Sep

OUR AWESOME CHATBOT FEATURES

NMODES chatbots and conversational AI solutions come with a unique set of features.

Our goal is to make it easy for businesses to create and manage chatbots. The features we offer are important for successful implementation of a chatbot not only because they significantly improve its quality, but they also allow you to edit your chatbot in natural language, without any need to have technical knowledge or AI specialist in the team. 

1. Free AI Training 

Our chatbot solutions come with free AI training for life.

We will train your chatbot and continue to enhance it indefinitely.
It is our responsibility to ensure that your chatbot has the updated natural language processing capabilities. It is also our responsibility to guarantee that it understands not only common language but also language that is specific to your business, such as names of the products, terminology used in your industry, inventory list, and more. 

Your chatbot will be interacting with the customers all the time. We will enable it to learn from these interactions continuously and improve its language understanding and responses as a result of this learning.

2. Editing in natural language 

We realize that AI is a complex body of knowledge and one of your biggest concerns is that you are not familiar with it well enough. We made sure that you don’t need to be technically savvy to successfully manage a chatbot. Using our simple and friendly online interface you can control your chatbot in real time using common natural language. No technical knowledge is required.

At NMODES we continuously improve our AI capabilities. We use our AI not only to make the experience of your customers, conversing with your chatbot, better, but also to make your own experience, conversing with our platform, better.

Eventually the platform will be able to interact with you fully in natural language. We are not entirely there yet (it is an immense task). Still, we hold true to our promise that there is no need in being technically savvy to operate our platform even today. When the platform does not understand natural language our highly trained specialists are always ready to take over and provide support.


3. Real time connectivity 

Often there is a need for chatbot to access structured data (such as inventory database) to answer customer’s question. We made it easy for your chatbot to create external queries in real time and modify the responses accordingly. Your chatbot is able to decide in the middle of the conversation, based on the information it received from your database, how to respond and how to proceed with the conversation.

These are the most exciting among the features we created so that our customers have easy and enjoyable chatbot experiences. But there are other features available: conversational templates, dynamic AI Engines clustering, multiple widget skins and more! Let us know if want to see the full list of features.

To learn about the core technologies required to build a chatbot check out this post:

Interested in reading more? Check out our other blogs:

Artificial Intelligence Chat Is Evolving Faster Than IVR

                                                         

Although it doesn’t feel like all that long ago, way back in the 90s one of the most important factors to a call center’s success was the ability to route a customer to the right support agent with the IVR (Interactive Voice Response). Countless hours were spent identifying the most efficient call routing patterns and expert agent capabilities to ensure that your request reached the right person quickly. This technology is still widely used today and there are still teams in the largest companies programming IVR systems to accomplish pretty much the same goal.

As the standard for customer support evolved there have been many attempts to improve the function and the customer experience associated with IVRs to reduce hold times and provide more relevant support faster. Even today some companies will use their IVR system as a way to keep a customer on hold, rather than provide a solution, when agents are inundated with calls.

For those of us who’ve worked in the voice industry for some time, we’ve seen first-hand the attempts to accomplish a customer’s need before reaching an agent. First there was expert agent routing that delivered your call to the agent most qualified to help you. Then came advances in voice recognition, which today has evolved to be a very effective tool to increase containment rates and deflect calls from reaching a live agent. My two favorite examples of the power of voice recognition are Cox Communications and Capital One, two examples of great voice recognition and routing.

Our memory, however, is short. It wasn’t so long ago that we were all pulling our hair out punching digits into the phone or constantly repeating “agent”, “Agent”, “AGENT”, AGENT!!!!!”.

Whether it was a limit of computational power or the sheer cost of developing and implementing advanced call center technology, it took decades for phone systems to be able to front end the customer support process as efficiently as they do today. Thankfully we all survived to see it without boiling over from the hypertension usually associated with calling with a customer service department.

Bad customer experience is definitely not the case with Chat Artificial Intelligence (Chat AI). While we seem to hear about the shortcomings of Chat AI like the disconnected conversations and the robotic like responses, these experiences are usually the product of Chatbots with limited AI functionality or early stage deployments. The increases in both computational power and the massive advancements in machine learning are driving excellent customer experiences that improve over time.

When was the last time you heard of technology actually performing better, on its own, without a ton of additional development work or continuous updates? Well, that’s the case with Artificial Intelligence. Like a person, the more experience it has interacting with customers and information, the better it performs with little need to be manually improved or fine-tuned.

Today, AI Chat can be used to answer a large majority of customer requests and because Artificial Intelligence learns as it is used, customers prefer to interact through AI chat to avoid all of the frustrations commonly associated with calling a contact center agent. 

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Intent-driven Data Critical for Sales Growth

One of the most central causes of missed growth opportunities and overspending is a failure on the part of businesses to create strategies that are tailored to the intent of the consumer. Recognizing and harnessing visitor intent brings increased engagement with relevant messages and calls to action.

Once a business identifies purchase intenders it can create content that aligns with their needs and desires in order to increase the likelihood of conversion. Consequently it can pick up on pre-sale signals from visitors in the research phase and drive lead-nurturing initiatives accordingly. The ability to identify this spectrum of visitor intent is key to creating relevant engagement campaigns that drive sales.

nmodes has been at the forefront of delivering consumer intent to businesses.

We sort the intents based on conversation topics, called ‘streams’.

Here is a stream of people looking for a hotel:

A stream of people who are getting married:

A stream of people thinking of going on a cruise:

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