Chatbot use cases: 25 real-life examples

AmTrak, a railroad service in U.S.A and Canada, has used this chatbot use case. Hiver, a service that provides shared-email services to companies, does this job beautifully. In fact, you can ‘bake’ this function right into the chatbot’s chat window with an option clearly labeled ‘get a free refund’. And of course, in the same way, a chatbot can make a refund, it can also process item exchanges as well. For example, PVR Cinemas own one of the largest chains of movie theatres in India. And on their website, you’ll find a chatbot that helps visitors quickly book movie tickets, view offers, and leave feedback.

This level of intelligence is vital in delivering a personalized shopping experience for the consumer. A tornado of technological advances has changed consumers’ expectations, and commerce is now focused on building experiences for the individual, and not the mass market. For consumers, there are a multitude of touch points and influences that generate purchases. Whereas AI based personalisation for eCommerce takes the multi-channel approach. New AI engines, such as Boomtrain, sit on top of the multiple customer touch points to help the business analyse how customers are interacting online. Well, some businesses are now using facial recognition to capture customer dwell times in the physical store.

Personalized Shopping Experiences

As retail became tech-empowered, it also served as a strong example of conversational AI use cases. The use of chatbots and other conversational AI forms act as virtual shopping assistants for people who want to shop from home. Even inside a store, chatbots help the customers in exploring the inventory for their chosen product. Intelligent chatbots help customers find suitable product recommendations according to their preferences and needs. In e-commerce websites, chatbots help in adding products to the cart and checking out with them. Even in offline stores, conversational AI helps customers make payments and checkout without human interactions.

What isn’t so common right now is integrated chatbots on shopping cart pages. This integration could stop shoppers from abandoning their carts at the last minute by answering questions there and then. Recommendation engines are another popular application of AI in eCommerce. They use machine learning algorithms to analyse customer data and provide personalised product recommendations. This helps online retailers increase their sales by suggesting relevant products that customers are more likely to buy.

Marketing Guides

Also known as ‘searchandising’, or ‘search merchandising’, this involves customising and organising search results so that they fit a set of rules or criteria. Getting the right message to the right people at the right time is vital if you’re going to trump your ecommerce competitors. It’s difficult these days not to get into a conversation about Artificial Intelligence, especially if you’re in business, and even more so if you’ve got a digital marketing strategy on the go. Moreover, AI algorithms require continuous monitoring and maintenance, which can add to the overall cost of implementation. Retailers must carefully evaluate the cost-benefit of AI solutions and choose the ones that provide the most significant value for their business.

However, getting a visitor on the company’s website interested in a company’s email series the business/company is providing can be a real challenge because it doesn’t matter how effective the email campaigns are. Unless website visitors are subscribing to them,  email campaigns are of no use. ecommerce chatbot use cases Businesses who are willing to invest money in gaining an audience can do so through giveaways, contests, and quizzes. Contests, quizzes, and giveaways that promise discounts tend to have a high chance of going viral and help businesses gain new loyal customers very effectively and smoothly.

Creating personalised experiences

OpenAI had to program ChatGPT to specify the date when the shared information was last accessed. Prior to this, it wasn’t uncommon for the obtained information to be outdated, since the AI only had access to data up until 2021. Strictly Necessary Cookie should be enabled at all times so that we can save your preferences for cookie settings. In any case, SMEs still have to grapple with barriers to entry when embracing ML technologies. Fortunately, technology consulting companies are on a mission to help startups and enterprises adopt advanced technologies with minimal friction.

Fully open-source LLM variants are being developed, giving broader access and demanding reduced hardware requirements for running. All of which aim to combat the exclusive and closed nature of the technology. Python-based projects, such as LlamaIndex and LangChain, provide similar capabilities extending the reach and capabilities of LLMs even further. Another enhancement would be to replace the Object Store with a database (such as MongoDB) depending on whether the extra features and functionality of a complete NOSQL database would be helpful.

A better solution instead would be to categorize products into specific and limited categories, then gently guide users through the product catalog and ask them what products they wish to see. Businesses can use another effective customer acquisition tool and combine it with their email marketing efforts to develop a more powerful lead generation channel. Any company wishing to simplify its product/service pricing can employ the chatbot use case for this very purpose on their pricing page as well. Chatbots provide a less-annoying, more engaging way of collecting leads. Unlike forms, which simply demand email addresses in exchange for a lead magnet, a chatbot tries to start a thoughtful conversation asking the visitor what they would like to do. Instead, a better option would be to add a chatbot to your website’s homepage.

• Thus often chatbots end up not leaving the ‘experimentation’ stage, as they’re not sufficiently better than what was before – thus failing to ‘retrain’ user habits.
• In recent years, it has become perfectly viable to list products ranges, take one-click orders and offer tracking functionality inside Messenger without ever needing the user to leave the chat window.
• Now, let’s take a closer look at some of the top AI chatbots on the market.
• While chatbots certainly are effective at each individual task they are given, chatbots built this way won’t realize their full potential.

Large-scale manufacturing companies use virtual assistants to schedule despatch of product shipments. Moreover, chatbots help in checking the lead status and fill in the lead details for sales executives. https://www.metadialog.com/ If you’re not already making use of conversational commerce, you should be. Imagine a customer entering a store and browsing products as a sales assistant approaches and asks if they need help.

A Chatbot as an Intelligence Tool

AI chatbots are most successful when they can learn from thousands of service interactions (like those already saved in enterprise CRMs), machine learning algorithms and scripts. OpenAI’s ChatGPT has revolutionised the field of artificial intelligence. It sparked global interest in its diverse applications for both personal and professional use, including customer service.

Brands that have already implemented AI shopping assistants powered by trusted generative AI see satisfaction rates of up to 70%, results that are well above the average for conventional chatbots. Evangelists also predict that chatbots will redefine how businesses sell products and services. One of the most prominent examples of effective AI within retail is the use of chatbots. Among all the communication channels used by brands, chatbots have shown the fastest growth rate. Recent survey findings reveal that 67 per cent of global customers interacted with a chatbot over the last twelve months.

The Pro Carrier Portal chatbot can help you with Where Is My Order (WISMO) queries, check HS codes and look up invoices. Integrating AI solutions with existing eCommerce platforms and systems can also be a challenge. Retailers may need to modify their existing systems and processes to accommodate AI algorithms, which can be time-consuming and costly. Moreover, integrating AI solutions with legacy systems and platforms can be challenging due to compatibility issues. Chatbot suppliers acknowledge this and want to make the tech more accessible, no matter what the budget. Therefore, you can imagine it will evolve to be another Software as a Service (SaaS) sell for vendors.