Insurance Chatbot

Success KitHow to transform your digital customer

experience

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ContentsDedication

Welcome

Part 1: An insurance and chatbot love story

Part 2: The 3 pillars of an insurance chatbot

Part 3: The key to successful collaboration

Acknowledgements

Our story

Spixii, the beginnings

Ready to take the next step?

Works cited

Insurance Chatbot Success Kit

Emma Pegg

This edition first published January 2017.

We are Spixii, a company incorporated in England and Wales (No. 10362895).

For details on our technology and information about how to reuse the material in this paper, please get in touch at team@spixii.ai.

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Dedicated to the individuals looking to

transform the insurance industry.

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WelcomeWalk down Leadenhall Street in London and you'll soon see the Lloyd's building. Towering amidst the metal London skyline, tubes and pipes protrude like bowels and guts from its exterior. This is the 'inside-out' building, where the staircases, lifts and water pipes have all been moved to the outside to leave the inside streamlined.

The insurance industry is ready for transformation. Like the Lloyd's building, it's time to embrace change and incorporate the old with the new. This insurance chatbot success kit will show you how. This builds on 2 years of experience working with global insurers to build chatbots for the insurance industry. Our vision and hope? For companies to help more people get better protected through first- class customer experience. We want to see a world that is 100% insured.

The ideas in this kit are for innovators: those looking to collaborate with startups to improve efficiency, get smarter analytics and improve customer service. They're not for people who simply want to cut operational costs while ignoring their customers' needs. Before you even begin to introduce innovation, you must be confident it's the way forward and it'll genuinely serve your customers. For the rest of the kit, that'll be assumed to be a given.

Having chatbot technology is a way for customers to interact with you like they would message their friends or family. It provides more data on how they like to behave, more than you could ever get from a form. You can see where and if they drop out, which questions they may struggle with, and how you can optimise the conversation to seamlessly guide them from A to B.

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By the end of this kit, you'll have a clearer idea of how to develop chatbots that fit your regulation and legal requirements while also providing a fantastic customer service. A part of innovation is iterative; stick with it because the potential is extraordinary. Once you have a chatbot plugged into your system, you'll be able to reduce operational costs, personalise conversation with your customers and enhance customer loyalty.

Customer service teams will not have to answer the same question over and over again; you'll automate those questions and leave the complex queries to specially trained people.

This kit isn't just about the pillars of a chatbot and methods to get one off the ground. It's also about digging into the problems the industry's facing, and how startups and insurance companies can collaborate. This philosophy of collaboration underpins everything.

Together, let's help more people get better protected.

Emma Pegg Spixiifier

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An insurance chatbot love story

Part 1

Here's how the two are a match made in heaven.

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The world of insurance

Insurance is one of the oldest industries in the world. For instance, property insurance in the UK is believed to have its roots in the Great Fire of London in 1666. It's estimated that around 13,000 homes within the city wall burnt to the ground, leaving 70,000 of 80,000 people homeless.

Around 20 years later, Edward Lloyd opened a coffee house on Tower Street. This developed into a popular haunt for shipowners, merchants and captains, who shared news on marine insurance. It would later grow into the Lloyd's of London.

Allianz points out that "insurance has changed little since".

You can still see the loss book on the first floor of the Lloyd's building, where significant losses were scratched by quill for 300 years. Meanwhile, on the 11th floor, there is an 18-century dining room on display. It was taken piece by piece from the previous Lloyd's building across the street. 

While many industries invested in their customer service early on, many insurers are still lagging behind, held back by outdated legacy systems that require increased maintenance and struggle to make sense of new data.

History

Challenges

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Yet, we're no longer captains exchanging money on a promise to protect our ships and likelihoods. Now, we can reach our laptops and mobiles, fill out forms and receive lengthy terms and conditions.

To file a claim, we call a phone number, wait on hold and get in touch with a customer service representative. They might know the answer to our question or may need more paperwork that we don't have available.

The process is often time-consuming, frustrating and thankless.

What's a chatbot?

Essentially, a chatbot is a robot in a chat: a piece of software plugged into a messaging interface like Facebook Messenger, Whatsapp or WeChat. It allows customers to interact with your company like they would a friend or family member. It's available 24/7 and fully automated.

Although built on principles dating back to 1966 with the birth of Eliza, chatbots soared in popularity in 2016. Companies such as Domino© rolled out AI bots promising "to make ordering easier than ever".

In 2017, customer appetite for a quick and easy service showed no sign of declining. The popularity of apps declined while the demand for on-demand, easily accessible information remained as strong as ever.

The rise of the chatbot

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The insurance industry is renowned for being dry and disengaging. Yet, insurers provide a product that helps better protect people. In developing countries without such an ecosystem of insurers and reinsurers, the personal consequences of not being insured can be devastating. Events such as the hurricane season in 2017 highlighted the importance of making insurance accessible to all.

Despite the social and economic value of insurance, buying it is often difficult and time-consuming. Customers might receive anything from a 20-50 page document laying out the terms and conditions. As the product is complex, customers must legally have this information to hand. Yet, the majority will skim-read it at best. Some may misunderstand it and others might avoid it altogether.

However, this document becomes vital if a customer registers a claim. If they didn't read a note in the document that excluded them from cover, they might be disappointed at their time of need, feel like they had been misled or wasted their time and money for nothing. The trust is broken.

For insurance to work, the relationship between insurers and their customers must be fixed. Insurance products must be sold through personal engagement, with technology designed around the customer.

Innovation is a small piece of the puzzle, yet as we usher in a new era of digital simplicity and personalisation, insurers cannot risk being left behind. The time to invest in digital customer experience is now.

Relevance to the industry

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At first glance, a chatbot is a straightforward piece of technology that reduces operational costs.

The majority of customer service team conversations move through a decision-tree style. Customers are frustrated by the need to repeat information they may have already entered online.

Meanwhile, the customer service industry has one of the highest turnovers of any industry. According to SJS Solutions, it's costing the UK call centre industry as much as £2.3 billion every year. Automating as many calls as possible seems a quick and easy solution to save money.

However, chatbot technology will never be able to replace humans. Particularly in the case of claims, it's expected that many customers will still want to speak to a human being. In this situation, chatbots can provide a phone number immediately or handover to a live avatar. In automating the simple, day-to-day queries, customer service teams have more time to handle complex or sensitive queries.

Jamie Macgregor, Senior Vice President of Celent, believes the future of chatbots lies in personalisation and customer segmentation. For Macgregor, "in any remote transaction not involving a human, chatbot technology must pay attention to cultural and linguistic differences if it will truly replace humans." In this way, it can go beyond the human tendency to mirror another person's style of speaking, accent or colloquialism."

Reducing operational costs

Potential for personalisation

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Let's imagine you have a 21-year-old looking to get a quote estimate for car insurance. They've just passed their driving test and now have the keys to a new car in their hand.

On the right, you have a 65-year-old pensioner. They've stayed with the same insurer for the past twenty years and are now downsizing. They need to update their home insurance policy with the new address.

The chatbot can collect data on each customer group to find out how these two customer groups, on average, like to interact. For example, the chatbot might find that those aged 65 and over prefer a more formal tone of voice, while customers in their twenties use more emojis. 

The chatbot will be able to apply algorithms ('reinforcement learning') to the rich data it collects on each customer group, and over time, learn how to personalise to individuals.

This level of personalisation has already been shown to increase conversion rates. During Spixii market trials, lead capturing increased by up to 5x and sales saw a 30% uplift.

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There will always be a place for humans in insurance. Automating the entire digital customer journey alone will not return trust. Yet, automating part of the journey with customer-centric technology is one step towards what Macgregor describes as an "evolution, not a light-switch moment but a long and hard journey that will take years."

To create an effective chatbot, you need to use emotional intelligence, a deep understanding of human behaviour and experience in the technology.

The second part of the success kit will explore this, plus further best practices.

Relationships with humans

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Spixii's 3 pillar framework

Part 2

Here is how you can accelerate the design of successful chatbot conversation, working alongside

compliance and regulation.

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Pillar 1

What value are you bringing to your customer?

Let's imagine you need to build a chatbot to help people buy travel insurance. In this case, your value lies in the end travel insurance product. So, how can you deliver it most effectively?

To start mapping out your current customer journey, you'll need a desk and post-it notes. Write down each step on separate post-it notes and lay them out. Where does the journey start and where does it end? Consider every possible scenario. This will provide an overview of problems you can turn into opportunities to add value to your services.

Value

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Value, meaning, engagement framework (VME)

First, look at the problems your customers are facing. Then look at how you can solve these problems.

Each use-case will mean something different for your customer, and may vary person to person.

Let's take Sue as an example.

Situation A: Sue is looking to file a claim on life insurance after her husband passes away. The priority is to connect her with a compassionate customer service handler as quickly and easily as possible. The last thing she needs is to search for a phone number online or wait for hours on hold.

Situation B: Sue is moving house and needs to update the home address on her insurance policy. This simple, day-to-day task could be completed in seconds through an online chatbot. Instead of needing to call while at work, she can do it when she gets home at 9:30 pm.

It's important to carefully evaluate the meaning of each interaction when designing your chatbot. In Situation A, the situation will likely be very emotional and need an immediate human switchover. Meanwhile, in Situation B, a simple, seamless service is required to take Sue from A to B.

How do you want your customer to feel? List the emotions. For instance, you could write:

Engagement

Meaning

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Delight. Surprised by the ease and simplicity. Trust. Feel that the insurer is giving you all the information you need to make a decision. Laughter. Perhaps as part of your branding, you would like to create a bot to charm your customer like a charismatic broker.

One of the ways a chatbot can engage a user is through gamification. However, you must apply this with caution. Gamification is used in technology and social media to create addictive habits for the user. For instance, an Instagram user might keep returning to the app to get more likes and follows. Each like, follow and positive interaction is registered as a reward, together with a release of dopamine.

If you're selling a product, gamification is potentially unethical. Yet, if you're looking to encourage good financial habits such as saving money each month, regularly checking a bank balance or checking an insurance cover, it might be useful to get customers better protected.

One example of gamification is PNC's Virtual Wallet, and its 'Punch the Pig' game.

And it worked! One reviewer called it "one of the coolest features ... when I was spending money like crazy, I used to justify things by saying "it's only a dollar, it's only ten dollars". Well, now I do the same thing with saving money! I see the pig and can't help clicking."  

What would your customer users say? The next pillar explores the fundamentals of user testing.

Gamification

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"The only thing more rewarding than saving money is having a little fun doing it. That's the idea with Punch the Pig.

When you're banking online, you just "punch" the piggy bank

and money (the amount of your choice) will transfer from your Spend account to your Growth account. (That "punch' is a

"shake" for smartphone users.)    1

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1 https://www.pnc.com/en/personal-banking/virtual-wallet-overview.html 2 http://www.sooverthis.com/pnc-virtual-wallet-love-of-my-life/

Pillar 2

This is perhaps the most important step of the entire process. It's easy to forget how much work goes into every product behind the scenes.

To make it seamless, you must test every potential outcome thoroughly. Ensure you have as diverse a customer group as possible. To make insurance accessible for everyone, and for a world that's 100% insured, we must recognise the needs of customers vary widely.

Questions to consider:

User testing is an integral step to the Spixii chatbot, which informs the analytics. The analytics dashboard shows you where customers drop out or stop engaging. If you're able to get this information, it is often helpful to see whether this is an issue due to the chatbot itself, or the information being asked. Do they have enough background or context to answer? Is the language unclear?

User testing

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Conversation scripting

How would someone with a visual impairment use the chatbot? Does the language suit a bilingual tester, who speaks English as their second language? If you use colloquialisms, are any culturally sensitive? Does someone with limited digital skills intuitively know where to click to continue the conversation? Instead of relying on gut feeling or instinct, it's key to test with people outside of the insurance industry. You might be surprised what feedback you receive!

Another important feature of usability and customer-centric design is its length. How long is your conversation? If you see a lot of customers dropping out towards the end, try reducing the number of questions. Tools such as the Spixii CXD allow you to visualise your conversation and see where you can simplify or shorten the customer journey.

Signpost your customer throughout. For instance, tell them when they're halfway through or how many questions they have to go. On a form, you can scroll down to see the number of questions. In a human conversation, there may be spoken signposts or visual body cues that build trust. Design your chatbot to mediate between the two.

Dialogue management

Signpost your user

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Matteo Schgor UX and UI designer

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Pillar 3

Once you have optimised your workflow, you can add Natural Language Understanding (NLU).

In chatbots like Replika, an app that "learns from you, gets to know you, and keeps your memories"  using artificial intelligence, NLU is frequently used. This means you can type freely and give detailed answers, just like you would a close friend. The interaction feels personal. Indeed, it may even start to feel like a friendship if used regularly.

However, NLU also makes conversations difficult to audit for compliance, legal or marketing purposes. If the technology makes a mistake and misreads a customer's answer, the chatbot could switch a customer into an inappropriate workflow.

For instance, let's imagine your chatbot is designed to sell life insurance. If the chatbot misinterprets the size of your customer's family, it might switch to a workflow designed to sell life insurance for a large family instead of a small one. The differences would be so subtle, the customer might not realise and buy an ill-suited product.

In this situation, who's liable? The state of today's machine learning can never successfully predict situations with 100% accuracy. This would suggest overfitting: the practice of training on a model of data until it can successfully predict outcomes within that model. However, when presented with a new set of data, it will not be able to predict with the same level of accuracy.

Liability

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Artificial intelligence (AI) and natural language understanding (NLU)

3 https://replika.ai/

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In use-cases where 1% of error is acceptable, NLU can be used. For example, if a webpage receives an average of 60k visitors per month and a third (20k) interact with the chatbot, this 1% would equate to 200 people per month. This means 7 people every day. Here, evaluate whether your business can accept the risk of potentially them. Until NLU is 100% accurate, a chatbot with one-click buttons can be fully audited, thus meeting your legal and regulatory demands.

NLU should be seen beyond being a simple reply to a message. It should fit the context of the conversation.

AI has become a buzzword of the last few years, and not only in the world of fintech and insurtech startups. Indeed, in 2016, Andrew Ng, Stanford professor and former Google scientist, called it "the new electricity" at the WSJD Live Asia conference:

Arguably, one of the challenges with AI is in its 'black-box' tendency and a misunderstanding of its potential. In a recent poll, Spixii asked its Twitter followers what they expected to be the biggest benefit from using AI. The answers?

'Black-box' AI

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"Just as 100 years ago electricity transformed industry after industry - transport, communications, healthcare

- today, we see a surprisingly clear path for AI to transform all of these industries."   

Andrew Ng

43% automated processes 36% increased personalisation  14% more customer insights

4 https://news.stanford.edu/thedish/2017/03/14/andrew-ng-why-ai-is-the-new- electricity/

The application of AI to chatbot technology will certainly enable insurers to optimise their conversation flow and use data to choose the most effective question. With AI, there's no reason why you can't personalise every conversation you have with customers, and continuously iterate based on your customer data (as demonstrated by the value-adding wheel below).

Should we worry about AI and its application to insurance?

It's important to consider that we have already used AI, at least in a rudimental form, for decades. Joel Bassani, Insurance Consulting Manager, explains how AI can be seen in email management.

"For 20 to 25 years, your inbox filters incoming mail by determining whether it's spam or not. This filtering is based on two things: first, the repetition of words that you, or the filter, considers spam. Each time you mark an email as spam, the filter learns which words to look out for," Bassani points out.

Concerns

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"Today's artificial intelligence is a consequence of that technology. You can design more rules and improve them in this decision-tree style automation. You move towards individualisation, and the more individualisation you get, the more data. For insurance companies, this means focusing on precise requests from customers and using deep learning technologies to understand and learn from that content."

Undoubtedly, the application of AI and machine learning is not without its ethical challenges. An innovation of any kind must occur alongside careful discussions on its potential impact on society.

For instance, machine learning might enable a chatbot to personalise a conversation so efficiently, the customer buys a product that they don't need. Similarly, an overreliance on technology risks discriminating against those without digital skills.

The 3 As to consider when considering AI and machine learning?

Having these three things in place means one step towards better protecting customers.

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Accountability  Auditability AI that's transparent

The Key to Successful Collaboration

Part 3

It all starts with a spark. This short sweet guide will help you lay the foundation for a successful strategic

partnership.

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In the last two years, Spixii has seen tremendous growth. From ideas between two training actuaries to a B2B2C insurance proposition and fully fledged technology company, we now have data scientists and developers working across the globe to help insurance companies enhance their digital customer experience.

From the beginning, we have had plenty of successes and failures - and we've celebrated both. Between 2015-16, many insurers were only just putting digital transformation onto the agenda. Innovation and customer-centricity became buzzwords, but the roadmap to achieving real value for the end customer remained unclear.

From our experience, there are three consistent common dominators underpinning every successful partnership.

Firstly, you need a team who have devoted ample time and investment to the project. When designing and building a chatbot solution, you need support from across the organisation, including marketing, compliance, IT and regulation. It's important for everyone to see the value of the technology from the get-go in order to prioritise its development and iteration.

Secondly, a good level of technical understanding goes a long way. With new technology and advanced analytics, the integration stage often needs a close understanding of your APIs, back-end rating engines and data security standards. These entry requirements are necessary upon scoping a project. If straightforward to deliver, they can significantly accelerate a project's delivery.

PartnershipA note from the co-founders on successes and failures

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A focused team

Technical expertise

However, companies are at different stages of awareness of machine learning, chatbot technology and artificial intelligence. Some may have trialled a chatbot before and have a clear idea of their success metrics. Others might be completely new to engaging with their customers through a messaging interface, but curious about the impact on their customers.

When upper management invests into the project, we have seen a huge uplift in pace and efficiency. Innovation cannot happen in a vacuum, nor can it fall on one department within a company. It must be company-wide, with buy-in from the executive team.

In a similar thread, there are endless ways accelerators might vary. We graduated six accelerators and found that the involvement of the executive team transformed the project for both parties.

Bearing this in mind, we hope you find the remainder of the kit helpful. 

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Appropriate sponsorship

Alberto Chierici          Renaud Million      Alberto Pasqualotto CPO and co-

founderCEO and co-

founderCTO and co-

founder

Culture

The cultures of insurance companies and startups are often seen as polar opposites. Yet, they may be closer than you think. Even though Spixii was co-founded by three professionals taking a risk to do what they believe is right, a startup is arguably as aware of risk as an insurance company.

A spark starts between people, not companies. If you are passionate about the power of technology to improve insurance and society, and see how it can benefit your day-to-day life, that's a strong starting-point for introducing innovation to your company.

We believe it's the duty of a startup to help prepare an insurer for future regulatory changes, such as General Data Protection Regulation (GDPR) and the Insurance Distribution Directive (IDD). That's why we designed Spixii's technology to meet all legal and compliance requirements.

One of the ways to imbue your company with agile frameworks and passion for new technology is simple. Bring the startup to you. As Jamie MacGregor points out, "there's a movement in the industry to set up smaller labs, in an effort to break down internal barriers. It shows a marked increase in appetite to try new technology and signal an internal culture drive towards innovation." The next part will tell the story of the Bupa Customer Lab, as told by John Moore.

Start with a spark

Regulation and data privacy

Bring the startup to you

Startup vs. insurer?

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Bupa

"The Customer Lab took about a year working on different parts of the business, taking advice from consultants, talking to startups and looking at other businesses until deciding this is what we wanted to do: a customer-focused change in the company. We knew we couldn't do that alone so we set out to build a community of startups and partners," says John Moore, Head of the Customer Lab.

"Regarding innovation and change, you can't just say, 'I'm going to innovate'. You really must change the way you work, and strive to bring the principles of human-centred design to solve problems. It's about having a safe place in the organisation to see what works and what doesn't."

The Customer Lab was based in Bupa's head offices, where startups were working closely alongside Bupa staff. By the Demo Day, they were all excited by the potential of the technology and its impact on the lives of their customers.

How can the new technology save time and make your employees' lives easier? James Oughton from the Bupa Customer Lab said of Spixii:

The story

A shift in culture

Get everyone excited

Customer Lab

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"The Spixii team made my life easier. The auditable, structured chatbot technology met our compliance and legal

requirements during the trial, and has been straightforward to integrate."

Internal

Although startups and insurance companies are generally expected to operate under different timeframes, it benefits both - and most importantly, the customer - to adopt agile frameworks, in which innovation can be introduced, tested and iterated. Experience shows that it's normal to start a new project with some scepticism on the value it can deliver, yet grow to embrace it as the technology develops. Embracing technological change requires a culture shift across your entire organisation.

So, how do you do it?

If you work with a startup, share what success means for you. What key metrics are you looking for? Sharing your business model and strategy helps the startup prepare for your future accordingly. Clear, transparent communication keep the spark alive in strong partnerships.

Startups place the bar high by shooting hypotheses, expecting most will be invalidated by market research and/or customer insights. They celebrate failures as much as successes and are used to quickly turn ideas into reality. If there's a problem, there's a solution. You can always make change happen.

Adopt an agile framework

Be transparent

Embrace agility

Nurture an internal innovation culture.

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We use the lean startup model, or Rapid Prototype Design (RPD), a methodology designed to deliver results fast. We rapidly build, test and learn prototypes, then iterate based on customer feedback and data. This step cannot be overlooked. To build truly customer-centric technology, it's crucial to listen to customers not just at the end of the development but to embed it within your product roadmap. If you only add user testing at the end, there may be fundamental problems that will delay the overall delivery. Instead, it is far better to bookmark user testing at several points during the development process, even if the product isn't perfect.

Ultimately though, making change happen takes work and resilience. Never lose sight of your mission, the reason why you get out of bed in the morning. For Spixii, that's to help more people get better protected, for a world that's 100% insured.

Lean startup model

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Spixii first took wings in 2012. The three co-founders, Alberto Chierici, Renaud Million and Alberto Pasqualotto, shared a belief in the social and economic value of insurance. Alberto C. and Renaud first met at a tutorial preparing for the actuarial qualification. Renaud was a French engineer by training, while Italian-born Alberto C was a data scientist. Both were insurance professionals in London, frustrated by the way insurance was sold but passionate about its social and economic value.

This value was illustrated when Alberto C delayed buying home insurance for his new flat for three years. Even while working in insurance, he struggled to find a product that was flexible enough. Meanwhile, Renaud's apartment was burgled and wasn't adequately protected to file a claim. Alberto P also found himself unprotected when he returned to his car with its windows smashed in.

Insurance is important to everyone. So let's make it accessible.

In 2015, the co-founders left their offices and talked to people about their insurance stories. Inside, outside, in coffee shop queues, on work commutes - everywhere and anywhere, thousands of light-bulb moments happened across London. People called insurance a nightmare, or they had no idea where to start. 

For many, their first reaction was to text a friend or family member for advice. The idea for Spixii was born: a trusted chatbot that could take people under its wing and guide them through the process. 

Our story

Spixii, the beginnings

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Further readinghttps://futurism.com/images/the-history-of-chatbots-infographic/

https://www.spixii.com/blog/humans-meet-insurance-chatbots

http://www.fsb.org/2017/11/fsb-considers-financial-stability-implications- of-artificial-intelligence-and-machine-learning/

 Works cited"Andrew Ng: AI is the New Electricity." The Wallet Street Journal, Dow Jones & Company, 9 June 2017, www.wsj.com/video/andrew-ng-ai-is- the-new-electricity/56CF4056-4324-4AD2-AD2C-93CD5D32610A.html.

Allianz. “Look out for these new innovations.” The Telegraph, Telegraph Media Group, 6 Oct. 2017, www.telegraph.co.uk/business/risk-insights/biggest-new-innovations- in-insurance/?WT.mc_id=tmg_share_tw.

"The True (And Scary) Cost of Contact Centre Agent Disengagement in the UK." SJS Solutions, 18 Aug. 2017

"PNC Virtual Wallet: Love of My Life." So Over This, 7 June 2016, www.sooverthis.com/pnc-virtual-wallet-love-of-my-life/.

Susan. "Why We're All Addicted to Texts, Twitter and Google." Psychology Today, Sussex Publishers, 11 Sept. 2012, www.psychologytoday.com/blog/brain-wise/201209/why-were-all- addicted-texts-twitter-and-google

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The history of chatbots

The relationship between humans and chatbots

AI and machine learning in financial services

Spixii first took wings in 2012. The three co-founders, Alberto Chierici, Renaud Million and Alberto Pasqualotto, shared a belief in the social and economic value of insurance. Alberto C. and Renaud first met at a tutorial preparing for the actuarial qualification. Renaud was a French engineer by training, while Italian-born Alberto C was a data scientist. Both were insurance professionals in London, frustrated by the way insurance was sold but passionate about its social and economic value.

This value was illustrated when Alberto C delayed buying home insurance for his new flat for three years. Even while working in insurance, he struggled to find a product that was flexible enough. Meanwhile, Renaud's apartment was burgled and wasn't adequately protected to file a claim. Alberto P also found himself unprotected when he returned to his car with its windows smashed in.

Insurance is important to everyone. So let's make it accessible.

In 2015, the co-founders left their offices and talked to people about their insurance stories. Inside, outside, in coffee shop queues, on work commutes - everywhere and anywhere, thousands of light-bulb moments happened across London. People called insurance a nightmare, or they had no idea where to start. 

For many, their first reaction was to text a friend or family member for advice. The idea for Spixii was born: a trusted chatbot that could take people under its wing and guide them through the process. 

Our story

Spixii, the beginnings

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Want to add value to your digital customer experience and help make insurance less of a hassle, more of a delight?

To learn more about the principles discussed in this kit and see how you can put them into action, please email team@spixii.com.

It also starts with a conversation.

Ready to take the next step?

http://www.spixii.com/

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