Custom Chatbot Development For Modern Enterprises

This article attempts to explain why small startups and large enterprises are interested in having a chatbot solution. So, if you are someone who wishes to use them for their advantage, here are some of your questions answered:

• Why are Chatbots Essential for Business?
• What are the Different Types of Chatbots?
• Application of Chatbots Across Different Industries?
• What are the Best Practices for Developing a Smart bot?
• How Much Does it Cost to Develop a Chatbot?

They are categorized into two main types based on their functionality.

1. ML-led (Conversational AI-Bots): These bots learn from previous conversations and efficiently handle complex queries in the future. They can accurately process questions and understand the context well.
   -Ideal for offering personalized customer service across industries.
2. Rule-based (Informative Bots): The info bots can only perform tasks they are programmed for, like making a reservation or paying a bill. They can be trained to answer FAQs and offer specific information, like weather forecasts and more.

-Ideal for answering close-ended queries and can be trained on set rules.

Here’s how different business segments are using bots to stay accessible, serve customers and supercharge their sales & marketing efforts:

The future holds brilliant opportunities for enterprises with virtual help desk and info bots. Implementing them as an early adopter will put you in a much better position to benefit from the evolving technology ecosystem.

Before you get started, it is crucial to define what you want the bot to do, the scope of activities and the possible challenges before the chatbot is fully trained to reach its full potential.

Follow these best practices to build an intelligent chat assistant

1. Define its Goals Based on Audience Analysis
Knowing the needs and pain points of your audience will equip the bot to answer their queries accurately. Diving deeper into what your customer wants and accordingly approaching the development process will ensure success.

2. Define the Right Technology Deployment Platform
To arrive at the right language, tech and platform, you need to understand the customer’s challenge area and how you plan to solve it. And, with that you need to ask yourself the following questions:

• Which channel will it be used for? If it is a text-based bot for social siltes like Facebook or Slack or others? Or you pick one of the frameworks and have it designed
• Type of integrations required & languages do you want to integrate
• What is the expected daily volume of customers?
• Which of your customers highly prefer chatbot development platforms?

As interactions occur and engagement increases, you will also need to assess if the infobot is adding value.

3. List the Possible Integrations

Depending on your business type, these integrations could be any of the following:

• Google Calendar
• CRM (Salesforce, Zoho)
• Maps
• Cloud storage solution
• Other software that your enterprise is using (Slack, Jira, Trello and more)

You also need to evaluate these integrations for channels, languages & automation. For this, you can use KPIs like importance, impact, ease of use, and time-efficiency. A proficient chatbot software development partner, like Rishabh, can help you make an informed decision.

4. Build a Content Model
Humans can ask the same question in several ways. So, your infobot should be smart enough to understand the context and provide an appropriate answer. Also, the response needs to be quick and accurate to add value. With small data sets, you will have to prepare modules on how to train the bot. A content model will allow you to build a bot that understand questions and give better answers, everytime.

5. Design a Dialog & Process Flowchart
A logical flowchart can create a user journey that would cover the spread of dialogs across questions. When the information for every answer is clearly defined, your virtual assistant will be equipped to offer satisfactory responses.

6. Train the Bot
The bot needs to be trained on user intent and explain to them different variants of what customers are requesting. For this, as a chatbot architecture design & development process, you will have to make the bot understand the existing data sets for text-based elements and machine learning related aspects. It will help assess the learning progress while working appropriately.

7. Rigorous Testing
Thorough testing is a vital factor for the success of any conversational agent. So, it is recommended to have a proficient chatbot app development team to perform the real-user testing. Periodic testing and improvements can make the agent smart and accurate over time.

There is no one-size-fits-all answer to this. To estimate the cost of developing a chatbot solution, it is imperative to understand the business needs, user demands, and chatbot features to make a great solution. The duration required for end-to-end development may range from a few weeks for a simple use case to a few months for a feature-rich solution.

For instance, eCommerce companies will need a conversational bot designed to display products and answer shipping questions. However, a healthcare facility would want an infobot that can book appointments and track prescriptions.
If you are looking to build a smart virtual assistant, the best approach is to partner with an enterprise chatbot development firm experienced in your niche.

While there is no shortage of off-the-shelf chatbots, you need to consider “your data and context” to create a conversational bot. The chatbot development cost would heavily depend on the said features.