This blog will introduce the slow growing formation of the chatbot ecosystem.
Over the years, the chatbot market has come to life as the Artificial intelligence (AI) market has thrived. Looking back, it's noticeable that the customer service market was disrupted with the introduction of social media. Customers can now reach out to their favorite brand digitally at any time without going to the store.
The introduction of social media meant having a presence on as many channels as possible for organizations. At this time, chatbots entered the market to help organizations maintain a meaningful presence over many channels effectively.
Businesses wanted to take advantage of this new and exciting technology. AI chatbots came with great new features, 24/7 availability, intelligent, , self-learning, and improving constantly with every user interaction were able to build a conversational ai ecosystem
Chatbots handled the repetitive and redundant queries of users. They were trained to transfer customer calls to live agents when needed. A successful chatbot will enhance the customer experience, increase customer satisfaction and reduce customer service costs. Chatbots provide a potential value to organizations by using conversational AI, it comes as no surprise that an ecosystem is developing around chatbots.
What is an ecosystem?
In simple words, an ecosystem is a complex network or an interconnected system. In the context of businesses, an ecosystem consists of interlinked companies that dynamically interact with each other through competition and cooperation for engagement and sales growth.
The chatbot ecosystem includes suppliers, distributors, consumers, government, process, product, competitors and is an end to end bot platform.
What are the main components of chatbot ecosystem?
Now that we understand the basics of both chatbots and ecosystems, we are sure you’d follow when we say- companies that build chatbots are at the center of the chatbot ecosystem. Furthermore there are two main types of companies that you can contact when you need a chatbot solution provider for your organization.
Let’s explore each of these categories in a little more detail.
The function of the chatbot platform depends on the size of the organization. While smaller organizations employ chatbots to do repetitive and simpler tasks, large companies tend to need a relatively complex chatbot solution. As they are reluctant to invest in engineering resources to develop a chatbot ecosystem solution, conversational ai ecosystem, end-to-end chatbot solutions.
Enterprise working with an end-to-end solution provider, certain things are common. They work with the client team to understand requirements, process customer data and use it to train chatbots. Also need to keep the customer base satisfied by constantly training the chatbot and dealing with errors, gaps as they come up.
The chatbot building companies, in return, leverage the latest developments in the fields of machine learning (ML), deep learning (DL), and natural language processing (NLP) in creating the chatbots. These conversational chatbots are now capable of handling a wide array of tasks in several fields. However, they still do not possess the ability for human-like conversations. They can handle routine tasks and attend to customer queries very smoothly.
On the other hand smaller organizations have very basic and minimal reasons for chatbot adaptation and deployment. No heavy budgets and very simple use are the key factors kept in mind by smaller organizations while using chatbots. Therefore these companies generally choose to go with a self-service solution provider. Their technical personnel can build a chatbot in a matter of days. They make use of the existing APIs or use self-service tools built into the chatbot.
Even Though large organizations build chatbots using the self-service solution on top of an existing framework to save time.
Building the chatbot is only one aspect of it. The means of testing and analyzing are also part of this ecosystem. You need to be able to analyze the data collected by your chatbot by using chatbot analytics.
Semi-automated and automated testing framework knowledge is necessary for chatbot testing.
Once you have built your chatbot, you need to open it to your users on different platforms. There are many channels that will allow you to run a chatbot. It is up to you to figure out where the best engagement can be achieved.
The ecosystem of chatbots is fairly new and still evolving with technological advances. Clarification about what one wants to achieve using a chatbot, or what kind of services are provided by the chatbot ecosystem. Chatbots are evolving and starting to take up more complex automation tasks with the passing of time.
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