burden of repetitive tasks, simple tasks, and questions away from agents while improving satisfaction results by quickly providing the info clients need.
Chatbots in Brief
Chatbots had evolved since their inception when programmers wanted to surpass the Turing Test and create artificial intelligence. For example, in 1966, the ELZA program fooled users into thinking they were talking to a human.
A chatbot is a computer program often using scripts that can interact with humans in a real-time conversation. The chatbot can respond with canned answers, handle different levels of requests (called second and third-tier issues), and can direct users to live agents for specific tasks.
Chatbots are being used in a wide variety of tasks in several industries. Mainly in customer service applications, routing calls, and gathering information. But other business areas are starting to use them to qualify leads and focus large sales pipelines.
The first chatbots of over 50 years ago were intended to show the possibilities of AI. In 1988 Rollo Carpenter’s Jaberwacky was designed more for entertainment but could learn new responses instead of relying on canned dialog only. As they progressed, chatbots surpassed “pattern matching” and were learning in real-time with evolutionary algorithms. Facebook’s Messenger chatbot of 2016 had new capabilities and corporate use cases.
The general format of a Chatbot system takes inputs looking for yes-no answers or keywords to produce a response. But chatbots are evolving to do more comprehensive processes, including natural language processing, neural networks, and other machine learning skills. These chatbots result in increased functionality, enhanced user experiences, and a more human-like conversation that improves customer engagement and satisfaction.
Benefits of Chatbots
Improved customer service. Clients want rapid and easy resolutions. HubSpot found that 90% of customers want an immediate response to customer service issues.
This is seen with the increase in live chat, email, phone, and social media interactions. Chatbots can provide service to users 24/7, handling onboarding, support, and other services. Even robo-advisors can use chatbots as a first line of contact.
More advanced systems can pull from FAQs and other data sources that contain unstructured data like old conversations and documents. Chat GPT uses a massive supply of information up to its 2021 cutoff point.
Improved sales. Chatbots can qualify leads and guide buyers to information and products that fit their needs, producing a personalized experience that builds conversions. For example, they can suggest promotions and discount codes to boost purchase likelihood. They can also be a checkout page aid to reduce cart abandonment.
Money savings. The goal of chatbot deployment for service and sales support is often to reduce casts. Chatbots can service simple and repetitive tasks allowing human agents to focus on complex issues.
For example, if a small HR team is slowed with holiday and benefits questions, a chatbot can answer 90% of these, lessening the HR team’s load. An Oracle survey found that chatbots could produce savings of more than half of a business’s upfront costs. While the upfront costs of chatbot implementation are high, the long-term cost savings in staff equipment, wages, and training will outweigh the initial spending.
Chatbot Implementation Mistakes
While chatbots cannot do everything yet, and it will be a long time before they can do many tasks, they have a skill set that can be used. They can help humans, allowing them to work on more human-required tasks.
No human option. This is a mistake many companies make. Chatbots cannot solve all problems, and the client should have a way to escalate their interaction to a human who can solve it.
Lacking customer research. A bot needs to know what to look for and what to address. If an implementation starts with the most common and time-consuming questions and decides if a chatbot can solve these, it will prove its value many times over.
Neglecting tool integration. A well-built chatbot will be part of the contact center platform, aiding agents and supervisors. Able to pull info from multiple sources and escalate to a live agent with useful contextual information allowing the agent to quickly take over from where the chatbot ended.
Use Cases of Chatbots
How can businesses use chatbots? Here are a few examples of great implementations improving customer service and outcomes.
Banks or online brokers will generally field simple questions from depositors and borrowers. However, many may come at times of vulnerability. The rising cost of living means a closer focus on finances. Clients may have pending transactions, payments, fraud, or other issues; technology could allow them to monitor these in real time.
If there is only a call center to address these issues, they will have added pressure. But these can be addressed across multiple channels. A banking chatbot with sentiment analysis can handle text-based digital channels (web chatbot, social media, SMS messaging).
Launched on the website, mobile app, and social media, this virtual assistant can handle first and second-tier queries (credit card payments, checking account balances). The implementation of sentiment analysis can detect upset customers, quickly getting them to a natural person.
Chatbots can also aid with the creation of balance alerts, alter other settings, and set up payment reminders, ensuring that both the present issue is solved and the likelihood of a future issue is reduced.
As a commercial and residential real estate business grows, more calls are coming in from customers covering a wide range of issues (rent, maintenance, renovations, and potential customers). As a result, they are taking up the contact center’s resources. For example, a chatbot could answer routine renters’ questions, guide them to self-service solutions, or submit a service ticket.
Chatbots can also collect info that will allow the direction of their query to relevant categorical information or help from the related agent. This reduces high call volume and becomes a source to produce tickets 24/7, not just when the office is open, providing notifications to the clients when their submissions are updated. Chatbots can also be set for rent reminders via text and provide online payment options to improve on-time payments—a win-win for the user and the company’s bottom line.
Logistics customers want to know where their items are and in real-time. Accurate tracking info is more widely available, but with logistics, there are many variables to contend with on the global level. In addition, high volumes of location requests can overpower a company; even if they are simple requests, they stretch a company’s resources.
A chatbot can deflect many calls from the call center to automated phone response or web services that have a text chat service, providing callers with a way to track their packages and lowering the strain on the service staff, allowing them to focus on complicated issues.
Online retailers have a lot of spinning plates. Supply chain, warehousing, couriers, drop shippers, and other order fulfillment, and running an E-com site. When one piece fails, there are unhappy customers. If a manufacturer has assembly issues for a hot new product, the company may experience high call volume and service requests, resulting in many refunds and returns.
An AI-powered chatbot like ChatGPT can be a lifesaver, guiding customers to troubleshooting and instructional media such as video tutorials or the webpage’s knowledge base. It can also take customer feedback and use this information to improve service outcomes, further optimizing flow.
It can also be helpful in the returns process, streamlining the system, resolving returns without the need for a human team member. In addition, by deflecting most inbound calls to self-service, the call center’s volume is decreased, reducing wait times and producing cost savings. The chatbot could also generate viable leads helping consumers find the right products for their needs while upselling products and services through personalized recommendations.
All of the use cases for chatbots provided above are currently being employed and are solutions that use chatbots that are less sophisticated than ChatGPT. However, chatbots can provide higher levels of service that can instantaneously scale with a business while doing so at an attractive ROI.
There are thousands of chatbot implementations possible for today’s businesses, allowing customers to get the real-time service they need with more personalization and specificity than before; this will only continue to improve and expand, allowing more to be provided to consumers.
As chatbots improve their capabilities, their use will likely broaden in scope and volume. Many things humans did in the past, or do now, will be replaced by the faculties of ever-advancing chatbots. These humans will need to be trained to do other work or higher-level service tasks so that we don’t have a glut of out-of-work service personnel.
On the other hand, this training will result in more satisfying work for employees, which in the long run can improve their lives. Balance is needed to gain further acceptance of chatbots by employees and the populace as a whole.
Disclaimer: The information provided in this article is solely the author’s opinion and not investment advice – it is provided for educational purposes only. By using this, you agree that the information does not constitute any investment or financial instructions. Do conduct your own research and reach out to financial advisors before making any investment decisions.
The author of this text, Jean Chalopin, is a global business leader with a background encompassing banking, biotech, and entertainment. Mr. Chalopin is Chairman of Deltec International Group, www.deltecbank.com.
The co-author of this text, Robin Trehan, has a bachelor’s degree in economics, a master’s in international business and finance, and an MBA in electronic business. Mr. Trehan is a Senior VP at Deltec International Group, www.deltecbank.com.
The views, thoughts, and opinions expressed in this text are solely the views of the authors, and do not necessarily reflect those of Deltec International Group, its subsidiaries, and/or its employees.