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Why Many Enterprise Chatbots Fail — A Study

Chatbot Developers Need To Know — A Study

Today, we’ll look at how chatbots or virtual assistants evolved, how to build chatbots for different cases, what aspects to consider when selecting the right use-cases and while building them, and what are the common challenges and solutions that most enterprises encounter.


How many of you guys have heard about this term?

Do you agree that earlier the culture was just meant to be about religion?
But, as time passes, things are changing. There is a development in the human lifestyle as humans evolving, it can be about anything, including art, devotion, politics, economics, psychology, and so on.

A study has been going on for a long time, but to better comprehend, it is a scientific study of humanity, concerned with human behavior, human biology, cultures, and societies. There are four major areas to consider in it:

  1. Archaeological — Which is a study of human activities through the investigation of physical evidence.
  2. Biological — This is focused on the study of human and non-human evolution. How different climates or temperatures, affect human evolution in different regions.
  3. Linguistic — About understanding the process of human communications, verbal and non-verbal.
  4. Cultural — This is the study of human similarities and differences in the community or between communities.

So now, these findings are no longer confined to textbooks or geographic channels. Researchers are attempting to understand how this data might be properly applied to assist humans by giving exactly what they want.
This is how organizations are understanding their customer's emotions to give them better comfort and meet their demands.

People’s modes of communication have shifted from telegrams to telephones, cell phones, and apps as technology advanced.
They figure out the quickest, smartest, and most cost-effective method to communicate, purchase something, transfer money, and make deliveries, etc…
In fact, people are treasuring their time for better work and spending time for themselves and their families.

And,,,,, That is how “chatbots and virtual assistants” became a reality!

People don’t like waiting for support on call forever. However, some people are hesitant or shy to speak. This technology has made their lives much easier.

Some may argue that virtual assistants such as Siri, Ok Google, and Alexa don’t always answer my questions, but always says I’m still learning.
They actually mean it. They’re trying to understand you, your likes and dislikes. That’s how everything gets off to a good start.
For example, when you adopt a pet, it takes time for the animal to get to know you and the environment. The same goes for these bots.

So, what are chatbots?

In simple language –

Any device that takes our text or voice command and performs our tasks is a chatbot.

A Textbook Definition –

A chatbot is a computer program that simulates and processes human conversation (either written or spoken), allowing humans to interact with digital devices as if they were communicating with a real person.

Trending Bot Articles:

1. How Conversational AI can Automate Customer Service

2. Automated vs Live Chats: What will the Future of Customer Service Look Like?

3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

Different types of chatbots?

Any method of building a chatbot depends on the use case.

1. Rule-based chatbots are mainly used for tasks that have a lower scope, limited and fixed range of transactions.

For example, chatbots for McDonald's, Dominos, Bus or Cab booking, Real Estate etc…

2. Smart Chatbots are highly backed by AI. There will be an NLP engine to identify the use context. The response provided by the bot would be more precise and no extra information is shown. The use cases chosen here would be wider in scope.

Few examples like — Alexa, Ok Google, Siri. And few Chatbots were created for customer support, IT team, Insurance Bots etc…

3. Hybrid Chatbots — This method is flexible to use and can adopt wider scope and wider users.

So, are Chatbots fit for any use-cases? The answer is Yes and No.

Yes, because the possibility is at the sky level. But, we need to look through some important factors before we decide to build the chatbot.

How to choose the chatbot use-case?

  1. Need — First and foremost is, do users really need a chatbot? Obviously, we do not want to waste our human and infrastructure resources for nothing.
  2. Users — Do we have a bigger user base for this? It shouldn’t be like we developed and nobody is there to use.
  3. Cost — Does the use-case minimize the cost? like, if a particular task was performed by 3–4 associates regularly, and by building a chatbot can save associates from doing the boring job? That saves multiple resources cost.
  4. Time — Can this innovation save your time? Can you get the answers quickly? For example, quickly book a cab, find the nearest gas station, or the best example is a ticket created to fix the software installation issue that takes 2–3 days SLA, can be solved in seconds if the same or similar queries are already answered by ADE associates before. The bot can pick that answer to show users.
  5. Trend — If the current approach or the technology used to resolve the issue or to perform a task is old, and, a chatbot is an easy access for users to get that task done.

Things to note while building chatbots

1. Convenience:

  • Choose a place (or omnichannel) that is most convenient for users to access the chatbot.
  • Ability to understand the language user like to chat with and respond accordingly.

2. Reliability (Dependable):

  • Handle the user queries accurately with a minimum 80% of accuracy.
  • Provides the relevant information.
  • Handle the escalations smoothly.
  • Having alternate measures to answer the queries (Live Support).
  • Avoid users from going to other sources to search for data.

3. Availability: To make it available 24/7. Should be available even during emergencies.

4. Scalable: Ability to accommodate new features without much effort.

5. Better UI/UX: Giving a better experience by look and feel brings a smile to the user’s face.

6. Handle Requests Load: Ability to handle millions of requests without breaking the conversation

7. Logging:

  • Logging the flow of data and the user conversations for analytics
  • To provide a better user experience from the past experience
  • For personalization

8. Monitoring: Having a dashboard or any tool to monitor post-production deployments

If you read the points again from the top, these also answer our point “why should we use chatbots?” isn’t it?

But, it is not over yet, there are other important points that benefit the business

How does it benefit the business?

  1. Improves customer retention: by keeping the ongoing conversation. Like how Instagram and Facebook keep us engaged in the app by giving more relevant and similar information.
  2. Increase Sales: How many of you agree that pandemic has increased sales? Bots encourage the consumer to purchase more relevant items.
  3. Promote Products: By providing offers and gifts, and Highlighting the product by comparison, demoing new items etc…
  4. One-Stop-Shop: Book tickets, events and perform other actions like tracking, cancellation, modify etc.
  5. Better UI/UX: show nice carousels, images, etc… to give a good feeling about the products
  6. User Feedback and Personalization: Asking user's feedback and observing user shopping patterns helps in personalization.
  • Who are they?
  • What do they expect? What are their preferences?
  • What are their pain points?
  • How is their experience with AI chatbots?

Let me show you the trending elements that a customer expects in his/her shopping experience.

E-Commerce customer experience trends 2021

What decides your chatbot is successful?

In short, it must fulfill all the business expectations.

  1. First of all, the percentage of happy customers
  • From their feedback — +ve or -ve
  • Their mood or sentiment analysis

2. By Chatbot accuracy — Above or equal to some threshold. Like above 85% or 90%

3. By the containment ratio

Even when we are good at considering all the above factors, there are some common challenges that most enterprises face.

Common Challenges

  1. Multiple Chatbots
  • When enterprises create multiple chatbots, users cannot know which chatbot to use for which problem?
  • If I am done with one query, for another I need to navigate to another place.

2. User spelling mistakes are hard to understand by chatbots, due to which the bots accuracy gradually drops

3. Engage live support when the chatbot escalates certain queries.

4. Complex Infra Setup: Every time it takes a while to build a new chatbot from scratch, test, retune, deploy and monitor.

Possible Solutions

So, how do we overcome these challenges?

  1. Collaboration
  • Teams who are building the chatbots need to collaborate. Define standard rules of building chatbots
  • Every chatbot deployment in the enterprise must be reviewed and deployed

2. Build a concierge bot to handle multiple chatbots from a common screen. I have explained it in detail in my previous article.

3. Set up a common monitoring platform for all the chatbots across the enterprise.

4. Setup platform to reuse the architectural components so that no other development team needs to spend time again in rewriting. That saves a lot of time.

5. Automate chatbot building process. Leverage AI techniques to fulfill the need. For more — check this article.

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Why Many Enterprise Chatbots Fail — A Study was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.