Conversational AI chatbot integration: 5 use cases and examples

Automate support, personalize engagement and track delivery with five conversational AI use cases for system integrators and businesses across industries.

Senior Content Marketing Specialist

Razan Saleh

Senior Content Marketing Specialist

From chatbots to virtual assistants, conversational AI is rapidly changing how businesses interact with customers. This technology allows companies to communicate with customers through conversational chatbots, providing instant responses, support, and personalized experiences.

These digital assistants are also used for various other use cases across many channels, devices, and platforms. In fact, you’re probably interacting with them more often than you think.

So, how can businesses integrate conversational AI with their platforms and maximize its potential to the fullest? In this blog, we’ll walk you through five conversational AI use cases you can implement with an AI chatbot and see why it’s becoming a game-changer for many industries.

Chatbot vs conversational AI

Before we elaborate on the specific use cases of conversational AI, let’s get one thing out of the way – a conventional chatbot is not the same as conversational AI.

Chatbots are a type of computer program created to provide information and support in a more human-like way. Simple chatbots use predefined rules and conversational flows, while more sophisticated chatbots use natural language processing (NLP) and AI to automatically recognize what the person needs help with and respond accordingly.

Conversational AI is wider term that refers to the technology that enables computers to communicate with humans using the text and speech patterns that are naturally familiar to people. Conversational AI systems use a combination of machine learning algorithms, deep learning models, and NLP techniques to understand intent, and then dialog management strategies to respond in a conversational style.

Many people use “conversational AI” and “chatbots” interchangeably, as conversational AI technology is used to create sophisticated AI-powered chatbots with advanced capabilities. However, conversational AI has much wider applications and is used in everything from autonomous transportation, automated healthcare assistants, and in the gaming industry to create ever more realistic and immersive virtual worlds.

Let’s take a closer look at the entire conversational AI development journey.

What does a conversational AI development journey look like?

In general, the process of developing an AI chatbot can be broken down into five stages:

Discovery stage: Create a detailed vision of the project including: Defining main business goals and priorities and developing an outline of the future conversational AI assistant, its feature set, and the platform it will be based on.

Training stage: Like any Machine Learning (ML) based model, conversational AI is data-hungry. So, developing a smart virtual helper capable of replacing call center agents means teaching it everything a call center agent must know. Meanwhile, developers will integrate the AI engine within the company’s systems and configure how the chatbot reacts to relevant triggers in order to deliver a seamless user experience.

Testing stage: In this stage, your team will run extensive tests, including user experience testing, accessibility, and integration testing, evaluating the conversational assistant’s performance, response time, and how it reacts to various expressions.

User-acceptance stage: Test the product during the pre-launch stage by interacting with the AI chatbot and getting feedback from stakeholders. You can run the chatbot through different scenarios to test its capabilities and evaluate how it responds to specific questions and requests.

Post production development and support: After the conversational AI chatbot is deployed, the development team continues to monitor its performance and identify areas for improvement to enhance its capabilities.

Now, let’s dig into some of the main business use cases for conversational AI used across several industries.

Five major conversational AI use cases

1. Retail and eCommerce

Conversational AI is making significant strides in retail and mainly in customer service. Here’s how:

  • Customer service automation: Conversational AI chatbots can handle repetitive customer queries, freeing support agents to handle more complex issues. These queries can range from product availability to store hours, location, and even recommendations. This in turn reduces the need for human intervention and improves agent efficiency.
  • 24/7 customer support: Conversational AI enables uninterrupted, 24/7 customer support in multiple languages. Customers can get their queries answered anytime, anywhere, and over their preferred channels and chat apps. As a result, this improves customer satisfaction and boosts loyalty.  
  • Lead generation: AI chatbots can also be integrated into marketing campaigns to generate leads through click-to-ad links. By engaging with website visitors or social media users, chatbots can collect customer data, answer queries, and provide personalized recommendations. As a result, businesses can efficiently generate new leads and gather valuable data for targeted marketing campaigns.

2. Marketing and advertising

Conversational marketing uses real-time interactions to move customers through every stage of the buying process in the most efficient and engaging way possible.

  • Product recommendations. AI-powered chatbots can analyze customer behavior and preferences and act as personal shoppers that offer personalized product recommendations. This data lets you track customer interactions and purchases to understand their preferences and needs. Based on this analysis, the chatbot can suggest products the customer is likely interested in, increasing the chances of conversion.
  • Personalized engagement: Use an AI chatbot for personalized marketing campaigns by sending product updates and informing loyalty club members about benefits and offers.
  • Maximize Customer lifetime value (CLV): AI solutions provide you with a comprehensive view of every customer, including personal and transactional data. With this data, you can engage with customers using an AI chatbot at key times when they are close to making a repeat purchase or renewing a contract.

3. Healthcare

Use cases for conversational AI are increasingly impacting the healthcare industry by assisting in diagnosis, managing patient care, and analyzing medical data. Let’s explore these cases in more detail.

  • Appointment scheduling: With an AI chatbot, patients can message your clinic asking to book, reschedule, or cancel appointments without the hassle of waiting on hold for long periods. Using an AI chatbot can make the entire experience more personal and give them the impression they are speaking with a human.
  • Insurance claims: A conversational AI chatbot can significantly enhance the insurance claim process by answering simple questions regarding the policy and coverage and navigating personal insurance plans to help patients understand what medical services are available and how to submit a claim.
  • Collect patient feedback: Not everyone has time to give you feedback on their experience with your healthcare center, but answering a few short questions with an AI chatbot does make the entire process easier. It provides you with more data on how to improve your patient experience.

4. Finance and banking

Conversational AI has the potential to become a game-changer in the finance and banking sector, offering various applications and use cases. Let’s review how:

  • Customer service automation. AI chatbots can provide account balance information, assist with account setup, answer simple FAQS, and engage with customers in a natural, conversational manner. As a result, this makes the banking service more accessible and user-friendly.
  • Fraud detection and security. Conversational AI plays a  crucial role in enhancing the security measures of banks and financial institutions. Advanced AI algorithms can analyze user behavior and real-time transaction patterns to detect fraudulent activities. This adds an extra layer of security and enhances the overall user experience.
  • Satisfaction surveys: AI chatbots allow banks and financial institutions to boost their CSAT scores and maximize positive reviews by requesting customer feedback directly after transactions

5. Transportation

The future of transportation and ride-sharing is conversational. Integrating an AI chatbot brings a lot of benefits to the transportation industry. Here’s how:

  • Driver and user registration: Conversational AI can help you engage with customers and enable driver and user registration through Ads that click to chat where customers get a direct link to sign up. Signing up for a service the old-fashioned way was no fun. See how Bolt used a conversational WhatsApp chatbot to optimize their driver sign-up process and increase conversion rates by 40%.
  • Booking a ride: Integrating an AI chatbot with a ride-sharing app can simplify the ride-booking process by easily finding a ride and confirming pick-up location directly from a chat app. Riders and drivers can communicate effortlessly throughout the entire journey. Users can book a ride and track its arrival in real-time with just a few taps on their smartphones.
  • Ride tracking and updates. An AI chatbot can also provide real-time ride tracking information, offering updates on location, estimated arrival time, and live alerts on possible delays.

Examples of Infobip AI integrations

Croatia’s first fully digital insurance provider, LAQO, wanted to improve customer service with 24/7 availability, accessibility, and personalized support. Together with Infobip’s chatbot building platform Answers and Azure OpenAI Service, LAQO was able to launch a generative AI-powered assistant that:

  • reflects LAQOs brand voice and personality
  • offers 24/7 support for FAQs and repetitive queries
  • is available to assist in two languages: Croatian and English

Infobip partnered with Master of Code to create a Generative AI commerce chatbot for BloomsyBox to drive user engagement and personalized experiences on Mother’s day. Bloomsybox was able to launch a generative AI chatbot that:

  • engaged with users and hosted quizzes for a chance to win free bouquets
  • assisted users in generating heartfelt messages and personalized greeting cards
  • used humor and personality to capture the sender’s bond with their moms

The largest regional food company, Podravka partnered with Infobip to create an AI digital assistant, SuperfoodChef-AI by Coolinarika. The AI assistant is conceptualized and designed based on human-centered design principles and nudge architecture. SuperfoodChef-AI can:

  • create an enhanced user experience on the largest regional culinary platform
  • show users the importance of a varied and nutritionally rich diet in a simple, engaging and conversational manner
  • help users with culinary and nutritional advice and recommendations of delicious and healthy recipes

Co-create with Infobip Partnership Program

Integrating Infobip’s conversational AI chatbot enables System Integrators (SIs) to enhance their value proposition and create differentiators for their clients. Through our partner connect program, we will co-create solutions to help you with:

  • Grow your business and reach new customers
  • Create new cross-sell and up-sell opportunities
  • Extend your product capabilities and enhance your portfolios with value-added services
  • Unlock new revenue streams and monetization opportunities through transactional channels and customized API plug-ins.

By partnering with us, SIs can leverage a growing conversational commerce market spend on channels, set to reach $290 billion by 2025.

It’s a win-win situation, SI’s will have a direct impact on the platform, and we, in turn, will empower you to drive revenue and offer scalable solutions by providing you with the required information, support, and training.

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Dec 5th, 2023
8 min read
Senior Content Marketing Specialist

Razan Saleh

Senior Content Marketing Specialist