Chatbot technology is a designed tool powered by the rules of Artificial Intelligence (AI) and Machine Learning (ML), acts as a simulator of human conversation for the purpose of automation and business process. Chatbots facilitate users to interact when placed within the messenger apps that act as a platform for supporting the bots.

Like Siri for chatbot brands, chatbots are quickly rising as a new “voice” in consumer communications. These chatty computer programs respond to texts, effectively carrying on conversations with the humans on the other end which can be a potential customer. Thanks to advancements in Natural Language Processing (NLP) and Artificial Intelligence (AI), which help in building these bots with stronger conversation abilities than ever before.

There are some advantages to using chatbots:

  • They can be proactive or reactive to chats.
  • Their responses are consistent every time despite knowing the customer.
  • They can respond to customers immediately and even effectively.
  • They can help you in collecting important data and also learn from the data collected.
  • They can make use of them through a variety of different mediums like SMS, live chat, or even social media.

Understanding Chatbots and their Types

Smart bots take an extremely long time to develop, code, launch, and test, but they’re often a necessity for meeting customer satisfaction and their goals.

Here is an easy-to-build bot versus a difficult-to-build one.

Easy-to-build bot

Think like you want to build a bot that tells the current temperature to the users. The dialog for the bot only needs coding to recognize and report the requested location of the user and temperature. To do this, the bot needs to pull a lot of data from the API of the local weather service, based on the user’s location, and to send the data back to the user basically as a few lines of template code and you’re done with it all.

Difficult-to-build bot

What if you have to create a bot for a major online clothing retailer? For starters, the bot will require a greeting and some basic details (“How can I help you?”) as well as a process for saying its goodbyes to the customer. In between, the bot might need to respond to input, which could range from shopping and inquiries to questions about shipping rates or return policies of the product, and the bot must possess a wholesome set of the script for fielding questions it doesn’t understand.

From any point in the conversation, the bot will ask you where to go next. If a user writes, “I’m looking for new pants,” the bot can ask a cross-question, “For a man or woman?” They type, “For a woman.” Does the bot then ask about the size, style, brand, or color of the product? The possibilities are endless, and every one of them has to be mapped with rules.

How do chatbots work?

A chatbot acts as an intermediary that imitates human conversations by initiating live chats instantaneously and responding tirelessly to the user queries at any point in time.

All the working chatbots which are in usage today are mainly based on this model:

  1. Knowledge Base/ CMS:
    1. Real-time, personalized customer experience
    2. Universal contact accessibility and personalization
    3. Ability to reach and retain customers.
  1. NLP Layer:
    1. Mapping can give input in natural language into a useful representation
    2. Analyzing different aspects of the language.
  1. Data Store:
    1. Data required to train the bot
    2. Users chat comes to the bot once it’s deployed.

Why chatbots are important

Chatbot applications and streamline interactions between people and services, enhancing customer experience. At the same time, they can offer companies new opportunities to improve the customer engagement process and operational efficiency by reducing the typical cost of your customer service.

The success of a company and a chatbot solution should be able to effectively perform both of these tasks. Human support plays a key role here to enhance chatbot. Regardless of all kinds of approaches and the platform, where human intervention is crucial in configuring, training, and optimizing the chatbot system.

Best Chatbot Strategy

Your chatbot strategy will depend on your company goals. The best thing to do is to ask yourself some basic questions:

  1. What is the ultimate goal of your chatbot like distribute content, create purchases, explain directions, customer support, etc.?
  1. Who will be creating and managing your chatbot? How much time will they have to do so?
  1. What analytics are you looking to get from your chatbot? And where do you need this information stored?
  1. How consistently accurate do you need this information to be like if there is an NLP error, will your users be flexible with this error?
  1. What platform will best serve your users? Is it for internal purposes? If so, do your employees often use Slack?
  1. How much time can you devote to managing your chatbot? How big of a priority are chatbots for your company?
  1. Will you require images or videos in your chatbot?
  1. Do you need your chatbot to upload and save documents?
  1. Will you require your chatbot to have the capability so it can “talk” to your internal systems like inventory or CRM systems?
  1. Have a separate marketing budget to launch and acquire potential users for your chatbot if it’s on external platforms like Kik, Facebook, etc?
  1. How will your users utilize your chatbot? Will they request simple direct tasks, or might they be varied and nuanced? 
  1. What will be the most convenient way to use your chatbot? Through voice or audio or both? And if both, at what point will you tell the user to switch?
  1. Who do you need to have access to the data of your chatbot? Will, it must be within the tech team’s domain, or will the marketing team need full access to both editing and analytics?

In conclusion

For many of the applications, the chatbot is connected to the database of the company. The database is utilized to sustain the chatbot and provide appropriate responses to every set of users and audiences. NLP can translate human language into data information with a blend of text and the patterns that can be useful to discover applicable responses to the audience.

There are NLP applications, programming interfaces, and services that are utilized to develop chatbots. And make it possible for all sorts of businesses – small, medium, or large-scale industries. The primary point here is that smart bots can help you in increasing the customer base by enhancing the customer support services, thereby helping to increase sales.

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