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Here’s How You Measure the ROI from Chatbots

Nidhi Agrawal
5 minutes, 6 seconds read

IBM reports that globally businesses spend over $1.3 trillion/year to handle roughly 265 billion customer calls. Chatbots spring up to minimize the expenditure on handling customer queries, especially the most redundant ones.

It’s quite common for businesses to assess the return on investment before adopting new technology.

However, ROI from chatbots may vary according to the purpose it serves. For example, an insurance chatbot ROI differs from that of an HR chatbot. Here are certain parameters to consider for calculating the return on investment from chatbots.

#1 Average Human Live-chat Cost

The total number of tickets raised per month and the number of agents involved gives an idea of the average price per contact.

According to Help Desk Institute, the average cost/minute for a live chat is $1.05, while the average cost per chat session is $16.80. Assuming an organization handles 10,000 chats in a month, the cost incurred sums up to $168,000/month.

Depending on the number of people involved and their compensation, you can calculate the amount you’re spending on your organization’s customer support. Here’s a salary reference, which can be used in further calculations.

sample customer support operational cost

The salaries mentioned are referred from Job Futuromat 2019 wrt 12 months, 18 working days, 8 hours.

The actual operational cost also depends on material resources invested like office space, conveyance, communications, gadgets, etc. You can consider these aspects on your chatbot ROI calculator.

#2 Bot Installation Cost

The phases of bot installation cost involves brainstorming sessions, integration, and training both bots and agents.

During kick-off sessions, stakeholders discuss the scope of the bot, define goals and responsibilities, and make a project plan. After this, programmers and managers integrate the bot on the organization’s website and other platforms. Customizing the bot according to the client’s support cases covers the bot training phase. Testing the bot and training agents to use it are also factored into the ‘bot’ installation costs.

According to Ometrics, the average development charge for a chatbot may range from $1,000 to $5,000. But, this is a one-time charge, and after that the bot-developer may bill for maintenance charges.

chatbot roi calculator: installation cost

If the chatbot requires a higher level of customization, then the bot-developer may also claim additional charges. Also, the number of days spent for bot installation varies according to industries and organizations.

#3 Gains through Bots

Here we’re assuming all the customer queries are routed through the bot and it is accurate 50% of the time. Out of the 50% queries handled by a bot, if half of them are self-served and the remaining required human intervention, then monthly gains from the bot can be-

chatbot roi calculator: gains from chatbot

You can find the exact cases and accuracy from your bot’s analytics dashboard.

#4 Monthly Maintenance Cost

Like humans, bots also require human assistance for its successful operation. Its monthly maintenance cost is a summation of the organization’s human resources it needs and developer’s charges. Here, let’s assume a chatbot maintenance fee, which ranges from $100 to $1,000 a month. Similar to the bot development charges, maintenance fees vary according to bot capabilities.

chatbot roi calculator: montly maintenance cost

#5 Chatbots Return on Investment Calculation

The return on investment is a ratio of benefit from the investment to the cost of investment. It evaluates the efficiency of an investment. Mathematically, ROI = (Current Value of Investment – Cost of Investment) / Cost of Investment.

Since chatbots incur a one-time development cost and recurring monthly maintenance cost, here’s the chatbot ROI calculation from both perspectives.

Chatbot ROI during the first month: This includes the bot installation charges. 

For the above case,

ROI = (Gains through bot – Installation charge – maintenance charge)/(installation charge + maintenance charge)

ROI = ($63,000 – $9,292 – $3,647)/($9,292 – $3,647)

ROI = 3.9 or 390%

Chatbot ROI after the first month: This excludes the bot installation charges. 

For the above case,

ROI = (Gains through bot – maintenance charge)/(maintenance charge)

ROI = ($63,000 – $3,647)/($3,647)

ROI = 16.3 or 1630%

Using this method, you can build your own chatbot ROI calculator considering your own business parameters.

NLP and AI-powered chatbots can yield a better return on investment. For instance, Religare has incorporated a service chatbot on its Web portal and WhatsApp integration to handle customer queries. It has resulted in 10 times more customer interaction and 5 times more sales conversion.


For the above case, where bots are able to handle 50% of customer queries, there’s a direct 50% capital gain to the organization. The human-time saved can be utilized for more productive tasks, which can eventually accelerate the organization’s productivity. 

Powerful bots result in better success rates for customer facing operations. For example, Diageo’s iDia chatbot has led to a 55% drop in help desk tickets. 

Here are more enterprise chatbot use cases.

Researchers predict that by 2025, chatbots will accomplish more than 90% of the B2C interactions. Also, chatbots can cut operational costs by more than $8 billion per year in the next three years.

We specialize in developing industry-specific AI-powered chatbots. Drop us a word at to learn more.


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Chatbots are the assistants of the future and they are taking the Internet by storm. Ever since their first appearance in 1994, the goal was to create an AI that could conduct a real dialogue with their interlocutors. The purpose is to free up customer service agents’ time so they could focus on more delicate tasks- which require a more human approach.

If you are thinking about including a chatbot on your website, here are the things you need to keep in mind to boost customer engagement and deliver high-quality services.

Define your audience

First things first- think about who will be interacting with the chatbot? Who are your customers? How do they talk? How can you address them in a way they’ll enjoy? How can you help them?

For instance, if your company sells clothes that are mostly designed for young adults, using a less formal tone will be much more appealing to them.

Lisa Wright, a customer service specialist at Trust My Paper advice: “Customer service calls are usually recorded, so listening to a few of them can be a good place to start designing your chatbot’s lines of dialogue.”

Give your bot some character

People don’t like to talk to plain, simple robots. Therefore, giving your chatbot some personality is a must. Some brands prefer naming their chatbots and even design an animated character for them. This makes the interaction more real.

For example, The SmarterChild chatbot- designed back in 2000, was able to speak to around 2,50,000 humans every day with funny, sad, and sarcastic emotions.

However, the chatbot’s character needs to match your brand identity and at the same time- appeal to customers. Think about – how would the bot speak, if they were real? Are there some phrases or words they would never use? Do they tell jokes? All these need to be well-thought through, before going into the chatbot writing and design phase.

According to a report published by Ubisend in 2017, 69% of customers use the chatbot to get an instant answer. Only 15% of them would interact for fun. Thus, don’t sacrifice the performance for personality. 

Also read – 5 Key Success Metrics for Chatbots

Revise your goals before chatbot writing

Alexa- Amazon bot has 30+ skills which include scheduling an appointment, booking a cab, reading news, playing music, controlling a smartphone, and more. However, every business bot doesn’t need to be a pro in every assisting job.

Before entering the writing phase, think over once again – WHY you need a chatbot? Will it help customer service only? Or will it also help in website navigation, purchase, return, refund, etc.?

Usually, customers want one of the three things when they visit your site: an answer to something they’re looking for, make a purchase, or a solution to their problem. You can custom build your chatbot to tackle either one or all of these three situations. Many brands use chatbots to create tailored products for their clients.  

Cover all possible scenarios

When you start writing the dialogue, consider the fact that a conversation can go in many directions. To ensure that all the situations are covered- start with a flowchart of all possible questions and the answers you chatbot can give.

To further simplify your chatbot writing, take care of one scenario at a time and focus on keeping the conversation short and simple. If the customer is too specific or is not satisfied with the bot’s response, do not hesitate to redirect them to your customer service representatives.

For instance, Xiaocle is one of the most successful interactive chatbots launched by Microsoft in July 2014. Within three months of its launch, Xiaocle accomplished over 0.5 billion conversations. In fact, speakers couldn’t understand that they’re talking to a bot for 10 minutes.

Also read – Why should businesses consider chatbots?

This article is contributed to Mantra Labs by Dorian Martin. Dorian is an established blogger and content writer for business, career, education, marketing, academics, and more.


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The antiquated commodity of Financial ‘Coverage & Protection’ is getting a new make-over.  Conventional epigrams like ‘Insurance is sold and not bought’ are becoming passé. Customers are now more open than ever before to buying insurance as opposed to being sold by an agent.  The industry itself is witnessing an accelerated digitalization momentum on the backs of 4G, Augmented Reality, and Artificial Intelligence-based technologies like Machine Learning & NLP.

As new technologies and consumer habits keep evolving, so are insurance business models. The reality for many insurance carriers is that they still don’t understand their customers with great accuracy and detail, which is where intermediaries like agents and distributors still hold incredible market power.

On the other hand, distribution channels are turning hybrid, which is forcing carriers to be proficient in their entire channel mix. Customer expectations for 2020 will begin to reflect more simplicity and transparency in their mobility & speed of service delivery.

A recently published Gartner Hype Cycle highlights 29 new and emerging technologies that are bound for greater business impact, that will ultimately dissolve into the fabric of Insurance.

For 2020 and beyond, newer technologies are emerging along with older but more progressively maturing ones creating a wider stream of opportunities for businesses.


Irrespective of the technology application adopted by insurers — real, actionable insights is the name of the game. Without it, there can be no long term gains. Forrester research explains “Those that are truly insights-driven businesses will steal $1.2 trillion per annum from their less-informed peers by 2020”.

Based on the major trends identified in the Hype Cycle, 5 of the most near-term disruptive technologies and their use cases, are profiled below.

  1. Emotion AI
    Emotion Artificial Intelligence (AI) is purported to detect insurance fraud based on the audio analysis of the caller. This means that an AI system can decisively measure, understand, simulate and react to human emotions in a natural way.

    F0r Insurers, sentiment and tone analysis captured from chatbots fitted with emotional intelligence can reveal deeper insights into the buying propensity of an individual while also understanding the reasons influencing that decision.


Autonomous cars can also sensors, cameras or mics that relay information over the cloud that can be translated into insights concerning the emotional state of the driver, the driving experience of the other passengers, and even the safety level within the vehicle.

Gartner estimates that at least 10% of personal devices will have emotion AI capabilities, either on-device or via the cloud by 2022. Devices with emotion AI capacity is currently around 1%.

  1. Augmented Intelligence
    Augmented Intelligence is all about process intelligence. Widely touted as the ‘future of decision-making’, this technology involves a blend of data, analytics and AI working in parallel with human judgement. If Scripting is rules based automation, then ‘Augmenting’ is engagement and decision oriented.

    This manifests today for most insurance carriers as an automated back-office task, but over the next few years, this technology will be found in almost all internal and customer facing operations. Insurers can potentially offer personalised services based on the client’s individual capacity and exposure to risk — creating opportunities for cross/up-selling.

Source: Gartner Data Analytics Trends for 2019

For instance, Online Identity Verification is an example of a real-time application that not only enhances human’s decision making ability, but also requires human intervention in only highly critical cases. The Global value from Augmented AI Tools will touch $4 Trillion by 2022.

  1. AR Cloud
    The AR Cloud is simply put a real-time 3D map of an environment, overlayed onto the real World. Through this, experiences and information can be shared without being tied down to a specific location. Placing virtual content using real world coordinates with associated meta-data can be instantly shared and accessed from any device.

    For insurers, there is a wide range of opportunities to entice shopping customers on an AR-Cloud based platform by presenting personalized insurance products relevant to the items they are considering buying.

    The AR ecosystem will be a great way to explain insurance plans to customers, provide training and guidance for employees, assist in real-time damage estimation, improve the quality of ‘moment-of-truth’ engagements. This affords modern insurance products to co-exist seamlessly along the buying journey.

  2. Personification
    Personification is a technology that is wholly dependent on speech and interaction. Through this, people can anthropomorphize themselves and create avatars that can form complex relationships. The Virtual Reality-based concept will be the next way of communicating and forming new interactions.

    VR Applications such as  accident recreation, customer education and live risk assessment, can help insurers lower costs for its customers and personalise the experience.

    Brands have already begun working their way into this space, because as they see it — if younger generations are going to invariably use this technology for longer portions of their day for work, productivity, research, entertainment, even role-playing games, they will shop and buy this way too.

  3. Flying Autonomous Vehicles and Light Cargo Drones
    Although this technology is only a decade away from being commercially realized, the non-flying form is about to make its greatest impact since its original conception. Regulations are the biggest obstacle to the technology taking off, while its functionality continues to improve.

    The Transportation & Logistics ecosystem is on the brink of a complete shift, which will create a demand for a wide array of insurance related products and services that covers autonomous vehicles and cargo delivery using light drones.

While automation continues to bridge the gaps, InsurTechs and Insurance Carriers will need to embrace ahead of the curve and adopt newer strategies to drive sustainable growth.

Mantra Labs is an InsurTech100 company solving complex front & back-office processes for the Digital Insurer. To know more about our products & solutions, drop us a line at


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