Email Support: The Pros and Cons of AI Customer Service Tools (Updated July 2021)

Written by Can Ozdoruk  on   Jul 25, 2021

Customers today demand more. To meet expectations for convenience, companies need to offer omnichannel programs and email support system solutions. While channels like Twitter, Instagram, Facebook Messenger and WeChat gain prominence, email support will dominate as the digital channel of choice for customer service in the foreseeable future.

According to Hubspot4, 62% of customers want to communicate with companies via email for customer service. This compares to 48% who want to use the phone, 42% who like live chat, and 36% who want “Contact Us” forms. An aside: the best chatbots can work on email (as opposed to just chat and social channels).

Consumers prefer to communicate with customer service 47% more often over email compared to live chat.

An email support system is superior in many ways. It’s not asynchronous and therefore is inherently more convenient. A person can send an email to a company and walk away, checking for a response when it’s convenient for them. A person is not committed to engaging in a real-time conversation which can get interrupted or lost due to connectivity issues or by simply clicking to a new Web page. Email also keeps a record. Emails can be stored and accessed later. On a phone call or Webchat interaction, no record exists.


Learn more about companies using chatbots for customer service.


Why Aren’t Traditional Email Support Systems Meeting Expectations?

Email is the most used digital customer service channel according to Forrester 1, but 62% of companies do not respond to customer support emails2. This presents a real risk to customer loyalty and satisfaction.

For the companies that do respond by email, they are not doing so quickly enough. Customers expect businesses to respond to their emails within an hour3. The average response time to a customer service request is 12 hours and 10 minutes2. Furthermore, only 20% of companies are able to completely answer questions on the first reply2.

From these numbers, it’s clear that email customer support needs to be improved. Customers want resolutions in their inbox. Making this worse, customer expectations for service in every channel are increasing; they expect faster response times and better responses. Companies like Amazon and Zappos have set the benchmarks for customer service, and people now demand quick, convenient support from every company they do business with.

“The handful of companies that respond promptly and accurately to customer emails increase trust in their brand, bolster customer satisfaction, and boost sales both online and offline.”

How Can Conversational AI Impact Your CSAT?

When launching an AI-powered Agent, email is often forgotten. Most companies start with social channels or live chat. Email, however, offers incredible benefits in terms of training an AI and delivering high customer satisfaction (CSAT).

AI Agents managing email conversations need to be more advanced than those deployed on a website or social channels. This is because email messages are typically longer and contain multiple intents. It’s important that you leverage a conversational AI platform that has the ability to decipher the intent from longer messages within the right context to be able to accurately resolve a ticket and reduce frustration.

Conversational chatbot AI can eventually manage over 50% of emails without human intervention, according to what we see from our customers. This offers the convenience and immediacy customers want on their preferred channel which keeps CSAT high.


Discover the key questions to ask when scheduling a chatbot demo.


Should You Launch a Virtual Agent on Your Customer Support Email?

Training an AI is initially done using historic data.

When you’re training an AI, it’s important to not focus on how you think people ask a question, i.e., the FAQs listed on your online help center or knowledge base, but how people are actually asking questions. In one example, Comcast found that their customers ask the simple question “I want to see my bill” in 7,500 unique word and phrase combinations.

By training with historic data, you’re able to set the AI Agent up for success by giving it knowledge and confidence to correctly classify intents across a larger number of utterances. The more data that’s available, the more accurate an AI will be. Because email has been used by companies for much longer than other channels, companies tend to have a much larger dataset.

Email is the most desired and used channel by customer service organizations and their customers.

When providing and omnichannel experience, it’s important to note that your customers ask things differently based on the channel in which they are seeking support. Chat is usually succinct. An email might contain multiple questions and additional detail. In a nutshell, people will ask things differently on email than other channels. So using your troves of historic email data will be most useful if you’re using it to train an email-based Conversational AI.

How Can Email Impact Reinforcement Learning?

People don’t expect an answer immediately on email like they do on chat or voice. This allows companies to start leveraging an AI Agent “behind the scenes” and conduct reinforcement learning. In this type of training, an AI Agent has no direct interaction with the customer. Instead, an AI reviews every incoming email and suggests a response to a human agent. The AI learns how the human agent responds in order to build confidence over time. Because the expectation for instantaneous support does not exist with an email support system, you have the leeway to train with real interactions without disrupting the customer experience.

Excited to deploy AI for your email? We can kick start improving your email channel by free analysis of AI fit in your organization. Just ask us how.

References 

11 Insurance Chatbot Use Cases (and Why Providers Need AI Now)

Written by Emily Cummins  on   Jul 16, 2021

Chatbots are providing a new avenue of innovation for the insurance industry. The use cases for an insurance chatbot are beneficial for both insurance companies and their customers alike. Companies using chatbots for customer service can provide 24/7 access to support, even in the middle of the night. The best AI chatbots can even provide an instant quote and change policy protections without the help of a human agent.

For insurers, chatbots are a scalable solution to quality support. In an industry where customer lifetime value is so high, implementing an insurance chatbot can pay massive dividends that will satisfy the customers, C-suite, and investors. When companies are able to offer a streamlined solution, it can also lead to a better price for the customer. We’ll cover all that and more later on.

A Brief History of Insurance as a Service

The insurance industry is rapidly evolving. For centuries, the industry was able to rest on its laurels because information was inaccessible. Customers were operating in the dark with little insight into competitive policies and coverage. Insurance was often mandatory or a necessity for financial security. For decades, there was not a need for insurance providers to prioritize the customer experience because – although people lacked trust and affinity for their providers –  turnover was low. The industry, though, looks a lot different today. 

Why Providers Should Evaluate an Insurance Chatbot with AI for their Business

Consumers are now in control. Information is readily accessible at their fingertips. Policyholders are empowered to look at reviews, see coverage options and pricing, and compare offerings from a growing set of established auto, health, car and life insurance providers as well as digital disruptors. 

To thrive in this new environment, providers need to become truly customer-centric and rise to meet the expectations of the modern policyholder. People today expect effortless, convenient and omnichannel interactions. If expectations are not met, consumers are quick to switch to a competitor. With pricing, policies and coverage so similar, a key way for insurance providers to differentiate is on customer experience. Increasingly, insurance providers are investing in modern conversational artificial intelligence (AI) to scale personalized, effortless and proactive customer experiences.


Fintech companies are only getting half of the Customer Experience right.
Learn how AI is rewriting the rules of Fintech CX.


The CX woes for insurance providers and the threat of churn 

Insurance is complex. Purchasing a policy can incorporate many different factors; and filling a claim involves a complex ecosystem of providers, adjusters, agents and inspectors. Getting clarity and the support needed along the customer journey is often difficult. 

There’s also widespread mistrust amongst policyholders, which is influencing retention: 42% of customers don’t fully trust their insurer1 and only 29% of policyholders are satisfied with their current providers2. According to a 2020 survey, “50% of consumers question their medical and life insurance policies3.”

Keeping existing customers happy is more important than ever as the costs associated with customer acquisition have never been higher: 15.8% of gross written premium (GWP) in 2018, 16.6% in 2020, and an expected 17.9% in 20221.  In just one example of the high acquisition costs for insurers, one study shows that insurance-related keywords for Google and Bing ads are among the most expensive at 50 or more per click4

The Insurance Industry’s Investment in CX is on the Rise 

Insurance providers recognize the need for CX investments: while 60% of insurance executives agree their organization lacks in CX strategy, 85% are deploying CX to at least a moderate extent. In fact, investment in customer experience tools is rapidly rising from “1.1% of GWP in 2018 to 1.5% of GWP in 2022, an increase of 36%1.” And when we drill down into the specific areas of investment, two-thirds are significantly focusing on customer service, claims, and the phases of customer onboarding1.  This is good because 61% of insurance consumers in the United Kingdom, 76 percent in Germany and 79 percent in Spain say their insurer choice is influenced by the carrier’s claims handling and customer service quality5

Service Chatbots Powering Customer Self-Service in the Insurance Industry 

A big part of customer service CX investment is around automation and leveraging AI to automatically resolve inbound tickets and proactively reach out at key parts along the customer journey. Customer service chatbots can be deployed across key digital channels, including: email, Web chat, messaging, SMS, social and voice channels. When providers rely solely on human agent teams, it’s difficult to provide the effortless and immediate resolutions that people expect. AI can help automate resolutions to repeatable tickets, assist agents by gathering information from customers and back-end systems before handing off to an agent, and even drafting responses for an agent to review. 


Discover the key questions to ask when scheduling a chatbot demo.


Which Companies Use Insurance Chatbots?

In 2017, Aflac aired the first ever commercial to feature an AI chatbot. They were the first major insurance company on record to have a customer service chatbot on their website. Since then, advancements in artificial intelligence have made chatbots significantly more powerful. As a result many insurance companies have invested in AI for a better customer experience. Watch Aflac’s insurance chatbot commercial below:

As AI advances, it will be able to take on a more significant role within the support team. Today, there are a few key use cases that insurance carriers should leverage AI.


Want to hear an honest conversation about how customer service can differentiate your insurance company?
Learn why the best customer service is when you don’t need it.


Top 11 Insurance Chatbot Use Cases

1. Immediate, personalized quotes

When a prospective customer is looking for a quote, a chatbot can gather key information about vehicles, health, property, etc., to provide a personalized quote in seconds. Chatbots that leverage Natural Language Understanding (NLU) – instead of rigid decision trees – enable people to ask questions during the information gathering process, a similar experience to engaging with a human agent.

2. Claim filing

When a policyholder needs to submit a claim, a chatbot can collect the right data to process the claim. This can include probing for the required documents and –  depending on the type of insurance or claim –  request images or video. By leveraging AI-powered image recognition technology, chatbots can also ask for new pictures or files if a file does not meet requirements. For example, an American car insurance company, Metromile, was able to approve 70-80% of claims immediately after launching its chatbot.

3. Claim status updates

As soon as there is a change in the status of a claim, chatbots can proactively reach out to policyholders to keep them informed throughout the process. This reduces the time that a customer has to contact a customer first, and makes a dramatic impact on the overall customer experience. 

4. Tailored coverage advice and education

If a policyholder reaches out with questions related to coverage and specifics of their policy, a chatbot can provide updates in seconds. A chatbot can also answer general questions related to a provider’s products and services. At key points along the customer journey, a chatbot can also preemptively reach out with key information based on patterns of when questions arise based on products used and profile attributes. 

5. Fraud prevention

In the US, property-casualty fraud accounts for $30 billion a year6.  AI-powered chatbots can flag potential fraud, probe the customer for additional proof or documentation, and escalate immediately to the right manager. This fraud prevention can result in significant savings for providers.

6. Personalizing responses

88% of insurance customers demand more personalization from providers7. AI can help agents respond to customers faster with tailored responses by curating data from back-end systems on agents’ behalf and even drafting personalized responses.

7. Instant responses to FAQs

AI-powered chatbots can instantly respond to everyday questions, including: account management, cancellations, discounts, cards and documentation, and billing / payment. By automating these highly-repeatable queries, agents can focus on more complex issues.

8. Ticket triage AI

In more complex cases, an AI chatbot can act as the first line of defense to gather information from a policyholder before passing it off to an agent. This can help agents work faster while decreasing resolution time.

9. Cross-selling and up-selling

AI-powered recommendation engines can identify the right services and products for agents to cross or up-sell, and the exact moment during a conversation or the customer journey that a policyholder is likely to purchase.

10. Proactive care

AI-powered chatbots can act on signals from back-end systems as well as contextual data in order to preemptively intervene before a problem becomes a bigger issue or a policyholder has to reach out to a company themselves. For instance, after a big storm, a property insurer can preemptively reach out with steps on filing a claim and all necessary information and documents.

11. Broker communication

Beyond customer-facing chatbots, insurance providers can deploy chatbots to manage broker relationships. Chatbots can answer queries, especially if they are facing complex client inquiries or need an update on the status of an application.

The payoff of good Customer Experience in Insurance is more than happy customers 

Making the right investments in CX improvements can dramatically impact revenue. McKinsey found that auto insurers that provide excellent experiences have seen 2-4X more growth in new business and 30% higher profits than other firms8. Why? Satisfied customers are 80% more likely to renew their policies. In even more proof, 90% of customers who feel appreciated and 69% of those who feel valued will increase their spending with an insurance company9

Insurance is a lot like the travel industry. Rooms and airplane seats are remarkably similar, as with many insurance policies. There is little differentiation between coverage, pricing and policies. Customer service is now a core differentiator that providers need to leverage in order to build long-term relationships and deepend revenue. With the lifetime value of policyholders so high, and acquisition costs also sky-high, keeping current customers happy with stellar customer service is an easy way to reduce churn.  

For more related information, visit: SMS Customer Service and SMS Chatbot Strategies.

Find out what your ROI will be if you build an AI chatbot. Try our free chatbot ROI calculator today.

References

  1. https://www.ibm.com/downloads/cas/AAV81JLZ
  2. https://ins.accenture.com/ins-capturing-customer-of-tomorrow-rp.html
  3. https://liveperson.docsend.com/view/idj9hf42866jwqcc 
  4. https://www.wordstream.com/blog/ws/2015/05/21/how-much-does-adwords-cost
  5. https://insuranceblog.accenture.com/customers-experience-demands-illustrate-the-importance-of-insurers-going-digital-now
  6. https://insurancefraud.org/fraud-stats/
  7. https://insuranceblog.accenture.com/customers-experience-demands-illustrate-the-importance-of-insurers-going-digital-now
  8. https://www.mckinsey.com/industries/financial-services/our-insights/the-growth-engine-superior-customer-experience-in-insurance# 
  9. https://www.quadient.com/blog/why-insurance-companies-need-mind-gaps-when-it-comes-customer-experience