How Chatbot and Mobile Apps Works Together


Chatbots centrally whim to make use of a customary messaging channel for its deployments like Facebook Messenger or Skype. But as Andy Groves had quoted, “Privacy is one of the biggest problems in this new electronic age,” the question regarding the security of the data always remains a matter of concern. To avoid any kind of security blunders, enterprises are reckoning to build conversational bots in the customer’s private channel.

Enterprises have a common practice of employing web chat services on their websites. This serves the primary purpose of live chat with the customers or chatbot self-service. Some businesses are moving a step further in this cut-throat competition of satisfying customers with their services. They are into transferring this conversational experience straight into their mobile apps.

Before integrating a bot with the app, let us look upon the different types of app:

1. Native Mobile App

By using Direct Line API, native code apps can communicate with the bot framework via REST or web sockets.

2. Web-based mobile app

Structures and web language used to build a mobile app such as Cordova may establish a communication with the Bot using similar components of that of a bot embedded within a website using with a difference which is encapsulated within the shell of a native app.

3. IoT App

With the help of the Direct Line API, communication between an IoT app and the Bot Framework can be carried out. For enabling capabilities such as image recognition and speech, there might be a need for using Microsoft Cognitive Services.

Top Articles on How Businesses are using Bots:

1. Series of stories on AI, chatbots and how can they help businesses

2. What I learned in making three chatbots for small businesses

3. Why Messenger is the Ideal Bot Platform for Now

4. Chatbot Conference 2019 in NYC

The integration of Chatbots with mobile apps the companies have opted in three different ways:

1. Chatbot as an app

2. Chatbot in a tab

3. Chatbot as UI

Let us bellyflop each of them in details.

1. Chatbot as an App

Objective: Provision for a secure, dedicated, 24X7 conversational channel for the customers.

As the heading goes, all you are required to do is bundling a chatbot within a mobile app. Once done, distribute to the app stores.


1. Data privacy is maintained as there is no data sharing with social networks or third-party companies.

2. Chatbot development is budget friendly. Therefore developing a chatbot is much preferable than building an app with similar features.

3. Chatbots help to get rid of the complexity of structuring and reinforcing complex UI screens and interactions.

4. No dependency on the limitation of external messaging providers.

5. The rich UI is completely controlled within the conversational UI completely.

6. The need for learning curves for the users is absent except for the transactional bot.


1. There is always a need to download the mobile app.

2. There is always an extra acquisition cost for establishing a user base in a new mobile app.

3. A traditional UI is much suitable for charts or shopping cart.

Also Read: Why AI-Augmented Virtual Assistants Will Soon Be Your Medical Companion

The right time to have a chatbot as an App:

As per the conversations with the customers who have a will to own a chatbot as a mobile app, the majority aim to implement chatbots that are focused on internal employee facing scenarios.

Reason Behind this: The enterprise-grade messaging platforms like Skype for Business hasn’t tried their hands on the consumer platforms for chatbot support, adoption, and ecosystem.

Case Study:

Operator | iOS


If you have to order a casio for your eight years old, Operator is there for you. It is an app designed in aiding people in buying things. Tell your requirement to Operator by texting it, and someone somewhere will start researching for the best deal that would suit you. In other words, the chatbot plays the role of the middleman. The role of the Operator is to read the message by the user and analyze it and determine which is the perfect fit for the user of the Operator.

2. Chatbot in a Tab

Challenge with the First Approach: The requirement of having chatbot as an app requires a lot of effort and resources to grow.

Objective: To reduce app fatigue an effective way is to incorporate a chatbot in an existing mobile app having a user base.


1. The existing audience can have an introduction with the chatbot.

2. The options available are- Traditional UI and Conversational UI

3. The mechanisms for authentication and security present in the mobile app, both can be reused.

4. New users get comfortable with a chatbot easily for an initial experience rather than complex UIs.


The users might get confused with its usage if the mobile app’s functionality is a simple replica of your chatbot.

The right time to have a chatbot in a tab:

Want to optimize lengthy and repetitive forms? If so, then building chatbot within your existing mobile app will serve this purpose.


They are best suitable for structured processes like submitting stock orders, signing insurance or initiation of a bank account.

Case Studies:

There is a provision for electronic access to stocks, options, forex, futures and futures options in a comprehensive and immersive mobile app with the help of IBKR, a mobile trading app by Interactive Brokers. There is a separate tab for their IBot chatbot which is in turn given as a complement to the mobile experience by the Interactive Brokers.

3. Chatbot as UI

Objective: Rather than isolating the chatbot with a separate app, use the conversational UI rather than traditional UI. This tact is useful in low engagement and high abandonment rates.


1. Chatbots as UI has a combination of advantages of both first and second methods.

2. The engagement rates for your mobile app increases.


Conversational UI can be created by your own. You are not allowed for partially integrating a chatbot into a mobile app as none of the chatbot vendors are allowed.

The right time to use:

Worried about low engagement rates and high abandonment rates? Conversational UI is your stress buster.

Case Study

“Amy” is a virtual assistant piloted by complex machine learning algorithms and can be operated by humans. Scheduling meetings are always hectic. This AI software aids in scheduling across your entire company irrespective of your business genre.


It has become a fad to employ chatbots with mobile apps. This integration is constantly being explored by various companies irrespective of different verticals. Many Chatbot Development Companies are trying their hands on chatbot development in consideration with the above use cases explained.


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