Ever faced a long holding time while connecting to a customer support channel? The answer, a resounding YES. But wait, that was an old trend, chatting on apps is in vogue, and millennials are embracing this trend worldwide.
With over 5 Billion users worldwide, instant messaging has become the preferred mode of communication. The rise in the use of chatbots in businesses is further proof of this phenomenon. The global chatbot industry is expected to grow at a CAGR of 37% between 2017-2021, as per a report by Technavio.
The key drivers for the industry are believed to be the 24/7 availability of customer assistance and instant answers to queries, without having to go with the IVR lines. Eight out of ten customers said that they would not do business with brands if they were not handy in precisely these situations.
The insurance companies, typically experience high operational costs for selling the products and maintaining relations with clients. This cost is increased because of the need to keep a call centre workforce, bringing the margins down, therefore affecting the bottom line.
With their experience in the lead generation industry and understanding this pulse amongst customers, Antoine Paillusseau and Romain Diaz conceptualized FinChatBot. They had previously co-founded Far Ventures together in 2015.
With automating the lead conversion process for the insurers, the chatbot startup has been able to increase the conversion rate of leads for its clients from 8% (without chatbots) to 36% (with chatbots).
The startup launched in Cape Town in 2016 met insurers with their product at an MVP stage and was able to attract interest for launch.
Far Ventures invested USD 25 K in pre-seed capital to kick-off the startup and built its first MVP, then Richard Marsden, CEO, Envision Risk Underwriting Managers, invested USD 136 K seed funding to improve their technology and onboard its first client.
FinChatBot utilized this money to develop their product offering and in the last six months has seen a 300% rise in their monthly recurring revenue.
Realising that Johannesburg was where the maximum traction with insurers lies, the company quickly shifted its base there. It has a strong team of 12 people with developers, and AI engineers.
How do they do it?
The Finchatbot team estimates that resolution to 80% of the queries generated by customers of the insurance sector can be automated. For the remaining 20%, they believe an agent is the best solution.
The team sits with each client and defines live cases and scenarios for which their call centres respond to the customer queries. Interestingly, the leading insurers are getting lead generation, customer support, FAQ’s and Onboarding replaced by chatbots.
Initially, the young startup charged a setup fees for placing the bot in their client’s system like any other software agency. As their product improved over time, their income shifted focus to monthly retainer model instead of the setup fees. The one-time installation fee was waived off for the clients and entered the “performance-based income.”
“We have a performance-based income stream with our clients, whereby we earn a share of the revenue that we help them generate through our chatbots or a share of the costs that we help them save on call centre seats,” states Romain with a gleam in his eye.
The team firmly believes clients value this model because it aligns their interests with FinChatBot and in turn incentivizes the team to continuously improve the performance of their chatbots to generate maximum outputs for clients.
Most of their clients are based in South Africa and they have been working closely with leads based across Kenya, Morocco, Nigeria, Zimbabwe, and Australia.
The boundaries don’t seem to have had any effect on the modules as the technology can adapt to a variety of scenarios. The chatbot conversations are scripted based on narrow and very well-designed scripts, developed through live cases. The bots which are plugged in as API in client’s platforms have high accuracy for the rate of conversions as the startup deploys heavy usage of Machine Learning to train the bot.
A robust study goes behind the choice of language for the bot considering the gender, age, geolocation and segmentation data of the customer (looking for insurance). The conversation is optimized continually for better deliveries by the bot. So far, the bots rely majorly on the incoming traffic on the client’s (insurer) site.
Settling well in the insurance sector, the startup now feels it needs to explore other industries that too can leverage the accuracy of chatbots. However, due to security reasons in the banking sector, it experiences the hurdle of Onboarding clients in the industry.
The startup that is promoting its product amongst client primarily through word of mouth and networking is close to breaking even. They want to accelerate from here and are currently looking to raise a seven-digit (Rand) Pre-Series A to increase the number of resources in their sales and data science team.
The AI startup that operates as B2B2C is also underway in developing a payment gateway for enabling the purchase of policy on the client’s website.
L to R: Antoine Paillusseau, Richard Marsden, and Romain Diaz
So, what’s next?
The FinChatBot team envisions creating a product that can get insurance for a customer in a matter of minutes. They want to create a product where a customer at the airport, queueing for check-in, sees an advert with QR code for travel/luggage insurance; he/she scan it with messenger of Facebook and get insured while still in the queue.
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