Top 3 Mistakes to Avoid so your Chatbot Doesn’t Fail

It seems like every company on the block has a shiny new chatbot. That shouldn’t come as a surprise considering they’ve been proven to improve customer support and service environments, and help consumers find what they are looking for more easily. In fact, research from Gartner suggests organizations are seeing a reduction of up to 70% in calls and live agent chat volumes after implementing a virtual assistant. However, Gartner also predicts that 40% of chatbots deployed in the last year will be decommissioned. 

To prevent becoming just another statistic, there are a variety of precautions that can be taken to ensure your chatbot and Conversational AI strategy will succeed. Below, we explore some of the common mistakes companies make when deploying a chatbot, and how you can avoid them.

 

Mistake #1: Too quick to deploy

As you begin to build and deploy your chatbot or virtual assistant, every step in the process is critical. Testing is crucial, and if you are not testing thoroughly enough, it will not take long for flaws to surface. Customers, especially those who may be skeptical about communicating with AI, are quick to dismiss a bot if they feel it is not capable. It is much wiser to delay your launch and spend more time testing and discovering flaws for yourself versus releasing your AI prematurely and leaving your customers to uncover them. 

We get it. A quick deployment might be driven by a strategic business event, and sometimes you have no choice but to launch and hope for the best. If that’s the case, ensure you have a team dedicated to training and optimizing your chatbot so if content gaps and flaws surface, you can react quickly to them. After all, launching your bot is just the beginning of your Conversational AI journey, not the end. 


Mistake #2: Expecting too much from your bot

While using Conversational AI is incredibly helpful, it can’t be your organization’s sole provider of customer service. Placing too much responsibility on your bot, especially in its early stages, can be setting you and your customers up for disappointment. Defining specific functions and use cases for your bot will ensure it is performing as expected, and complementing your existing customer service environment. It is also important to be transparent with your customers about the functions your chatbot is capable of, and familiarizing them with the type of questions and issues it can handle. This will help to maintain their trust as well as manage their expectations, lowering any chance of your bot disappointing them. If customers are led to believe that your bot is more capable than it is, they will become frustrated very quickly. 

According to Kissmetrics, around 70% of customers leave a business due to poor customer service, while only 14% will leave a business due to a lack of satisfaction with products or services. Customer satisfaction with your bot must always be a priority. 


Mistake #3: Lack of maintenance and AI optimization

No matter how intelligent or capable your Conversational AI is, it will always need to be maintained and optimized to continue performing favourably. Even the best bots become useless if they are left to operate independently with no ongoing training or optimization. Without regular maintenance or a dedicated team committed to improving its performance, your bot will quickly change from a helpful service to an outdated burden. 

Training and optimizing your bot regularly ensures it will continue to get smarter and grow alongside your organization and customer needs. This is something to consider if you plan on investing in a DIY chatbot where you are responsible for maintaining it internally. It is important that you have the resources and staff dedicated to the success of your bot and its regular optimization, otherwise your investment will fall flat. In order to keep it optimized and performing well, you’ll need to take note of instances where it did not have a response to questions asked or when customers were not satisfied with it’s performance. Once a customer is finished with your bot, be sure to have it ask for feedback on the interaction. This will keep you updated on your Conversational AI’s performance and give you insight as to when improvements need to be made. 

As Conversational AI continues to make the transition from a novelty to a norm, customers expect more from bots and have less patience for error. This is why it’s more important than ever to ensure your Conversational AI is the best it can be. One surefire way to guarantee your bot is successful is to partner with an experienced managed service provider who will be committed to improving and optimizing your bots performance, and can analyze conversations to provide rich business insights.

If you would like to learn more about the pitfalls in Conversational AI and how to avoid them, download our whitepaper on the 5 Reasons Conversational AI Fails and the One Way to Guarantee Success.

Related posts

0 replies on “Top 3 Mistakes to Avoid so your Chatbot Doesn’t Fail”

Artiom Kreimer

VP, Product & Analytics

Artiom has spent 10 years in software and mobile engineering, specializing in quality assurance and customer service. He has worked in testing and QA at both startups and in enterprises such as Clickfree, TELUS, and Freescale Semiconductor.

Michel Benitah

VP, Optimization & Delivery

Michel has 20 years of experience in leading the successful delivery of Conversational AI and Natural Language Customer Care solutions to some of the largest financial, telco, healthcare, utilities, and retail enterprises throughout North America. 

 

Prior to joining Wysdom, Michel spent 20 years at Nuance Communications, holding senior management and leadership positions within the enterprise division, most recently as director of the Toronto office and professional services team.

Frederic Lam

SVP, Sales

Fred brings in 25 years of international experience in sales and business development across North America, the Caribbean, Asia-Pacific, Europe, and the Middle-East.

 

Prior to Wysdom.AI, he held sales leadership positions at Oracle, Redknee, and Movius/Glenayre, successfully growing revenues in both large and small organizations. Fred has also been involved in the start-up community in the earlier stages of his career as an Investment Manager with SP Capital and was an alternate director on a few investee companies.

Karen Chan

Chief Engineering Officer, Co-Founder

With 20 years of experience in software and mobile, Karen has held senior technical roles at 5 startups, including Wysdom.AI, Clickfree, Mobile Diagnostix (HP), Teamatic, and Virtualthere.

Karthik Balakrishnan

Chief Technology Officer

Karthik has over a decade of hands-on, proven global expertise in emerging technologies and implementing intricate platforms and solutions for telecommunications and enterprise during his time at Amdocs, with senior positions in their India, Cyprus, America, and Canada offices.

Nitin Singhal

Chief Operating Officer

Nitin has over 20 years of success in global executions of business technology, driving operational efficiency and digital scalability for some of the world’s largest enterprise clients. 

 

Nitin spent 16 years at Redknee holding executive positions in Research and Development, Customer Operations, Partner Alliances, and most recently as COO.

Jeff Brunet​

President, Co-Founder

Jeff has more than 20 years of experience in the startup world, founding and growing 4 software companies: AracNet, Mobile Diagnostix (HP), ClickFree, and Wysdom.AI. 

 

His in-depth understanding of software development and the challenges in making new technologies successful in the startup world prove invaluable as he serves on the boards of XMG, SurfEasy (Opera), Locationary (Apple), Groupie, and as an advisor to Pushlife (Google), LogMeIn (IPO) and HP. 

 

Jeff holds 23 issued patents in the wireless and consumer electronics spaces and is the lead inventor on 30+ pending patents.

Ian Collins​

CEO, Co-Founder

Ian has founded and grown 6 technology companies over the past 20 years, primarily in the enterprise software space including Wyrex, Mobile Diagnostix (HP), Clickfree, and most recently Wysdom.AI. 

 

Ian invests, mentors, and sits on the boards of several startups in the Toronto area.