OUR AWESOME CHATBOT FEATURES

sasha uritsky

Sep 05, 2018

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.

WHAT IS AI TRAINING? LEARN ABOUT BASIC CONCEPTS nmodes.com

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:

CHATBOT PLATFORMS. HOW TO CHOOSE THE RIGHT ONE?nmodes.com

Interested in reading more? Check out our other blogs:

Social selling. Difference between Facebook and Twitter

There are obviously some key differences between Facebook and Twitter that make them appealing to different people as well as businesses. If possible, businesses should try to leverage both networks in their marketing and sales efforts.

But marketing approaches for each network differ. Consequently social selling approaches differ as well. Here are some major differences of the two networks that impact sales strategy:

- Twitter lets all the accounts commingle, Facebook makes a definite distinction between business and personal. This can be an issue because a business page cannot proactively connect with individuals with personal profiles. Individuals have to first like a business page and still the business can’t reach out to them directly unless they message first. This is not the case with Twitter, as anyone can follow pretty much anyone.

- Facebook preferred way to market products and promote online sales can be compared to a showroom. The prospects can see the product and purchase it through some other channel, however engagement (with prospects) is limited to friends and followers. Hence growing the number of friends and followers becomes a critical task on Facebook. Twitter does not offer promotional capabilities but engagement activity is not limited to followers. The engagement on Twitter is therefore more straightforward and can lead to direct sales.

- Facebook user data is typically open to friends or followers. Twitter data is typically open to the entire world.

- Twitter is fast (minutes). Facebook is slower (hours and days).

- Twitter is more about building a brand identity. Facebook is more about business relationships.

To summarize, a direct timely engagement could be a good strategy on Twitter. In a typical scenario a user tweets that she needs a taxi or asks where to dine tonight. A taxi company or a relevant restaurant engages in a conversation and secures a customer. It is an efficient approach with immediate ROI.

On Facebook a good strategy is to grow and educate a community of followers. Facebook is excellent for promotional campaigns. This is a longer-term strategy with effects not visible until after several months.

What Is AI Engine and Do I Need It?

Chatbots and assistant programs designed to support conversations with human users rely on natural language processing (NLP). This is a field of scientific research that aims at making computers understand the meaning of sentences in natural language. The algorithms developed by NLP researchers helped power first generation of virtual assistants such as Siri or Cortana. Now the same algorithms are made available to the developer community to help companies build their own specialized virtual assistants. Industry products that offer NLP capabilities based on these algorithms are often called AI engines.

The most powerful and advanced AI engines currently available on the market are (in no particular order): IBM Watson, Google DialogFlow, Microsoft LUIS, Amazon Lex.

All these engines use intents and entities as primary pnguistic identifies to convey the meaning of incoming sentences. All of them offer conversation flow capability. In other words, intents and entities help to understand what the incoming sentence is about. Once the incoming sentence is correctly identified you can use the engine to provide a reply. You can repeat these two steps a large number of times, thus creating a conversation, or dialog.

In terms of language processing ability and simplicity of user experience IBM Watson and Google DialogFlow are currently above the pack. Microsoft LUIS is okay too; still, keeping in mind that Microsoft are aggressively territorial and like when users stay within their ecosystem, it is most efficient to use LUIS together with other Microsoft products such as MS Bot Framework.

Using AI engine conversation flow to create dialogs makes building conversations a simple, almost intuitive, task, with no coding involved. On the flip side, using AI engine conversation flow limits your natural tendency to make conversations natural. The alternative, delegating the conversation flow to the business layer of your chatbot, adds richness and flexibility to your dialog but makes the process more comppcated as it now requires coding. Cannot sell a cow and drink the milk at the same time, can you?

Amazon Lex lacks the semantic sophistication of their competitors. One can say (somewhat metaphorically) that IBM Watson was created by linguists and computer scientists while Amazon Lex was created by sales people. As a product it is well packaged and initially looks pleasing on the eye, but once you start digging deeper you notice the limitations. Also, Amazon traditionally excelled in voice recognition component (Amazon Alexa) and not necessarily in actual language processing.

The space of conversational AI is fluid and changes happen rapidly. The existing products are evolving continuously and a new generation of AI engines is in the process of being developed.