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A conversational AI platform is used to build conversational user interfaces, such as chatbots or virtual assistants, for a wide array of use cases.

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Chatbot platforms are one of its subsets dedicated to the textual medium, although modern platforms such as Senseforth’s A.ware have built-in support for voice bots as well. Solutions built using these platforms can be deployed across various channels such as instant messengers, social media sites, SMS, webchats or even WhatsApp They can even be extended for third-party customizations via developer API.

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All you need to know about chatbot platforms

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A chatbot is a software program designed to give users the ability to communicate online without any human intervention. They combine the steps of complex processes to streamline and automate repetitive, mundane tasks via text (or voice) commands. Various customized chatbots are embedded in everyday business workflows to reduce execution time and improve operational efficiencies.

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With the growing sophistication of Artificial Intelligence (AI), self-learning chatbots that can interact with humans more naturally are becoming normal. As enterprises seek to harness the many benefits of this technology, they are faced with the crucial decisions of investments, knowledge gap of teams, changes required in the existing architecture, implementation risks, and likewise. A chatbot platform is a packaged solution to all these stressors!

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Before the advent of platforms, chatbot development was difficult as it required sophisticated toolsets. One needed to create a complicated backend using concepts like data mining, Natural Language Processing (NLP), and Machine Learning (ML). Chatbot platforms solve this problem by impeccably blending AI and user-friendly interfaces to aid development with minimal coding, allowing effortless creation of chatbots. They create a virtual environment to interact with support tools that can develop and deploy chatbots for a real enterprise. Also, they have the in-built infrastructure and standard communication features packaged in a simple programming library. This means that building chatbot does not require researching through communication protocols and establishing frameworks from scratch - teams can directly dive into the business problem and focus their efforts unidirectionally.

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An enterprise may or may not have the capabilities and resources to build a chatbot. But with a chatbot platform, a business can easily integrate its own bot across various channels without facing technical fallbacks. It also allows IT departments to have complete control and access to monitoring bots.

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Which chatbot building platform is made for you?

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How do you zero down on one chatbot platform amongst the plethora of options available in the market? What are the features you should look for? Which chatbot platform is best suited for your specific needs?

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Read on to have a better understanding of the features that different chatbot platforms offer and how you can evaluate them.

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While venturing into the world of chatbots and virtual assistants, the most perplexing phenomenon is the feature list. These features or attributes in the platform essentially define the entire workflow of your end-product: the chatbot. Different chatbot platforms provide different features that might look attractive at first glance but would not be addressing your business needs. Few of the features that are commonly seen in the market are as follows:

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  1. Natural Language Processing - ability to understand natural lingo (slangs, grammatical errors, regionalism, etc.) and respond effectively
    2. \n
  2. Context and Coherence - ability to hold long conversations without losing cohesion
    3. \n
  3. Machine Learning - ability to self-learn and analyze based on recorded logs
    4. \n
  4. Prediction - ability to identify patterns in the user’s messages and recommend similar suggestions
    5. \n
  5. Account Manager - ability to design, test, and deploy comprehensive project coordination
    6. \n
  6. Collaborative Model Training - ability to provide customized training to engineering teams for conversational AI and ML skills
    7. \n
  7. Enterprise-grade - has a reliable infrastructure with industry-specific pre-training
    8. \n
  8. Live Chat - has a Human-in-the-Loop (HITL)/ human takeover feature
    9. \n
  9. Automated Sequences - higher conversations and automated messenger marketing
    10. \n
  10. API of Different Types - enables the communication between existing systems
    11. \n
  11. Intent and Tone Models - the ability to adapt decoded messages in-depth
    12. \n
  12. Role-based Access Control (RBAC) - ability to restrict access to authorized users
    13. \n
  13. Conversational Flows - ability to analyze conversations hopping from one intent to another
    14. \n
  14. Deep, Reinforced Learning - advanced semantic analysis and conversational computing
    15. \n
  15. Trigger Support - ability to send notifications/pop-ups to users for redirection
    16. \n
  16. Encrypted Cloud-based Storage - ability to automatically store attachments for a prompt reference.
    17. \n
  17. Drag-and-drop interface - ability to just build custom user interfaces by simply rearranging the existing design models
    18. \n
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As stated earlier, you need to clearly understand each feature and its impact for the best results. E.g. – a chatbot built just for answering FAQs related to employee onboarding might not need NLP but an intelligent chatbot designated to address customer support on a website will require NLP, trigger support, and deep learning.

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Once you have understood and decoded the features you want in the chatbot platform, the next thing to look for is Key Performance Indices (KPI’s). Since there are several platform providers, selecting the one that will ensure ROI is not an easy decision. It largely depends on the type of analytics the platform supports. Check how easy it is to track the following KPIs in real-time before you zero down on a chatbot platform.

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Before you draw the final call

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The final move before making a purchase involves brushing up the basics. Take a step back and evaluate the nitty-gritty of installing a high-tech system into your traditional legacy framework. There will be ripple effects. There will be a talent gap. There might even not be an immediate profit boost. The best way to tackle these aftereffects is reconsidering your need and comparing risk versus benefits. There are 4 basic things that you might want to look into:

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Learning: The learning competence along with knowledge and infrastructure is the basic attribute of a chatbot. That said, a chatbot platform that requires manual feeding of training data and skills is not a favorable option. The most viable platforms are the ones that can absorb the organizational knowledge corpus from different sources including but not limited to Salesforce, e-commerce website, and internal communication tools like Skype.

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Understanding: A chatbot platform without NLP is an obsolete choice. Without the contextual understanding of the user’s messages, the chatbot would just be scripted or meant/button based. Since technology has come way ahead of that framework, such rule-based chatbots barely make a difference in engagement. Therefore, it is wise to look for the latest NLP capabilities in the chatbot platform.

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Deployment: The best chatbot platforms have a dialogue manager, behavior engine, and other service tools. Apart from all these peripheral interfaces, flexibility and fast integration with the existing system is the primal feature a chatbot platform can have. It provides scalability and agility, and employees can get acquainted with the technology smoothly. The sooner the business gets started with a chatbot, the sooner it can reap the benefits.

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Pricing Model : Platforms use a combination of monthly license fee (subscription), pay-per-call, and pay-performance pricing models. Monthly license fee provides regular support and maintenance – you can build limited or unlimited bots for a flat monthly (or annual) fee, pay-per-call has the flexibility to pay only after the launch of the chatbot (cost is based on usage and number of API calls), whereas pay-per- performance allows savings since the costing will be based on the achieved deliverables only. They all have one perk or another and you must select the one which is best suited for you.

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To summarize

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The last few years have seen major messaging platforms like Facebook Messenger, WhatsApp, Slack, and IM gaining a lot of popularity. Not only do these apps draw in more users, but people are also spending more and more time on them. The clear manifestation of people engaging in textual communication is the high adoption of chatbots by businesses. AI chatbots are becoming effective mediums to reach out to audiences for multiple business processes like marketing, customer service, and employee enablement. Enterprises see chatbot deployment as the ‘next digital opportunity’.

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However, the penultimate stage before harnessing the chatbot benefits is developing one that fits your system and requirements amicably. The chatbot platform you select will eventually decide the chatbot you develop. While there are hundreds of bot builder platforms with alluring feature sets, enterprises must survey and distinguish the features that truly aid their primary concerns. They need to factor in and determine the platform that will augment agility, adaptability, and speed and deliver results at the earliest.

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With that view, a pre-trained chatbot platform that has all the jargon, domain-specific database, and required actions/redirections/APIs built into it serves as a blessing (without a disguise). Such a platform is easy to integrate, requires minimal coding, can be leveraged to develop a bot immediately, does not draw learning gaps for the development teams, and can easily be customized and scaled as per requirement. A.Ware is one such platform. It has bot building frameworks designed not only by industry standards but for business processes as well! It can be used to deploy bots into a website, mobile app, WhatsApp, Facebook, Google Assistant, Alexa, email, and across many more touchpoints to create an omnichannel consistency. With other attributes like ‘zero coding environment’, real-time analytics, and multi-app integration, A.Ware allows businesses can build their own chatbot in no time.

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