How to Choose the Right AI-based Chat Bot for Your Business?
Updated on Apr 20th, 2021
Natalia uses a telemedicine app to find the best ophthalmologist for one strange problem that she’s been facing for a long time now.
She finds the chatbot icon on the right bottom corner that’s sharing vital information on the health scenario in her town. Clicking on it, she was greeted with:
“Hey There!!! What a great day to meet you?
Tell me the problems you are facing and let me help you find the best doctors”
Intrigued, she starts selecting the symptoms from the options provided, and by the end, she comes to know the problem is related to the brain for which she has to consult with a neurologist.
Well, the chatbot saved Natalia fee of 1 consultation that she was fixing with an ophthalmologist, and the hospital, a patient.
There are multiple similar ways in which chatbots can help you deliver the best experience to your target audience. Regardless of your industry, chatbots are nailing every aspect of the customer experience and rewarding businesses with great opportunities and customer retention.
But, how to choose the best one for your brand?
Discover the answer to the most crucial question here!!!
1. Truly Conversational
It may seem obvious but there’s a world of difference between a chatbot answering a question and holding an intelligent conversation. An engaging exchange will not only improve the customer experience but will deliver the data to help you increase your bottom line. To achieve this, the user interface needs to be as humanlike and conversational as possible.
A conversational chatbot must understand the user’s intent, no matter how complex the sentence; and be able to ask questions in return to remove ambiguity or simply to discover more about the user. It needs memory in order to reuse key pieces of information throughout the conversation for context or personalization purposes and be able to bring the conversation back on track when the user asks off-topic questions.
If you’re a multi-national company, you’ll need the chatbot platform you choose to do all this, and in your customer’s native language too.
2. Developmental Control
It’s very difficult to anticipate how people might use, or abuse, an AI application.
Certainly, Microsoft didn’t envisage that “helpful” members of the public would teach Tay to start Tweeting inappropriate messages. Tay was designed as a showcase of machine learning, but unfortunately very neatly illustrated the problem with some conversational AI development tools they lack the control required to supervise the behavior.
By ensuring a level of control within the application, enterprises can not only avoid awkward mistakes but provide a ‘safety net’ for managing unexpected exceptions during a conversation, always ensuring smooth customer experience.
3. Enterprise-Grade Solution
Few chatbot development platforms were built with the enterprise in mind. Consequently, features you might expect as standards such as version control, rollback capabilities, or user roles to manage collaboration over disparate teams are missing.
In addition, look for features that will aid the speed of development including automated coding, webhooks to allow flexible integration with external systems, and ease of portability to new services, devices, and languages.
4. Hybrid Model
Most chatbot platform development tools today are either purely linguistic or machine learning models. Both have their drawbacks. Machine learning systems function, as far as the developer is concerned, as a black-box that cannot work without massive amounts of perfectly curated training data; something few enterprises have. While linguistic-based conversational systems, which require humans to craft the rules and responses, cannot respond to what it doesn’t know, using statistical data in the same way as a machine learning system can.
A hybrid approach that combines linguistic and machine learning models is best and allows enterprises to quickly build AI applications whatever their starting point – with or without data – and then use real-life inputs to optimize the application from day one. In addition, it ensures that the system maintains a consistent and correct personality and behavior aligned with business aims.
5. Unique Personalization
Personalizing an automated conversation, whether it’s simply accessing account information to answer a billing query or taking into consideration that customer’s love of Italian food when recommending a restaurant, not only delivers a more accurate response, it increases engagement too.
While some information can be learned ‘explicitly’ (such as the customer choosing a preference from a list of features), it’s the automated learning through ‘implicit’ methods (like information gleaned from, previous interactions) that really harnesses the power of conversational AI. This can then be combined with other information and data sources such as geo-location, purchase history, even time of day, to personalize the conversation even further.
6. Data Ownership and Analytics
One of the key considerations in choosing a chatbot platform is data. People reveal vast amounts of information in everyday conversations. Their individual preferences, views, opinions, feelings, inclinations, and more are all part of the conversation. This information can then be used to feedback into the conversation to increase engagement, train and maintain your conversational AI chatbot interface; and analyzed to deliver actionable business data.
That’s why it’s so important that enterprises maintain ownership of their data. It’s surprising how many development tools allow businesses to create chatbots, but don’t actually provide any of the details of the conversation, just the outcome, such as that final pizza delivery order.
Alongside data ownership, carefully consider the data analytics package provided as part of the platform, including the flexibility in drilling down through the information and understanding the context of conversations, as well as the level of detail provided.
Conversational applications are gradually infiltrating all aspects of everyday life, so it makes sense to ensure that conversational applications can be easily ported to existing and future devices. While it’s easy to state that applications can be built to run on a variety of platforms or services, all too frequently each one requires a completely new build. Investigating how much of the original build can be reused at the start, may save significant resources in the long term.
It’s also worth looking at how the application will support your users as they swap from device to device during the day. Seamless persistence of conversations increases engagement and customer satisfaction.
8. Data Security
Data security is a key consideration for any enterprise, particularly when dealing with regulatory frameworks and customers’ personal information. Flexibility is essential in an AI chatbot platform to meet today’s exacting security conditions, across multiple geographies and legal requirements.
While most enterprises have no issue with a standard cloud deployment when complying with industry regulations, or ensuring security policies are met that the cloud isn’t always an option. Where this applies, ensure that an on-premises option is available.
9. Brand Differentiation
By adding an intelligent conversational UI into mobile apps, smartwatches, speakers, and more, organizations can truly differentiate themselves from their competitors while increasing efficiency. Customization offers a way to extend a brand identity and personality from the purely visual into real actions.
10. Proven Technology
And finally, before any final decision is taken, ensure you look beyond the marketing blurb. Check out real-life applications and talk to existing customers. Find out from them how easy it was to develop and build solutions; have they tried porting to new languages or services; how did they expand into new channels or devices; what benefits they’ve seen; and how they believe their Conversational AI chatbot platform will enable their digital strategy in the future.
Choosing the right chatbot is tough, but if assess these on the right metrics, it’s not daunting. We’re sure these points would prove to be helpful to you. In any case, team Matellio is right here to assist you for all the queries that you may have.
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