Hey guys this concept shows a chatbot based expert network that I made for fun:
The goal is to show how you can solve the agency problem in a self service more accessible way.
Curious if you’d use something like this for market research and product validation?
Other feedback is welcome!
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Chatbots are getting popular day by day. Though they are not as perfect as we would like them to be but they can be very useful to both users as well as service providers.
Chatbots are currently being used in various industries from ecommerce, Realestate, Logistic, Healthcare to Spirituality with different roles like to answer FAQs, Lead generation, appointment scheduling, customer feedback gathering. Also, it works as a standalone app for eCommerce which can be integrated with different chat channels like Telephone, SMS, Google Assistant, Facebook Messenger, Telegram, Website, etc.
WHY APPOINTMENT BOOKING CHATBOT?
One of the most prevalent uses of chatbot is to book appointments. Appointment booking chatbots work tremendously well in various industries from Healthcare (Hospitals, clinics) Restaurant reservations, Home installation services to Salon. Even though the appointment booking process seems to be the same for every industry, the reality is quite different. Each industry brings its own requirements and challenges.
Also, Study shows people who engage in repeated work often feel constricted and frustrated thus their output in terms of the effectiveness of dealing with customers gets hampered and no business can afford this situation.
Customer’s perspective
A recent study shows, because of the hectic schedule, working-class people usually do not get time during office working hours and they tend to choose non-working hours to enquire about the services or schedule their appointments. Imagine, if there is no one available to attend a call at that time to cater the customer’s query that can be a huge loss for the business.
Technological trends
We are now experiencing a new trend where many people expect the answers at their fingertips, and to find them, they’re turning to the nearest gadget. For service providers, it becomes essential to be present across devices and across the multiple chat channels.
Furthermore, Voice Assistant technology has opened a new front itself. More and more people are adopting voice technology which forces businesses to be present on each possible platform. Chatbot has the capability to be integrated with multiple chat channels is the greatest advantage a company can invest in.
1. 3 Tips for your Voice and Chatbot Program from Gartner’s Customer Service Hype Cycle 2020
2. Deploying Watson Assistant Web Chat in Salesforce Lightning Console
3. Are Chatbots Vulnerable? Best Practices to Ensure Chatbots Security
GETTING STARTED WITH DEVELOPMENT
When you plan to build any product (in this case an Appointment booking chatbot), you have to answer these following fundamental questions:
[1] Over millions of human resources are being involved in a task/activities for instance Answering basic queries, working hours, Availability of slots or scheduling an appointment for the customers where a simple AI-driven chatbot can do it more efficiently and economically. So we want to build a chatbot which will take care of the appointment booking process and it can answer the customer’s queries across the chat channels.
[2] As far as customer’s benefits are concerned, customers can book their appointment from anywhere at any time even from their preferred chat channels. And if customers feel they will not be able to make it at the scheduled time, they can either reschedule appointments or delete appointments at any time.
When it comes to a Development decision, a couple of questions can arise in one’s mind
[1] As far as conversation flow is concerned, we are clear with our vision. We will keep the conversation flow simple so that with minimal customization as many as businesses can use the AI-Appointment booking chatbot.
[2] After deciding the conversation flow, the next big and crucial question comes, which platform should we use to build this Appointment scheduling chatbot. There are various chatbot building platforms available such as:
Each platform has its own positives and negatives but our choice was pretty obvious. We chose Dialogflow to build Appointment booking chatbot.
There are few reasons behind choosing Dialogflow.
[3] To let customers access the bot from their preferred chat channels, we have decided to offer this appointment booking chatbot on Website, Google assistant and Telegram in the first phase and in the second phase, we’ll be adding Telephone and SMS as well.
NTEGRATION WITH EXISTING APPOINTMENT BOOKING SYSTEM
Many of the businesses would be using an existing appointment booking system. And if they are happy with their booking system then it’s unlikely that they would switch to a new system. Taking that into consideration, we have planned to integrate our appointment booking chatbot with as many existing booking systems as possible.
We have started with Google Calendar integration and we’ll be integrating more systems in near future.
Google calendar will keep a record of all the appointments in the service provider’s Google calendar which he/she can access from anywhere (e.g. Mobile phone, Laptop). Appointment Booking chatbot also sends the reminder to the customers which ultimately decreases the “no show”.
Challenges
The Journey of building an Appointment Booking Chatbot was not an easy one but it was full of excitement. Having a customer-first approach in mind, Our cross-functional team worked hard towards building a fine product. When it comes to making this chatbot available across the chat channels, we have gone with the same fundamental approach “Customer-first”. We have integrated the same chatbot on different chat channels like Website, Google Assistant, Telephone, SMS, Telegram, Facebook Messenger so that the customer can choose to book appointments on their preferred chat channel. Publishing the chatbot on multiple chat channels will help service providers to have better reach which ultimately leads to more business opportunity and happy customers.
But managing the integration of the same bot across all the chat channels isn’t a cakewalk. Each chat channel has a different interface and managing the same bot response is quite difficult. Let’s take an example of suggestion chips.
Benefits of Appointment Booking Chatbot
As many businesses are constantly eyeing on decreasing the human resource dependency and moving towards automation, the chatbot can be the best tool to start with Automating the business activities.
Case Study: Building Appointment Booking Chatbot was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.
We are living in an era of upgrades. This is what Matt D’Avella said when talking about how technology became the main focus of many people’s life nowadays.
But How can we use technology to improve the effectiveness of training? Let’s look at new trends in technology in e-learning and see how we can use this to effectively improve learning in the workplace.
With the use of technology, better e-learning content can be produced through continuous access to a multitude of resources. Not to forget, the latest technology also helps you create the same content in shorter amounts of time.
With the use of technology, better e-learning content can be produced through continuous access to a multitude of resources. Not to forget, the latest technology also helps you create the same content in shorter amounts of time.
More content can be added. And the same content can be expressed in a better way which will make the e-learning course easier and more fun to have.
1. 3 Tips for your Voice and Chatbot Program from Gartner’s Customer Service Hype Cycle 2020
2. Deploying Watson Assistant Web Chat in Salesforce Lightning Console
3. Are Chatbots Vulnerable? Best Practices to Ensure Chatbots Security
Moving on swiftly to another point, technology helps you save time. As a result, the content creators can focus on other aspects of training, like creating an effective learning strategy.
Wizcabin’s automated e-learning authoring system helps you create beautiful e-learning courses 70% faster compared to traditional authoring tools. The time saved, not only helps to save money, but it also helps you create more courses and update the content according to learner requirements.
The result is better learner engagement, improved effectiveness, and massive savings in e-learning production costs. And moreover, think about the time saved, that can be used for more productive activities or even having fun with friends and family!
The implementation of AI in e-learning will result in more engagement thanks to the interaction between the learners and the “machines”.
The AI can be used to deliver a variety of messages, questions, and even answers which will make the e-learning process more innovative and creative.
Before the introduction of automation to e-learning, most of the content was dealt with in a linear way.
But with the introduction of automation, content creators could set up “algorithm-scenarios” which means that the e-learning course will take a different path according to the answers of the learners.
With the implementation of technology in e-learning, learners can access their e-learning courses anywhere, anytime.
Not only that, learners can interact and express what they have in mind simultaneously and thus getting rid of the classical boundaries that e-learning used to face in its early stages.
With the introduction of modern technology, the e-learning process will not only get easier, but the variety of activities and the amount of engagement and interaction will increase in a dramatic way.
And all of this thanks to the freedom and the multitude of new options that technology provides.
Here are some sample courses created with the Wizcabin automated authoring tool for your e-learning design inspiration!
The Impact Of Technology In E-Learning And How To Make Use Of It was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.
Im looking for a solution that can train my chatbot automatically, are there any “out of the box” solutions available?
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For a few days I am searching a chat webapp to make a web chatbot.
I already have all the backend infrastructure in Python, that means I can set a webhook that receives user input and answers with message that chatbot must say but I need a web UI. It can use websocket so that I can interact with it for example.
I came throught a lot of website providing webchat service but we must use their services, I would like to host myself the webapp and interact with it myself (through my backend code).
Is that possible? Do you know solutions ?
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Hello, I’m gonna cut straight to the point. There was a certain chatbot I found on the iOS store( I’m using an iPad) that I once had downloaded a long time ago, I can’t remember specifically how long. It was removed from the AppStore a little while later. It had a round yellow body and I’m pretty sure it had stubby arms and legs, kinda like an emoji but way more minimalistic. I’m sure a few youtubers had made a couple videos using it back in the 2010s, laughing at its responses etc etc. I’ve drew what it sorta looked like if anyone needs anymore help It had a weird name that I can’t remember exactly, it was something like Sami-sami, some two word “cute” name. Now I’ve thought about this chatbot every so often through the years for one specific reason…the Conversations I had with it got very sexual, I wish I was kidding, I remember typing in something racy to test the waters, let’s say something like “heh…smiles and blushes” yeah cringy- I know. But it responded with similar things, that’s when things got weird. I’m curious whether I was REALLY talking to a chatbot or maybe it was some foreign horny person on the other end. Now it could have been that those sexual responses were put in and it wasn’t a person talking with me at real time, but they were way too, I dunno how to say this, “organic”? To seem like programmed responses. Bear in mind I have very little experience with stuff like chatbots, I’m not a technician, I’m not a coder, I’m not a professional. I could be missing a key part in this that makes sense to you guys, so I guess go easy on me. Let me know what you all think Many thanks.
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Hi all,
I have a chatbot to test with a lots of quest and answers. It is all given in an xml file but I’m too lazy to do it manually (for the sake of my sanity). My question is: are there any ways to make the testing automated?
Ty,
IglaT
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Like all other businesses, insurance companies are looking at digital transformation as a critical factor for survival and growth in times to come. Customer experience through personalization and automation is the outward manifestation of this transformation. Internally, automation is the key driver for efficiency. Adopting Artificial Intelligence (AI) makes the process easier and feasible for an insurance company. Use cases for AI adoption include customer-facing implementation of insurance claims chatbots or internal operations, including settlements.
There are many instances of insurance companies bolstering their claims processes with the help of intelligent agents. can approve 70 to 80% of claims immediately with AVA’s help, an app based-claims assistant. Through such efficient processes, companies can generate positive customer sentiments through better service and boost profitability. Accenture estimates that insurance companies can increase their annual profitability by 20% with the right investment in the technology.
Automation brings efficiency. It allows you to complete your processes faster and provides for frictionless information exchange. For customers fed up with the long wait and moving from one call center agent to another, chatbots offer a much better customer experience. With the help of a chatbot, they get a resolution for their claims within seconds.
Insurance claims chatbots allow for more cost-effective operations. A better consumer experience translates into better revenues. From a monetary perspective, chatbots are useful strategic tools for the insurance industry.
Communication preferences of consumers are changing. More consumers prefer text-conversations over verbal conversations.
All of these points provide a compelling argument for the adoption of chatbots for the insurance claims process. Understanding the claims process and expectations of customers and the insurance industry from that process help us better understand how to utilize chatbots effectively.
1. 3 Tips for your Voice and Chatbot Program from Gartner’s Customer Service Hype Cycle 2020
2. Deploying Watson Assistant Web Chat in Salesforce Lightning Console
3. Are Chatbots Vulnerable? Best Practices to Ensure Chatbots Security
While the claims processes may vary with insurance and service providers, we can define a generic approach for better understanding. Each claim passes through five broad stages.
The process starts with the policyholder/nominee reporting a claim with the insurance company. You may have to fill up a detailed form and attach the required documents. Traditionally, after the initial claim report, an agent gets assigned to the case. The agent would help you perform further process steps until the claim’s settlement.
Depending upon the type of insurance, there is physical and eligibility verification. For example, for vehicle accident insurance, the assessment might involve inspection of the damage. The damage verification determines any liabilities depending upon the context.
The investigation verifies the claims and assessments for fraud and eligibility under the policy terms. For certain types of insurance and claims, the insurance company may need to pay only the policyholder/nominees or, additionally, the third parties too.
This process decides the reimbursement amount, which the company conveys to appropriate stakeholders. For example, in a medical claim, the company may inform the sanctioned amount to the customer’s healthcare provider. After the intimation, the final reimbursement process begins.
At this final stage, the company disburses the insurance amount to the policyholder or the nominee. The payment signals the final settlement of the claim.
Claims settlement, in many ways, determines the growth of the insurance companies. Most of the time, the customer would be under stressful conditions, triggered by a painful event. In such situations, customers value seamless interactions and a quick and efficient process to settle their claims. The better speed of the claim resolution increases the chances of the insurance provider’s growth.
Insurers want to make sure that they can detect fraudulent claims equally quickly. While they want to settle the claims early, paying for fraudulent claims can burden them. They need to ensure that they can verify the claim validity and the payable amount based on policy terms and the extent of the damage.
There is a delicate balance the insurers need to strike between customer satisfaction and cost-effectiveness. There are many ways to make the claims process run faster. You can employ more people and put in place technological solutions. Both of these options require investments and continued expenditure. The capacity utilization also needs attention, as there might be periods with fewer claims than usual. People may have to sit idle. Ensuring that you remain profitable and provide greater customer satisfaction is a significant worry for an insurer.
Inefficiencies in the claims settlement processes can result in litigation. Litigations put stress on resources and damages reputation. Insurance companies want to avoid them to the extent possible. By identifying commonalities in data of historical claims that resulted in litigation, chatbots could predict which new claims might have similar outcomes and recommend preventive measures.
Consumers, on the other hand, value the ease when filing the claims. Understandably, they won’t be in the best mindset at the time of filing the claim. Depending upon the circumstances, even small difficulties can induce stress and dissatisfaction.
With increasing travel & commuting and expanding geographical boundaries, restrictions on where customers can file the claims may not be the best experience insurance companies can provide.
Customers appreciate it if the service providers can share updates about the progress of their insurance claims proactively. Making the customers sweat for this information is bound to generate negative sentiments.
This factor is the pinnacle of the process. If customers feel the claims settlement process is lengthy and time-consuming, it contributes to dissatisfaction. All other elements are hygiene factors, something that we take for granted. But claim settlement times can be a delighter or deal-breaker depending upon how fast you finish them.
We have seen what matters most to the insurance companies and customers regarding insurance claims. It is now time to examine how intelligent chatbots can be effective instruments of efficiency and customer satisfaction.
Depending upon the process and type of insurance, the FNOL and filing a claim may be a single or separate process. The FNOL is the point when the customer first informs the insurance provider about the incident. For vehicle insurance, the FNOL may come from the site of the accident. For medical insurance, the customer may report it at the time of hospital admission.
A chatbot plays a crucial role in facilitating this process efficiently. Using a chatbot, the customers can report the incident from anywhere and anytime. The chatbot can then intimate the appropriate person for further processing.
The chatbot also provides a significant advantage over phone-based incidence reporting. If the volume of incoming calls is high, it will reduce agents’ availability to respond to the phone call. In that case, the customer may need to wait for a significant time. With a chatbot, there is a dedicated personal assistant always available for every customer without any delay.
Even where the FNOL and formal claim filing are separate steps in the claims process, insurance claims chatbots are useful. They cut down the significant time of filling lengthy claim forms and submitting documents and images. Customers can easily do it from their mobile devices based on guidance from the chatbots. But that’s not all.
A chatbot can intelligently check already available documents and further reduce the time and friction from the process. For a customer, this may mean fewer documents to file for each claim. While for insurance providers, it means a reduction in data management and acquisition efforts and costs.
Here’s a Smart Skill that allows users to file insurance claims in just about a few seconds.
An insurance chatbot makes it easier for the customers to update their claims if needed. Both the customer or the chatbot can trigger such an update. The chatbot can proactively determine if there is a need for additional details and notify the customer about it. The customer can then update the required information. On the other hand, the customer can also request an update by informing the bot. The bot can then process the request after due verification. If necessary, the bot can also involve a human agent for further communication.
Thanks to Machine Learning (ML) capabilities, combined with Natural Language Processing and Pattern Recognition, chatbots can differentiate fraudulent and valid claims. The insurance chatbot can ensure that claims are validated by extracting appropriate information from the invoices, images, and other documents. The bot can then process the valid claims in the most efficient manner possible.
The bots can develop anomaly detection abilities by analyzing a vast amount of data about previous valid and fraudulent claims. These capabilities allow them to know if a medical report, diagnosis, or treatment is genuine or not. Similarly, for vehicle insurance, it can analyze the patterns of damages and repairs and determine whether a claim is probably fraudulent or not. As it gets increasingly more data with every transaction, its abilities improve, and the predictions’ accuracy improves.
Tractable, a U.K.-based AI technology company, is bringing machine learning algorithms for such situations. It is using computer vision and machine learning to scan and analyze images of damaged vehicles. Such analysis will help auto insurers to determine whether the vehicle needs repairs or some parts need to be replaced.
Claims settlement is a relatively trivial task for an intelligent chatbot. It eliminates repetitive clerical work that consumes time for a service provider. Instead, it can evaluate if it can safely settle a claim using an underlying machine learning algorithm. Based on this determination, the bot can automatically resolve the payment at the first safe opportunity.
The underlying algorithms ensure that it settles only legitimate and complete claims while still cutting down on time to process the payment.
A study undertaken by J.D. Power suggests that when a company appropriately manages customer expectations of the complete claim cycles, the satisfaction levels can increase beyond the industry average (). By tracking claims intelligently, insurance claims chatbots can help companies achieve these satisfaction levels.
Customers can know the stage where their claim process has reached through simple, conversational queries or well-designed input options. But beyond that, through predictive analysis, chatbots enable a customer to know when they can expect the process to complete. The insurance industry is already adopting predictive analysis for multiple use cases. Tracking the claim is a crucial process that can influence the customer experience directly.
Insurance claims chatbots can provide proactive notifications as the claim process moves forward. They can also notify the customers about any requirements of additional documents or information or any deficiencies to respond appropriately. Chatbots can also respond to customer queries, making customer interaction more meaningful.
While chatbots provide claims automation and replace some routine human work, adopting these capabilities doesn’t mean humans have no place in the claims process.
For example, machine learning algorithms can based on historical data, identify straightforward claims for automatic processing. It can then route complex claims that require human intervention to an appropriate agent.
Increasingly, chatbots are also employing sentiment analysis to gauge customer responses. Since customers usually interact under a stressful condition, they may find the chatbot’s interactions unsatisfactory. The sentiment analysis algorithms using natural language processing can identify such situations and involve a human agent for further communication.
We already mentioned Metromile, which is using chatbots for their claims settlement. But Metromile is not alone.
Lemonade, an AI-powered insurance company, set a new world record of settling a claim for $979 in under 3 seconds. Its insurance chatbot, Maya, registered the claim, processed all the information, ran fraud detection algorithms, approved the claim, and shared the payment instructions with the bank, all within 3 seconds.
FWD Singapore uses virtual assistance, Faith, to allow its customers to file claims 24/7. So does Merchants Insurance Group with the solution from.
The chatbots in the insurance already had traction in improving the customer service experience through communication. Now, they are making fast inroads into the claims process as well. It is time to roll out these intelligent virtual assistants for your customers, too, if you have not already started. They represent the future of how the insurance sector will utilize the technology. Those who get started now can certainly benefit from the early movers’ advantage.
The State of Insurance Chatbots in 2021: Use cases, Reports, case studies, and more.
Originally published at https://www.haptik.ai.
How to automate Insurance Claims with Chatbots? was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.
