How Chatbot Development Helps Modern Enterprises Move Forward

At the turn of the millennium, we might have believed that robotic assistants still belonged to the distant future. By now, though, AI-based solutions have permeated nearly all aspects of everyday life. Chatbots and software agents solve a host of problems, providing support with bookings, shopping, job search, or even breastfeeding. In business, they are disrupting all operational domains—from customer service and process optimization to recruitment and inventory management.

Propped up by advanced in AI consulting, chatbots are becoming increasingly sophisticated. These automated communication systems blend AI, machine learning, image and voice recognition technologies to simulate how humans talk, think, and interact. Modern chatbots not only understand people and provide intelligent answers based on amassed data but can also recognize a person’s mood and act on it. In some cases, these bots are nearly impossible to distinguish from a human. In fact, according to Solvvy’s 2021 State of Chatbots Report, 47% of respondents have mistaken a chatbot for a live agent.

While cuts in expenses and improved returns on investment are the main drivers behind chatbot adoption, businesses can take advantage of chatbots in other meaningful ways, especially in the sales and marketing space.

For example, customer services automation with chatbots can bring about increased customer engagement, better conversion, and broadened reach. Deep insights into historical interactions and multi-faceted analysis of customer behavior behind such intelligent assistants allow companies to consistently deliver personalized service, improve customer interactions, and create a positive brand image.

Interestingly, even SMEs can reap those benefits now as chatbots are cheap and easy to deploy. What’s more, they require minimal maintenance and can be easily extended with new features if needed. These characteristics make it possible for smaller companies to compete with industry giants by delivering the same level of personalized customer service.

Robotic process automation, or RPA, is the use of software with AI and machine learning capabilities to automate and facilitate business processes. RPA automates mind-numbing repetitive tasks typically outsourced to offshore companies. This leads to a reduction of expenditures, lower operational risk, and enhanced internal processes. While the technology is separate from chatbots, the two can be used in conjunction, and the lines between them are increasingly blurring.

At the foundation of all chatbots, there’s a conversation. The core characteristic of bot software is the interaction with humans via voice or text. However, chatbots are evolving beyond “dumb” virtual assistants toward much smarter conversational bots that can automate specific business tasks. These bots can be integrated with RPA solutions to become a fully functional service that handles not only the conversational part of the customer service process but can also input and manage data in various IT systems, such as CRM, knowledge bases, or ERP.

A practical example of how chatbots can leverage RPA capabilities comes from Amazon and its bot frameworks, Lex, and Elasticsearch Service. The frameworks allow building a fast search bot that supports employees in identifying and retrieving relevant documentation in an instant.

Imagine an admin worker who needs to get specific information from heaps of digital paperwork quickly. By using the solution, he or she may send a request to a chatbot, by text or voice, e.g., “I need to find Mr. Smith’s address,” and the bot will immediately fetch the documentation containing the required piece of data. That’s a brilliant solution with a range of applications across various industries. 

Does that sound like replacing humans by robots (again)? Not necessarily so. By taking over mundane, repetitive tasks, bot engines can streamline work for the current staff, making it more efficient and saving time (along with frustration). Other benefits of solutions based on chatbots and RPA include better data quality, relocation of resources to higher-value tasks, and enhanced customer experience.

By now, we can all agree that chatbots drive immense values for enterprises of all sizes. But how can a company start with this technology? One way is to build a chatbot solution from scratch, another one is to customize an existing platform.

There are a few DIY chatbot frameworks available, such as Azure Bot Service, Botpress, or Microsoft Bot Framework that can be leveraged to deploy bots for particular use cases. These platforms make it fairly easy for chatbot developer team to build a very basic bot and refine it with the desired features. However, if a company is looking to build a scalable solution allowing full control over the conversational flow, it makes more sense to build a completely new chatbot.

One of the reasons is that DIY chatbot builders are usually quite limited, and by default allow only a small number of features to be developed. Typically, those platforms have a limited scope of dedicated applications, and some of them work better in a given context or an industry than others. For example, Microsoft’s framework is well-suited to build messenger bots, Wit.ai can be used for IoT automation, while IBM Watson can be leveraged to design customer support and contextual conversation bots.

What’s more, getting tied to a particular platform may lead to several issues in the future. First of all, there’s vendor lock-in. What will happen to your bots when the platform goes down? Secondly, many chatbot platforms don’t allow external users to extend core features, which may hinder the development of your chatbot in the future.

The choice whether to create a chatbot from the ground up or use an existing platform depends on many factors. While it may take less time to develop a simple chatbot with a DIY framework, this option comes with challenges. At the same time, developing a fully proprietary chatbot to serve your company’s specific use cases seems to work better in the long term.