In this blog, I thought of introducing and talking about the chatbot ecosystem that has been forming slowly. So, what exactly are we going to talk about? Let’s go from the basics.
Over the years, chatbots have come to the limelight as Artificial intelligence(AI) market has thrived. Looking back, we find that the customer service market was disrupted with the introduction of social media. Customers could now reach out to their favourite brand at any time without going to the store.
The introduction of social media meant having a presence on as many channels as possible for organisations. At this time, chatbots entered the game, to help organisations maintain a meaningful presence over many channels effectively.
Organisations felt compelled to take advantage of this new and exciting technology. Chatbots came with great new features, always available(24x7x365), intelligent, self-learning and improving constantly with every user interaction.
They handled repetitive and redundant queries of users. They are also sensible enough to transfer customer calls to live agents when needed. Bots increase customer satisfaction and reduce customer service costs. Looking at the potential value that organisations stand to gain by using chatbots, it comes as no surprise that an ecosystem is developing around chatbots.
The Chatbot Ecosystem
What is an ecosystem?
In simple words, an ecosystem is a complex network or an interconnected system. Coming into the context of businesses, an ecosystem consists of interlinked companies that dynamically interact with each other through competition and cooperation to grow sales and survive.
In a typical sense, an ecosystem includes suppliers, distributors, consumers, government, process, product, and competitors.
Now that we understand the basics of both chatbot and ecosystems, we are sure you’d follow when we say- companies that build chatbots are at the center of the chatbot ecosystem. Moving ahead, there are two main types of companies that you can contact when you need a chatbot for your organisation.
- End-to-end solution providers.
- Self-service solution providers.
Let’s explore each of these categories in a little more detail.
End-to-end solution providers
The function of the chatbot will mostly depend on the size of the organisation. While smaller organisations employ chatbots to do repetitive and simpler tasks, large companies tend to need a relatively complex chatbot solution. As they are reluctant to invest engineering resources and management time in developing a chatbot solution in-house, end-to-end solution providers step in.
When an enterprise works 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. They also need to keep the customer base satisfied by maintaining the chatbot and dealing with errors and gaps as they come up.
The chatbot building companies in turn leverage the latest developments in the fields of machine learning(ML), deep learning(DL) and natural language processing(NLP) in the creation of these chatbots.
These chatbots are now capable of handling a wide array of tasks in many diverse fields. However, they still do not possess the ability for human-like conversations, they can handle routine tasks and attend customer queries without facing many roadblocks.
Self-service solution providers
When it comes to smaller organisations, their intentions behind employing a chatbot are pretty basic. They are also not the organisations that set aside a huge budget for chatbot technology. In other words, their needs are simpler and the budget is smaller to employ a chatbot. Hence, 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.
Sometimes, even large organisations 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 analysing are also part of this ecosystem. You need to be able to analyse the data collected by your chatbot by using chatbot analytics. You can find our blog on chatbot analytics here.
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 platforms 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. You need to be clear as to what you want to achieve using your bot, or what kind of service you want to enter into the ecosystem. Chatbots are starting to take up better and complex automation tasks with the passing of time.
Looking for a platform where you can build your own chatbot and have it running within minutes? Come check out our Engati chatbot platform today.
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