Machine learning and Artificial Intelligence are the two words those are on the tip of every technophile’s tongue. Over years, Machine learning and Artificial Intelligence have transformed all the aspect of our personal and professional lives.According to a research, it is found that nearly 85% of the global executives have a belief that AI will surely allow their companies to obtain and also sustain a competitive advantage which is going to play big role in enhancing the work productivity in the organization. Whenever it comes to applications of AI technologies, chatbots are the most popular and are also making biggest noise in the market.
According to studies it is found that
- 80% of businesses want chatbots by 2020 — Oracle
- The global chatbot market is set to grow at CAGR of 37.11 during the period of 2017–2021 — Orbis Research
- Chatbots are expected to cut business costs by $8 billion by 2022 — Juniper ResearchWhat
Along with the already popular applications in the B2C space, chatbots are also revolutionizing the B2E and B2B organizational scenarios.
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Chatbots in the enterprises
Whenever it comes to enterprises, chatbots must be readily available and must be accessible across the myriad of the channels along with the integration of the internal business with the Customer Relationship Management (CRM) and the Supply Chain Management (SCM) systems which are on the top priority. Enterprises have plethora of options when coming up with the bot development strategy. A single task bot is not a feasible option for enterprises those need an automated workflow coupled with the integration of internal and the external ecosystems and application of natural language processing.
The Chatbot frameworks also assist the programmers along with the structures which can be used to build the individual chatbots. However, these frameworks are merely just a collection of a set of tools and services. The frameworks can also be used to assemble and also deploy the single task bot which lacks the end to end development and the ongoing managing capabilities.
If the use case is small, frameworks tend to be useful and however for a particular enterprise where the overall requirements and since the scope is much more demanding, it is where the chatbot platform comes into picture. The chatbot architecture has the following requirements those are listed below, which the enterprises must consider for the development of the chatbot platform.
1. Multiple Types of Chatbots Executing Multiple Tasks
This functionality is importunate for the enterprises as it permits them to track and streamline the multiple functions at once. Ideally, the enterprise must have the ability to deploy a chatbot which works on a single task along with creating and deploying a multi-purpose chatbot that communicates with multiple systems and completes a variety of tasks within each of them.
The chatbot development platform must also offer pre-built and ready to deploy bots which address certain use cases (e.g., lead generation, customer support etc.) along with the ability to customize them to suit your business needs so as to handle multiple different workflows and processes pertaining to different customer interactions and your business offerings (e.g., a lead generation bot that also answers customer’s queries and replies with answers in a FAQ, document or website).
2. Multiple Channel Support
Whenever you see for chatbot development platforms, see to that where the bots can be deployed to the website, mobile apps, or the channel of its choice with the user interface that is customized for each channel, be it SMS, e-mail or social media. To add on to that, the bots should have the ability to interact with corporate tools like Slack, Telegram, Skype, etc.
3. Natural Language Processing and Speech Support
4. Deploying Intelligent Chatbots Through the Platform
5. Ability to Bridge With the Platform
6. Building the Chatbot
7. Industry Experience and Domain Knowledge
Identify and engage with the right technology and platform providers that have considerable industry experience and domain knowledge.
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