ChatGPT shatters pre-existing imaginations the public has about chatbots. It also prompts companies to seek how to make an AI chatbot of their own. Unlike its predecessors, ChatGPT provides near-human-like intelligence capable of doing more than answering simple questions. It also raises expectations of AI chatbots in general, particularly the ability to understand and respond coherently to different language styles and nuances.
Buoyed by optimism, the global chatbot market value will likely hit $1.25T by 2025, an immense magnitude compared to $190.8 billion in 2016. Organizations are experimenting with generative AI technologies, which power the likes of ChatGPT, in various business use cases.
As the AI expert at Uptech, I’ve overseen various apps embracing advanced AI capabilities to provide better and personalized user experiences. Our team has also built AI solutions with deep learning models, such as Dyvo.ai for business, to help business users and consumers benefit from emerging AI technologies.
In this article, I’ll share the benefits of chatbots and how to create your own Generative AI chatbot from scratch.
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What is AI Chatbot?
An AI chatbot is software capable of understanding, analyzing, and responding to human speech in a broad context. It uses machine learning, natural language processing (NLP), and AI algorithms to interact with human users. AI chatbots train with immense datasets and retain information from conversations for future learning.
AI chatbots, such as ChatGPT, are powerful software programs that continue to improve when they are in use. They allow businesses to create a personalized experience or conversation for each user. Rather than prompting users to choose pre-defined options, advanced AI-powered chatbots can answer questions usually asked in normal conversations. This makes AI chatbots useful for many purposes, including:
- Supporting internal business workflows, such as employee onboarding and knowledge-sharing.
- Providing personalized and 24/7 customer support.
- Offering recommendations tailored for specific users' preferences and past interactions.
AI chatbot market overview
Innovations in AI chatbot technologies bring new opportunities to businesses and consumers alike. Large enterprises like IBM, Google, AWS, and Microsoft are leading the charge in how organizations adapt and integrate conversational AI capabilities. They dominated 51% of the chatbot market share in 2022.
The e-commerce sector is a primary market driver for AI chatbot usage and will benefit from the engagement and personalized shopping experience the technology brings. Meanwhile, Precedence Research predicted that AI chatbots would boost growth in the healthcare sector by enabling privacy protection for patients seeking online consultations.
A study predicted the global market size will expand at 23.3% CAGR from 2023 to 2030. The promising growth is fueled by the chatbot’s ability to reduce operating costs and automate business processes. In 2022, standalone AI chatbot applications, such as Google Assistant, Amazon Alexa, and Apple Siri, took 57.64% of the market share.
Other interesting trends in the AI chatbot market include the following:
- 31.2% of chatbot applications revolve around customer services in 2022.
- 30.34% of chatbot solutions were deployed in the retail & ecommerce segment in 2022.
- North America was the largest market (30.72%) in the same year.
Popular real-life usage of AI chatbot
Chatbots are not new software technologies, but recent AI advancements have changed how they can be deployed in various industries. Let’s look at several examples.
Healthcare
AI chatbots bring efficiency and healthcare into patient management. Instead of relying on manual administrative staff, patients use chatbots to schedule appointments, receive diagnosis reports, get prescription lists, and seek other healthcare information. AI chatbots ensure patient anonymity while gathering feedback to provide a better care experience, which benefits mental health patients. Also, the recent pandemic has spurred AI chatbot usage in scheduling vaccination and limiting physical interactions at healthcare premises.
Retail
In the retail sector, AI chatbots prove helpful in providing customers with engaging and personalized shopping experiences. Retailers integrate chatbots in e-commerce stores to recommend products based on search phrases or product keywords. An AI chatbot remembers the customer’s previous purchases, which it uses to suggest relevant products. Then, the chatbot guides the customers through paying for the purchase in simple steps.
Finance
Financial institutions use AI chatbots to elevate customer experience, strengthen security and automate banking processes. For example, banks use AI chatbots to recommend insurance, investment, or other financial products based on customers’ credit profiles and transaction histories. Moreover, chatbots help customers receive the required information and financial services without delays. They can also detect fraudulent behavior by analyzing the user’s conversation patterns.
Media and Entertainment
Content providers use AI chatbots to streamline content delivery to their audience for better engagement. By integrating chatbots with users' databases, media companies can suggest content that might interest the users. A chatbot also allows users to search for content with text messages and receive personalized alerts for specific movies or events.
Travel and Tourism
Travel agents benefit from the versatility that AI chatbots offer in different ways. For example, they use a chatbot to keep track of bookings and upsell personalized packages to specific customers. Meanwhile, customers can use a chatbot to create a travel plan based on their destination, budget, and other preferences.
E-commerce
AI chatbots allow e-commerce stores to maintain an active and engaging presence across different channels. Customers can interact with these chatbots 24/7 to seek product information, make purchases and track product deliveries. Meanwhile, store owners leverage AI’s capability to process customer data, display personalized ads and follow up on abandoned carts to maximize conversion.
How an AI chatbot benefits your business
Companies face cost and time pressure to compete in different markets. Industry leaders like Starbucks, British Airways, and eBay continue to use chatbots to support their operations and improve process efficiency. Meanwhile, 57% of business executives reported significant financial returns with chatbots compared to the minimal implementation effort.
But what about your business? How does having your own AI chatbot benefit your team, customers, and profitability?
Instant 24/7 response
AI chatbots allow you to provide prompt customer support at all times without scaling your team. Customers can ask questions, get help and resolve issues quickly without waiting for human personnel. This improves brand perception and encourages customers to return to make more purchases.
Personalized engagement
Customers expect their wants and need to be listened to instead of being pitched a generic product or solution. An AI chatbot analyzes the customer’s past purchases, preferences, and interactions before providing relevant recommendations. It brings a personalized touch least expected from a digital screen.
Simplified process
Some users may need help navigating, searching, or shopping in a digital store. An intelligent chatbot helps to ease the user’s mind and take them through a series of easy steps. This way, you increase customer retention, satisfaction, and loyalty.
Multilingual response
Building your own AI chatbot helps you to expand your business to different regions while maintaining a consistent user experience. Instead of hiring large support teams in different countries, you train the AI bot in languages native to your customers. For example, you can train a chatbot to converse in English, Spanish, French, German, and dozens of other languages.
Automation of routine inquiries
Customers habitually turn to chatbots to ask fundamental questions. Implementing AI chatbots free your support team from replying to common questions. Instead, they can devote their attention to more complicated issues that need personal attention.
Cost-saving and time-saving
Hiring and scaling customer service personnel adds up to considerable business costs. Adopting an AI chatbot not only frees up financial resources but also improves the time spent responding to all customer queries manually. For a better picture, Jupiter Research predicted that the retail, healthcare, and banking sectors would save up to $11 billion in 2023 with chatbots.
Improved interactions and conversions
With an always-available chatbot, your customers no longer have to wait to be attended to. Instead, the chatbot provides prompt replies, accurate answers, and a human-like response, resulting in happier customers. A chatbot also serves as a funnel that connects to your email list or CRM software. In simpler words, an AI chatbot helps you build long-lasting relationships with visitors and turn them into leads.
Customer data collection
In the digital era, businesses rely on big data to strategize their next moves. AI chatbots are capable information gatherers, carefully filtering and sorting helpful information from each conversation. Your business can mine these data on the backend for actionable insights.
Increased session duration
Poor engagement is often blamed for customers leaving a website. AI chatbots can retain customers’ interest by actively engaging them. For example, you can train an AI chatbot to greet new visitors or intervene if the user is leaving your website by offering promotions or free gifts.
Improved customer experience
AI chatbot helps you to provide a better customer experience in various areas. Be it maintaining an omnipresence on different channels, personalizing customer journeys, or suggesting useful products; chatbots make interaction with your business a pleasant experience.
Anonymity
AI chatbot provides privacy for users hesitant to chat with human personnel. This is relevant in medical use cases, where patients share sensitive information when seeking treatment online. They perceive chatbots as neutral and non-judgemental and are likelier to open up about their problems.
Which Tech Stack Do You Need to Build an AI Chatbot?
You can develop your chatbot with these tech stacks.
Natural language processor
A natural language processor, or NLP system, allows the chatbot to understand and construct sentences like a human does. It provides linguistic capabilities, such as tokenization, part-of-speech tagging, and lemmatization, that separate ChatGPT-like chatbots from those limited to simple selections. Instead of building your own NLP systems, you can use those developed by Amazon Lex, Google DialogFlow, IBM Watson Assistant, and Microsoft Bot Framework. These NLP systems let you create, configure and adapt a chatbot to your business needs without much programming.
Cloud infrastructure
Cloud platforms allow you to deploy, manage and scale your NLP engine, machine learning workload, and chatbot application. While chatbots free you from over-relying on a human support team, they require sufficient computing resources to scale as your business grows. Cloud platforms like AWS, Microsoft Azure, Google Cloud Resources, and IBM Cloud abstract the complex server provisioning process. And they let you scale computing power to your AI chatbots as necessary.
AI/ML software
Once you’ve identified an NLP system and cloud platform, you may need to build software to bring the technologies to users. Often, the software incorporates artificial intelligence and machine learning (AI/ML) capabilities. We use several libraries and resources to create the AI/ML software.
- PyTorch is an open-source machine learning library that allows developers to build NLP applications.
- Tensorflow provides open-source tools for training deep learning models.
- Scikit-learn offers data analysis resources for Python developers to build machine learning algorithms.
- Pre-trained large language models, which you can fine-tune for specific use cases to save cost and time.
- Other machine learning libraries, such as Langchain and LLamaIndex, provide a framework for your chatbot application.
- Vector stores like PineCone.io allow the AI model to store long-term memories as vector embeddings.
6 Steps to Build Your Own AI Chatbot
Now, the real work begins to create your AI chatbot, and here’s what goes on behind the scene at Uptech.
Step 1: Define your use case
An AI chatbot serves various purposes. Are you building a chatbot to augment your customer support team? Do you intend to use conversational AI to drive more sales to your ecommerce stores? Asking such questions offer clarity and direction in your chatbot development strategy.
Sometimes, businesses need an AI chatbot that provides more than a simple FAQ. For example, you want to use a chatbot to drive sales by learning what customers want and suggesting relevant products. In such cases, you’ll need additional efforts to integrate various technologies together.
Step 2: Choose an appropriate tech stack
If your goal is limited to simple questions and answers, customizing a commercial chatbot from AWS, IBM, or Microsoft is more than enough. These chatbots are relatively easy to set up, and you can deploy them on various channels, including websites, social media, or as standalone apps. Alternatively, you can develop with the low-level machine learning libraries if you need capabilities not provided by standard chatbot engines.
Step 3: Design the chatbot conversation
Then, design the conversation flow for the chatbot. If you’re building a simple chatbot, configure the decision tree with actions and messages that users interact with. However, you’ll need to train the chatbot to understand user intent to enable the bot to take a more proactive role.
For example, a rule-based chatbot can’t respond to what it was not configured to do, but a machine learning-powered chatbot can. To build a chatbot capable of crafting human-like responses, you’ll need to select a base model and develop prompts to produce the desired response. The model then learns from the expected results and retains the learnings for subsequent usage.
Step 4: Build a knowledgebase for the chatbot
Skip this if you’re developing a simple, rule-based chatbot. Otherwise, integrate your AI chatbot with a knowledge base to support continuous refinement to the context it was designed for. A knowledgebase stores FAQs, chat histories, and other information that helps the chatbot better understand the user’s queries. In other words, it makes the chatbot a more thoughtful support agent.
Step 5: Integrate the chatbot with the app
Next, integrate and test the chatbot’s functionality with the product it was designed for. This involves designing a good UI/UX flow to assimilate the chatbot into a new or existing app seamlessly. It’s also important to streamline data flow, security, and monitoring on both software backends.
Step 6: Refine the chatbot
Test the chatbot with a selected group of users. Gather feedback and fine-tune the chatbot or the underlying deep-learning language model. Ensure that the chatbot responds as expected and that it’s possible to escalate a conversation to a human agent. Once satisfied, launch the AI chatbot to the public.
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Useful tips on building an AI chatbot
AI chatbots, particularly those harnessing the power of large language models, take a lot of work to build. I share several tips that help you avoid common hurdles.
- Avoid developing a generic chatbot like ChatGPT. They are prohibitively costly to build and don’t perform well in a context-specific to your business. Instead, fine-tune pre-trained models to save time and money.
- AI chatbots rely on high-quality data to provide accurate responses to users. Invest in efforts to design the chatbot conversation flow, set up a knowledgebase, and train the language model with quality datasets.
- Your chatbot may perform differently than expected during the initial release. Spend time fine-tuning the model as you gather more conversation data to reduce biases and inappropriate responses.
How Uptech can help
Uptech is an international app development provider servicing startups and companies worldwide. We help businesses embrace and adopt emerging technologies, including chatbots and generative AI. Our team comprises app developers, software experts, data analysts, and machine learning engineers skilled in building AI-powered apps.
One of our recent works involves incorporating an AI assistant for Plai. Plai is a digital HR solution that helps managers conduct employee performance reviews. The new AI OKR consultant allows managers to receive feedback and summaries based on the collected appraisal data. This allows managers to focus on charting the employee’s growth rather than being burdened by tedious analysis.
After years of delivering purposeful apps, we know great products start from understanding your users. Even if you’re building an AI chatbot, you can’t overlook the real problem your business is trying to solve. We work closely with our clients, ensuring the deliverables fit the target market. Along the way, we bagged several awards and recognitions, including Clutch’s Top 100 App Development Companies.
When you work with us, you can expect:
- A team of multidisciplinary software professionals who align tech requirements with your business goals.
- Open communication channels to ensure you’re informed of progress and able to provide prompt feedback.
- Cost-friendly chatbot development from one of the most preferred outsourcing destinations.
- The same quality and professionalism that has garnered good reviews from our clients worldwide.
- An AI chatbot of your own that engages customers just like your human support team does.
How much does it cost to build your own AI chatbot?
The amount you need to spend to build an AI chatbot varies. The development effort might differ depending on the use case, complexity, integrations, and tech requirements. Also, data security, hosting infrastructure, storage, and support affect AI chatbot development fees. You also can’t discount the fact that, AI developers from different countries might charge varying rates.
That said, building an AI chatbot within $20k and getting the PoC delivered in 3 months is possible. It’s best to consult an AI development team with specific requirements for a more accurate estimate.
Summary
Generative AI is changing how chatbots behave and increasing their value to businesses. Both customers and companies will benefit from the presence of AI chatbots at various interaction points. I’ve shared key technologies and steps our team uses to develop and integrate AI chatbots with business applications. And I hope you have a better idea to build your chatbots.
Otherwise, talk to our team, and let us create an AI chatbot with proven steps for you.