AI Business Chatbot Strategy, The Fundamentals - ServisBOT (2022)

(Video) Conversational AI: Sales and Customer Service Chatbot Use Cases for Small and Medium Sized Business

Chatbots

By Cathal McGloin5 Minute Read

AI Business Chatbot Strategy, The Fundamentals - ServisBOT (2)Before diving into business chatbot strategy let’s start with a look at the evolution of chatbots.

How AI bots have emerged and are maturing gives me flashbacks to the early days of mobile apps,as businesses started to look to use mobile as a new means of engaging with customers and employees. The hype and promises gave both consumers and businesses reason for excitement and anticipation, opening up a whole new world of opportunity for how businesses would engage and conduct business with their customers.

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Remember the early mobile apps that businesses and brands launched? They were pretty basic, more informational than transactional. Fast forward a few years. By integrating with internal business systems and third-party software, mobile apps became much more transactional, enabling users to reserve appointments, book travel, notify customers of events and alerts, and deliver contextual information and experiences that allowed us unprecedented opportunities to transact and interact on the go. But this didn’t happen overnight or by chance.

Emerging technologies, that often seem simple to use and consumer-friendly, such as mobile apps then and chatbots now, can pose many unforeseen challenges as businesses adopt them. A chatbot strategy, no more than a company’s mobile strategy, will help guide your chatbot success.

The Hype and The Reality of Chatbot Implementations

Although the first chatbot, ELIZA, was conceived in 1966, the true power of chatbots has only recently become a reality as advancements and access to natural language processing (NLP) technologies and the ubiquitous nature of mobile devices and messaging apps have opened up a whole slew of business opportunities that put them at the center of digital strategy.

Chatbot deployments have been wildly successful but also have failed miserably for many businesses. Some companies jumped in too quickly without considering some of the longer-term implications of having a poor bot experience. Some under-estimated how easy it actually is to implement bots that can respond successfully to a customer and execute the necessary business tasks, without having to immediately hand over to a human agent. And for others, it’s been a combination of factors that have led to bots not meeting the desired expectations.

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When the pandemic hit in 2020, many businesses had to quickly pivot to digital business models and accelerate their digital transformation initiatives. Many organizations had already deployed a chatbot, others were still in the planning stage of the conversational AI journey. The crisis created unprecedented urgency in implementing digital assistants that could fully or partially replace the need for human workers to handle routine and repetitive interactions and tasks, allowing the human role to be focused on resolving more complicated customer or employee issues. The strategic role that chatbots could play in automation and digital engagement placed them firmly in the spotlight.

Some Considerations for Your Chatbot Strategy

Here are some perspectives on how you can avoid some of the common pitfalls in chatbot implementations and strive for success. Think of your chatbot strategy as a living plan that is not set in stone. It doesn’t have to be a lengthy or tedious exercise but these tips will help pave the way.

  1. Don’t Boil the Ocean: Like all new technologies, starting small is often the best approach. It can be tempting to yield to pressure from business leadership and try to bring multiple bot projects to market as quickly as possible. However, by picking a manageable chatbot use case and rolling it out to a small customer- or user- base before doing a broader rollout, kinks can be ironed out and poor experiences can be averted. The learnings gained in starting small usually open up new ideas for subsequent use cases, for broader reach, a better chatbot architecture, or for additional features.
  2. Prioritize the Use Cases:Since all chatbots are not created equal, it can be helpful to think of them in terms of different skills. Each industry can have unique needs for deploying digital assistants or bots and then each business has its own unique priorities and objectives. An industry-specific example of use cases is that of AI insurance bots that can be deployed at different stages of the customer lifecycle, assisting customers with online quotations, onboarding new policyholders, helping them file a claim, or renewing their coverage. There are also use cases that are more generic and applicable across multiple industries, for example, AI customer service bots that can be as simple as an FAQ bot or involve a more complex customer journey, like customer onboarding. Identifying the use cases across departments and prioritizing these in terms of the business value and complexity of development, helps tie bot investments to business strategy and key performance indicators (KPIs). Your KPIs or bot metrics will help you track chatbot success and set you up for continuous improvements.
  3. Think Transformation: Chatbots have the potential to change the way your business engages with customers so when considering the use cases for bots, don’t just think of a bot as something that replaces a human agent and works 24/7. Conversational AI enables a whole new model for engaging with your customers through fluid and frictionless conversations, in contrast to interacting via guided clicks, swipes, and forms. So, rather than having chatbots emulate your current workflows, consider how the power of conversation can eliminate or automate some process tasks, remove friction, and transform how you meet your customers’ needs.
  4. Prototype and Iterate: Proof of Concept (PoC) is often a preferred route for organizations to prototype a chatbot idea before investing in a full-blown project. This allows the business to experiment and agree on features, design, and technology, gathering feedback from early users and stakeholders to improve the bot experience. Remember that your bots are also your brand ambassadors so careful consideration to how they properly reflect your brand is an important part of early design and prototyping phases.
  5. Communicate Early and Often: As with any new wave of technology that has the power to replace humans and automate processes, the fear factor around AI is palpable. Gaining buy-in and understanding for chatbot projects from your employees, especially those that will be directly affected, is critical to company culture. Communicating the bot strategy and even including frontline employees in decisions around bot deployments, helps avert unrest and assure staff of their continued role. AI in the workplace is already a reality. According to Gartner’s Future of Work, the good news is that “few jobs will be replaced by AI, but almost all jobs will experience some automation or augmentation”.The best business leaders understand that the workforce will continue to be their greatest asset and like any game-changing technology, the manner in which organizations implement AI will set them apart.
  6. Don’t Forget About the Data (And How to Secure it!): One of the many downfalls of early chatbot deployments points to them being too simple to be effective. Unless a chatbot can execute the necessary business tasks, it will quickly fail or need to hand over to a human agent. And executing a business process requires rules and data, necessitating integration, security, and governance. As customers chat via messaging or voice, they may not provide, or even have, all the information needed for a chatbot to fulfill their need, requiring the bot to access data via an appropriate API. For example, if a customer asks via SMS chat to change their flight, the bot can retrieve the data needed to do this, filling in the information gaps such as PNR, payment details, itinerary, flight schedule, etc. Needless to say, security becomes paramount as customer data moves from the business system to the customer so authentication, data isolation, governance, and control become important. This mirrors the path of mobile apps as they evolved in the enterprise and backend-as-a-service (BaaS) technology emerged to enable apps to integrate securely with backend systems to deliver more meaningful experiences.
  7. Choose the Right Technology: When planning chatbot implementations, consider how they may need to scale and extend their reach beyond the initial use case or audience. Underlying infrastructure and architecture decisions, while not the skillset or priority for lines of business, can often make or break the success of any software project, chatbots included. This is where choosing an enterprise conversational AI platform can really matter in terms of speed to market, performance, reusability, scalability, and value.Read more about how a conversational AI platformworks to support successful chatbot implementations.

Chatbots are here to Stay and Grow!

There’s no doubt that conversational AI technology is a hot topic for today’s enterprise. While the pandemic may have accelerated its adoption, there is no going back. Crafting and implementing a chatbot strategy doesn’t have to be a long or tedious exercise and ServisBOT is here to help support you.

If you need more clarification about Conversational AI and chatbots, read our Conversational AI vs Chatbot post.

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If you’d like to learn more about how to progress your conversational AI journey and maturity please check out our new Guide for a Successful Conversational AI Journey.

(Video) SITSP 2019 - ChatBot with Alexa and SAP Conversational AI + Hana

FAQs

What are the 7 steps to create a chatbot strategy? ›

Let's walk through them in order.
  1. Audience. The first key to a successful strategy is to profile your ideal customers. ...
  2. Goal. To define the purpose or goal for your chatbot strategy, begin with the end in mind. ...
  3. Performance. ...
  4. Key Intents. ...
  5. Storytelling. ...
  6. Platform Strengths: ...
  7. Feedback.

What questions should a chatbot answer? ›

Your chatbot must be programmed to answer any question related to your product or service, this will avoid any confusion on what you offer and save time for your customer service team.
...
Common questions to answer
  • How much?
  • What's the price?
  • I need a quote.
  • How much does it cost?

What is chatbot PDF? ›

A chatbot is an artificial intelligence program and a Human– computer Interaction (HCI) model (Bansal & Khan,2018). According. to the dictionary, a chatbot is ''A computer program designed to. simulate conversation with human users, especially over the Internet''

How chatbot works step by step? ›

Put simply, chatbots follow three simple steps: understand, act and respond. In the first step, the chatbot processes what the user sends. Then, it acts according to a series of algorithms that interpret what the user said. And finally, it picks from a series of appropriate responses.

How do I make a chatbot for my business? ›

  1. 7 Steps to Develop a Chatbot for Your Business. Image: Zapp2Photo/Shutterstock. ...
  2. Define the problem. First of all, it is important to decide why you would need a chatbot. ...
  3. Create the conversation flow. ...
  4. Selecting the chatbot platform. ...
  5. Integrating the chatbot. ...
  6. Testing the chatbot. ...
  7. Analysing the conversations. ...
  8. Improve the chatbot.

What is the best AI chatbot? ›

15 top AI chatbot platforms:
PlatformRatings ⭐️Best for
DialogFlow4.3/5 (42 ratings)Businesses operating with Google Cloud
MindSay4.6/5 (41 ratings)Large businesses
Wati4.6/5 (76 ratings)WhatsApp customer service
Mobile Monkey4.9/5 (119 ratings)Customer service on social media
11 more rows
17 Aug 2022

Are chatbots AI or machine learning? ›

The Types of Chatbots

Chatbots are often associated with Artificial Intelligence (AI). This happens because AI gives them the ability to handle requests without the need for human intervention. However, some chatbots don't have AI and, as such, are more basic.

What is chatbot application? ›

At the most basic level, 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.

What is a chatbot example? ›

A chatbot helps in collecting contact information, providing available listings, and book viewings. Structurely's chatbot, Asia Holmes, is a great AI chatbot example to handle customer queries in real-time and make conversations effective.

What is a good question to ask a bot? ›

15 questions that will test your bot
  • Are you human? / Are you a robot?
  • What is your name?
  • How old are you? / What's your age?
  • What day is it today?
  • What do you do with my data? / Do you save what I say?
  • Who made you?
  • Which languages can you speak?
  • What is your mother's name?
9 May 2019

Which is the first chatbot made using AI? ›

ELIZA was the very first chatbot as mentioned above. It was created by Joseph Weizenbaum in 1966 and it uses pattern matching and substitution methodology to simulate conversation. The program was designed in a way that it mimics human conversation.

Why are chatbots useful? ›

Chatbots can automate tasks performed frequently and at specific times. This gives employees time to focus on more important tasks and prevents customers from waiting to receive responses. Proactive customer interaction.

Is chatbot an example of AI? ›

Chatbots, also called chatterbots, is a form of artificial intelligence (AI) used in messaging apps. This tool helps add convenience for customers—they are automated programs that interact with customers like a human would and cost little to nothing to engage with.

How are chatbots used in business? ›

Chatbots rely on artificial intelligence and machine learning to perform tasks that are typically done by humans. Your business can use chatbots to help find quality sales leads, improve customer service and engage customers at different points in the sales journey.

Are chatbots effective? ›

Used as a targeted tool, chatbots can increase engagement up to 90% and sales by 67%. In 2020, 57% of businesses said conversational bots deliver substantial ROI for minimal effort.

Which software is used in chatbot? ›

Best Chatbot Software Comparison Table
SolutionBest forFree Plan
SendinblueSmall businesses, start-ups, SaaSYes
ChatraSmall businesses, ecommerceYes
HubSpotSales teamsYes
DriftB2B companiesYes
8 more rows
19 Aug 2022

What is the difference between chatbot and AI? ›

Conversational AI is all about the tools and programming that allow a computer to mimic and carry out conversational experiences with people. A chatbot is a program that can (but doesn't always) use conversational AI. It's the program that communicates with people.

What language is used for chatbot? ›

While making chatbots, Python makes use of a combination of Machine Learning algorithms in order to generate multiple types of responses. This feature enables developers to construct chatbots using Python that can communicate with humans and provide relevant and appropriate responses.

How do chatbots learn and improve? ›

Chatbots can learn automatically by analyzing past data and making assumptions on what is right. The other way chatbots learn is by having a human editing the system. In most cases, both are required. Even though a chatbot has artificial intelligence, a human still needs to audit the responses to make adjustments.

Are all chatbots based on AI? ›

Not all chatbots are based on AI. The so-called rule-based chatbots are often used for simple applications, standardised questions and uncomplicated issues. By linking commands, rules and keywords, the appropriate answers can be provided for predefined questions.

How do you create a chatbot using any AI based app or software? ›

How to create a chatbot in 3 easy steps?
  1. Enter your bot name to get started. Select the type of bot that meets your business needs.
  2. Customize the chatbot the way you want. Make a chatbot in a few minutes without any coding.
  3. Add Chatbot to your website or mobile app. Respond automatically to customers in real-time.
21 Jun 2022

How is chatbot developed? ›

The main technology that lies behind chatbots is NLP and Machine Learning. When a question is presented to a chatbot, a series or complex algorithms process the received input, understand what the user is asking, and based on that, determines the answer suitable to the question.

What companies use chatbot? ›

A growing number of businesses are using chatbots in lots of exciting ways - in fact, according to Facebook, there are now over 300,000 active bots on Messenger.
...
Here are 9 examples of brands which are using bots to great effect.
  • Lyft. ...
  • Fandango. ...
  • Spotify. ...
  • Whole Foods. ...
  • Sephora. ...
  • Mastercard. ...
  • Staples. ...
  • The Wall Street Journal.
23 May 2018

What are the type of AI? ›

These three types are: Artificial Narrow Intelligence. Artificial General Intelligence. Artificial Super Intelligence.

What is AI questions and answers? ›

4) How Artificial intelligence, Machine Learning, and Deep Learning differ from each other?
Artificial IntelligenceMachine Learning
It is a technology that is used to create intelligent machines that can mimic human behavior.It is a subset of AI that learns from past data and experiences.
4 more rows

What is artificial intelligence best answer? ›

Artificial Intelligence is a technique that enables machines to mimic human behavior. Whereas, Machine Learning is a subset of Artificial Intelligence. It is the science of getting computers to act by feeding them data and letting them learn a few tricks on their own, without being explicitly programmed to do so.

What exactly AI means? ›

artificial intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.

How are chatbots used in customer service? ›

AI chatbots use your existing resources, such as FAQs or knowledge base articles, to help answer and resolve your customers' questions. They can recognize and answer multiple forms of the same question and can be trained to give instant responses using your preferred voice and tone.

How do you make a good chatbot? ›

  1. Use a chatbot-making platform. ...
  2. Define your goals and expectations. ...
  3. Give your chatbot a unique name. ...
  4. Approach your customers with your bot. ...
  5. Create a natural conversation flow. ...
  6. Start small and simple. ...
  7. Evaluate and optimize your bot regularly. ...
  8. Unveil one feature at a time.
26 Apr 2017

How can you tell if someone is a bot? ›

The most common way to tell if an account is fake is to check out the profile. The most rudimentary bots lack a photo, a link, or any bio. More sophisticated ones might use a photo stolen from the web, or an automatically generated account name. Using human language is still incredibly hard for machines.

How do you expose a chatbot? ›

How to Break a Chatbot - Eight Ways
  1. 1 - Tell the Chatbot to Reset or Start Over. ...
  2. 2 - Use Filler Language. ...
  3. 3 - Ask Whatever Is on the Display Button. ...
  4. 4 - Answering Outside the Pre-Selected Responses. ...
  5. 5 - Ask for Help or Assistance. ...
  6. 6 - Answer the Question with Non-Traditional Answers. ...
  7. 7 - Say Goodbye. ...
  8. 8 - Ask Odd Questions.

How do you detect a bot? ›

Some basic ways to detect bot traffic are:
  1. If you see any irregular spikes in traffic, take a closer look at it.
  2. Check if a channel is contributing to most new sessions and users.
  3. Multiple bot hits can slow down your server performance.
  4. An increase in activity on your site from a remote location could be from bots.

What are the characteristics of chatbots? ›

Seven characteristics of a great chatbot
  • Conversational maturity. ...
  • Omni-capable. ...
  • Integrates with CRM. ...
  • Emotionally intelligent. ...
  • Free to explore. ...
  • Autonomous reasoning. ...
  • Pre-trained.
15 Jan 2020

What is rule-based chatbot? ›

A rule-based chatbot uses a tree-like flow instead of AI to help guests with their queries. This means that the chatbot will guide the guest with follow-up questions to eventually get to the correct resolution. The structures and answers are all pre-defined so that you are in control of the conversation.

What is strong AI called? ›

Strong artificial intelligence (AI), also known as artificial general intelligence (AGI) or general AI, is a theoretical form of AI used to describe a certain mindset of AI development.

What are the limitations of chatbots? ›

Each of them is strictly connected with a specific limitation of this technology or its bad implementation.
  • Unclear scope of the chatbot and/or too broad purposes of its utilization. ...
  • Setting unrealistic expectations is often the reason why chatbots fail. ...
  • Lack of customer perspective in building the chatbot.
12 Oct 2021

What is the difference between chatbot and virtual assistant? ›

The main difference between a chatbot and a virtual assistant is design and purpose. While virtual assistants are made to handle a variety of requests, chatbots are typically more specific with their offerings. Both increase the delivery of personal assistance.

What is the architecture of chatbot? ›

Most chatbot architectures consist of four pillars, these are typically intents, entities, the dialog flow (State Machine), and scripts. The dialog contains the blocks or states a user navigates between. Each dialog is associated with one or more intents and or entities.

What is a chatbot describe the process of how do you build a chatbot? ›

A chatbot is a dedicated software developed to communicate with humans in a natural way. Most chatbots integrate with different messaging applications to develop a link with the end-users. Though, some chatbots also function as standalone apps. Most businesses build a chatbot for managing customers and online visitors.

What is the main purpose of chatbot? ›

Chatbots allow businesses to connect with customers in a personal way without the expense of human representatives. For example, many of the questions or issues customers have are common and easily answered. That's why companies create FAQs and troubleshooting guides.

What is the main use of chatbots? ›

A chatbot system uses conversational artificial intelligence (AI) technology to simulate a discussion (or a chat) with a user in natural language via messaging applications, websites, mobile apps or the telephone.

What are the objectives of chatbot? ›

Chatbots are designed to give people an automated way to communicate with your company. They may answer basic questions, make product recommendations, and provide customer support.

Which is the best chatbot? ›

7 Best Chatbots (September 2022)
  • The Best Chatbots of 2022.
  • HubSpot Chatbot Builder.
  • Intercom.
  • Drift.
  • Salesforce Einstein.
  • WP-Chatbot.
  • LivePerson.
  • Genesys DX.
15 Aug 2022

What data does chatbot use? ›

To work out those answers, it will use data from previous conversations, emails, telephone chat transcripts and documents etc. This is the training data. Chatbots are only as good as the training data they are given. You can't just launch a chatbot with no data and expect customers to start using it.

Which language is best for chatbot? ›

Here are the 10 most popular programming languages that you should know of while building chatbots.
  • Python. Python is the main coding language for around 80% of developers. ...
  • Java. Java is one of the most powerful programming languages that is currently used in more than 3 billion devices. ...
  • JavaScript. ...
  • Kotlin. ...
  • R. ...
  • PHP. ...
  • Go. ...
  • C.
19 Feb 2022

What is the problem statement of chatbot? ›

Problem statement: Artificial intelligence chatbot is a technology that makes interactions between man and machines using natural language possible. From literature, we found out that in general, chatbot are functions like a typical search engine.

What are the software and hardware requirements for creating a chatbot? ›

IQ Bot hardware and software requirements
  • 32 GB RAM.
  • 8 Octa Core Processor.
  • 500 GB hard disk space 1
  • Ensure C: drive has 100 GB plus free hard disk space.
26 Nov 2021

What companies use chatbot? ›

A growing number of businesses are using chatbots in lots of exciting ways - in fact, according to Facebook, there are now over 300,000 active bots on Messenger.
...
Here are 9 examples of brands which are using bots to great effect.
  • Lyft. ...
  • Fandango. ...
  • Spotify. ...
  • Whole Foods. ...
  • Sephora. ...
  • Mastercard. ...
  • Staples. ...
  • The Wall Street Journal.
23 May 2018

What is chatbot development? ›

A chatbot developer is a person who develops applications that automate communication and customer services. As a chatbot developer, you create software applications that use artificial intelligence and machine learning to communicate with humans (customers) via text or audio.

Videos

1. Conversational Chatbot Use Cases for Retail
(Miracle Software Systems, Inc.)
2. What are some strategic use cases for Conversational #AI?
(Ronald Van Loon)
3. Zero Code Omnichannel Chatbot in 30 Minutes with Amazon Connect - AWS Online Tech Talks
(AWS Online Tech Talks)
4. CCMA Webinar: Call Deflection Customer Case Study
(ServisBOT)
5. Travel Trends 2020: What to bot? with subtitles
(Travelport)
6. Amazon Connect Chat Enhanced CCP [Demo]
(Perficient, Inc.)

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