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Gone are the days of the personal insurance agent. Insurance policies are sold online, and insurance companies must compete on price and conditions. The old ‘trusted advisor’ image has largely disappeared, especially when it comes to simpler insurance products like travel insurance.
At the same time, the insurance industry is under more pressure than ever before. This is driven by several factors, including the increasing impact of technology and the lower barriers for entrants from other sectors. EY (2018)1 state that “Technology is changing the nature of risk and is enabling new products, services and channels.”
The Power of Conversational AI
What if we could combine the ease of use and process efficiency of online insurance sales with tailor-made user advice that new channels provide? This is where Conversational AI comes into play, as it allows for personalization across different channels while, at the same time, allowing for far-reaching process automation by directly connecting to back-end systems. There are two aspects of Conversational AI that allow for this approach:
“Be available at the right time, on the right channel”
According to Georgian Partners (2018)², most users spend 50 percent of their time using just one mobile app. This typically is a messaging app, like WhatsApp, WeChat, Facebook Messenger or the device’s native messaging client. In fact, 50% of the all-time most popular apps are messaging apps. Next to that, mobile app usage is declining 20 percent year-on-year. This shows that users want to be able to interact in a “conversational manner”.
Brands should take this into account. Service-oriented firms can create real differentiation if they are able to engage in meaningful interactions with their customers. The channel approach that works best here is the so called “opti-channel” experience, which essentially states that, unlike “omni-channel”, it is not about being on every channel. Instead, brands should focus on being available at the right channel at the right time. Mastercard drives this point home in their newsroom article on Conversational Commerce (2018)3, by stating: “Optimizing the channel of communication to fit the context of the interaction, and ensuring a smooth handover, is crucial.”
If we take this one step further, it means that a customer might want to interact over a messaging app while on-the-move, but switch instead to an Alexa voice device after arriving home. A Conversational AI Platform like Cognigy.AI ensures that the conversational context and user data is maintained across these channels, allowing for a consistent experience. The same applies the next time a customer calls the insurer’s contact center. By seamlessly integrating with contact center systems like Twilio and Genesys, Cognigy.AI allows for conversational interactions over these channels as well. When we involve IoT, this concept makes even more sense; Afterall, who would switch to a mobile app to order products, if the fridge itself has a conversational interface? The same goes for other devices with voice capabilities, like any modern car.
“Utilize conversational AI to bond with the customer”
Being available on the right channel at the right time, however, is not enough. In his famous book “Integrated Marketing Communications”, Don Schulz (1993) states that all companies can in principle be copied, yet the one thing that stays unique is the way they communicate with their customers. The relevance of the interaction is incredibly important, as no one just wants to have a conversation for the sake of having one. Bots are increasingly expected to be able to deliver on a certain promise, namely that they can help the user along. The best way to do this is by knowing “who” the user is.
Especially in the insurance industry, which largely revolves around trust, it is incredibly important to be able to offer some form of personal advice. A conversational AI in the form of a virtual assistant might get to know the user – and vice versa. This does not only solidify brand-loyalty, it also allows for unique selling capabilities.
A customer might, for example, have ordered travel insurance by interacting with a conversational AI in the form of a virtual assistant. Based on the customer’s previous travel destinations, the virtual assistant might ask something about the purpose of the customer’s visit to try to upsell an additional service. To top this off, the next time the customer interacts with the assistant, it can ask how the trip was, which again strengthens the bond and therefore brand-loyalty. This allows for a loyalty mechanism that no loyalty card program can compete with - personal loyalty.
In more rational terms, this is a mini-ecosystem in the same way someone might have all her products within the Apple eco-system. This leads to a situation where a customer might opt for a given insurance because the insurance company’s virtual assistant knows exactly what the customer is looking for. In the customer’s experience this translates into: “My assistant knows me so well!”. In our case, this is realized by building upon existing customer data that the virtual assistant can utilize during the conversation.
In technical terms, this effect is realized by using context-driven conversational AI. In the travel insurance demo (see below), the assistant deliberately asks for the user’s destination, as it is designed to make the onboarding as smooth as possible and to get to know a user. It is then able to draw from this context on the fly, by using it in its utterances. It also realizes when the topic changed to “travel insurance”, reacting to a user from within this intent. Lastly, it tries to upsell a travel insurance offer, which has a high chance of succeeding because the virtual assistant acts as a trusted advisor.
Let’s be honest: aren’t we all longing for the days when we could share the excitement for an upcoming trip with a personal representative of a company? Thanks to Conversational AI, those days are back, available at any channel at the time you, as a customer, desire.
Curious as to what Cognigy.AI can do for your company? Schedule a demo session so we can discuss your case.
1. EY - Global insurance trends analysis 2018
2. Georgian Partners - An Overview of Conversational AI
3. MasterCard - Is anybody there? Giving Conversational Commerce a voice
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