Benefits of Developing Conversational AI for Customer Services

Сompanies using AI for customer service is a new trend in the modern world.

After the emergence of various chatbot companies that offered numerous generative AI solutions like ChatGPT for each task and purpose, the customer service industry has changed forever.

Frankly, conversational chatbots and various virtual assistants are not a new phenomenon. Yet, it is hard to deny, that they are quite popular and advanced nowadays. Besides, apart from more advanced algorithms of conversational AI solutions, many of them are open-source. So, using AI to improve customer experience is an easy and cheap possibility.

So, how can chatbots improve customer service, and how to develop or integrate conversational AI for customer service?

Conversational AI for Customer Service Explained

Artificial intelligence is a new-era technology, that allows the creation of advanced software, that can simulate cognitive activity and human-like behavior.

To simplify it, Machine learning (ML) and artificial intelligence (AI) are software development approaches, that make it possible to train machines and systems to perform certain tasks and activities. As a result, by combining artificial intelligence and customer experience, businesses can automate numerous processes and improve customer journeys.

Frankly, the potential of modern chatbots seems unlimited. They are incapable of all things at once, yet are also not industry-specific. Therefore, the best way to learn the potential benefits of adopting and integrating AI is to consider particular industries and specific usage purposes. For instance, let’s talk about the benefits of AI in customer service.

Artificial Intelligence and Customer Experience

Customer service is common in any industry. The main goal of customer service is to improve the customer experience of contacting and choosing your products.

Thus, the more advanced, faster, and precise customer support services you provide - the better the result will be. One of the major problems of customer service is scalability: the bigger the company is - the bigger the customer service cost is. Most modern companies still hire employees for customer support and similar tasks. As a result, many companies must hire whole call centers to improve customer experience (CX) and retention.

However, modern AI in CX can significantly cut spending and even improve customer service simultaneously.

One of the best benefits of AI in customer service is the automation capability. To make it simple, you can integrate a ready-made SaaS solution like ChatGPT via APIs, set up the behavior patterns, connect it to your database, and make it respond to users' requests via a convenient user interface.

In other words, such integrations are a relatively easy and cheap solution, which brings numerous advantages to the business, allowing redirecting other resources to more complex or prioritized tasks. Artificial intelligence also shows excellent results in customer experience. Most modern chatbots use the Natural Language Processing model (NLP). They can understand and generate human-like language in various formats (speech, text, etc).

So, modern generative AI for customer service can understand the client's request and find an answer to the question in a user-friendly manner. However, this is only the most basic and vital feature. Yet, it is worth mentioning the rest of the AI features, that make conversational AI for customer service one of the most efficient solutions in this field.

How Chatbots Improve Customer Experience

Let’s discuss the rest benefits of AI in customer service.

Apart from understanding the customer request, modern chatbots and AI solutions offer numerous advanced features, related to customization and process automation.

AI and Customer Service Automation

One of the most obvious and common cases of customer experience in the age of AI is using chatbots for fast response and customer service.

First, it helps free resources by delegating FAQs or other repetitive communication to AI. Hence, your company can relocate various resources and enable HR automatization, including customer support specialists to more complex tasks. In the long term, it helps cut expenses and offer better customer journeys and support.

Another advantage of using chatbots for such tasks - is that they can work 24/7. Therefore, customers will get an instant response at any time of the day. This will undeniably improve customer satisfaction, helping to avoid waiting for a response. Additionally, AI-driven chatbots can process multiple conversations simultaneously.

The AI customer journey can handle routine requests like order placing, parcel tracking, product information clarification, etc. If the customer request is too complex to process or requires human engagement, it can redirect users to customer support specialists.

AI Customer Journey Personalization and Targeting

Another advantage of ​​using AI to improve customer experience is advanced customization and personification of content and customer services.

AI in CX can use algorithms for creating personalized proposals like recommended goods and products, based on user preferences and customer historical data. Unlike humans, artificial intelligence is capable of processing big data in a matter of seconds. Integrating a conversational customer support chatbot with access to customer information gives you an advanced development tool to improve customer experience and personalized users’ journeys.

Data about previous operations within the app or platform, and historical data on prior users' reports or issues improve AI customer journey. The more data you gather - the better the combination of artificial intelligence and customer experience will be.

Many companies use AI for customer service personalization and improvement. Among the most well-known examples are Netflix, Facebook, and Amazon. Almost any modern web platform or application uses data gathering and analysis to create a more individual approach and advertisement for the customer. Nowadays, such functionality is possible without developing AI from scratch - many plugins and extensions propose the same functionality.

Using this feature of conversational customer support AI increases customer loyalty and retention. Moreover, such AI-driven customer journeys can be adopted for improved conversational customer support. Such AI solutions can also be used to indicate issue patterns of different users and find suitable solutions for common problems or requests.

Generative AI for Customer Service Analysis

Finally, chatbot companies offer advanced AI models, which are commonly open-sourced and free of charge.

Apart from generative AI for customer service responses, such software helps to analyze and process big data. In addition to the previously mentioned personalized conversational customer service, many AI-driven solutions can be used for fraud detection, risk assessment, and security testing.

Even conversational AI and simple modern chatbots are capable of machine learning and pattern detection. Altogether, this creates a great variety of use cases even for a single AI module. Pattern detection can also predict user behavior, define potential pitfalls or issues, identify reasons for customer turnover, and notify the company of what should be changed to prevent it.

The same NLP model can be used for customer support services and deep system analysis. In other words, AI integration is not limited to only AI customer experience examples. It can offer countless solutions and improvements for the rest of business aspects.

The best way to learn the benefits of AI in customer service - is to examine particular cases of companies using AI for customer service.

AI Customer Experience Examples

As was mentioned, many modern companies use AI for customer support services.

If a few years ago, the list of companies using AI for customer service was limited to tech giants, who had enough resources to develop and maintain their own AI and conversational chatbots, now - it is possible for even the smallest business company.

One of the most popular and simplest AI solutions, that can be adopted as conversational AI for customer service is ChatGPT. Its open-source nature makes it an ideal candidate for further integration and usage for conversational customer support, or similar tasks.

Apart from numerous examples of simple conversational customer service chatbots, which can be met on almost any eCommerce website, we can name a few exceptional examples of how chatbots improve customer experience.

Amazon Personalize

As one of the market leaders, Amazon was among the first companies to integrate AI in CX and machine learning algorithms.

Amazon Personalize is a software, based on machine learning algorithms. Its main goal is to improve customer experience in the age of AI, using new-era AI technologies.

It helps to set up advertisement algorithms, that enable hyper-personalization for the end user, adjusting advertisements and proposing the most relevant products, relevant to previous users’ browsing history, set preferences, etc.

Amazon Personalize is distributed as a SaaS solution, so any business might consider integrating it for an agreed price. To do so, you have to find app developers for hire, who can set up the AI environment. One of the most important aspects is to give this AI model to your database and set up data sharing between your IT infrastructure and this service.

Additionally, Amazon claims, that as a customer, business owners can customize and adjust AI algorithms to their needs and preferences.

Starbucks Personalized AI

Another example of using AI to improve customer experience is Starbucks.

They designed an AI, capable of analyzing customer behavior patterns. AI proposes personalized discounts on different company products, based on this information. The main idea of such a solution is to boost customer loyalty and increase customer retention.

Conversational AI for Customer Service: Incora Case

In our latest collaboration, we integrated a full-fledged AI module for CRM.

The main idea was to help with HR automation and redirect human resources to more prioritized tasks. To achieve the best results, we consulted our clients on potential IT infrastructure rearrangements, and changes in business logic.

As a result, customer support specialists are engaged in more complex and specific cases. At the same time, routine communications are performed by conversational customer service. The AI module is based on an advanced version of ChatGPT with certain code-based adjustments and arrangements within the custom-made CRM for construction company.

This conversation AI has all the answers to frequently asked questions, and can generally consult users on potential plans and issues. If customers have a desire to proceed further, than just a consultation - the chatbot redirects them to the company representatives.

This case showed us a few extra benefits of AI in customer service. In particular, such simple, yet efficient integration helped to improve customer satisfaction, and noticeably cut expenses on customer support services.

Artificial Intelligence for Customer Services with Incora

Frankly, this is not our only white-label custom software development project, related to artificial intelligence and customer experience.

If you want to see more examples of how chatbots improve customer experience - check our case studies.

Judging from our experience, if you want an efficient tool to improve your customer services, or are looking for instruments for process automation, you don’t have to develop an AI from scratch.

Nevertheless, it is important to find a trustworthy IT outsourcing vendor and hire a dedicated software development team, familiar with such technologies. Thus, you will get a chance to cut the expenses, still getting astonishing results.

If you haven’t worked with IT outsourcing companies before, here is a checklist, that help you ensure the experience of the potential IT vendor:

• Check B2B platforms like Clutch or GoodFirms. Such platforms constantly monitor and update information about outsourcing companies and teams, gathering client feedback and reviews, performing their evaluations, and giving the most detailed info on market actors.
• Read feedback and check case studies. Most companies, that offer dedicated software development teams for hire, commonly have such information on their websites. This step helps you to understand the experience of developers, the technologies, they use, and the final result of their work.
• Contact the preferred IT outsourcing company. After narrowing down the list of potential software development partners - contact them. Briefly explain your needs and ideas while filling out the contact form. Thus, company representatives will know what to expect and whether they can meet your expectations.
• Set up a meeting. After hearing back from the IT vendor - schedule a meeting. Thus, you can ask the questions you want and hear the offer.
• Discovery phase of the project and rough estimation. After clarifying all the details and writing SRS, the IT company will perform a rough estimation. This is an essential step that helps to learn the approximate time and material requirements for the development. Also, at this stage you can agree on the technologies to use, extra preferences or conditions, etc.
• Sign the agreement. After all the foregoing, you will understand the cooperation terms, required resources, and approximate software project time. If everything is satisfying for you - you can sign the agreements and proceed with other paperwork.