Cloud Solutions | Georgina | 9 July 2021
Insurers are increasingly more aware of the benefit of convenience. A fast quote, an easy cost calculator, perhaps a simple personalised chatbot on a quote page can be all it takes to convert a customer sitting on the fence. Insurance for the customer is not just about legal obligation; it’s about peace of mind. Personalised products sold at the right time can be the key to increasing customer acquisition. Recommendation engines can offer an enhanced customer experience and insight into the insurer’s customer base.
What is a recommendation engine?
A recommendation engine uses machine learning patterns and algorithms to promote a relevant product or item to a potential customer. Not only does this act as a boost for sales and revenue, but it also aims to provide the customer with a more tailored and personal user experience.
Consumers encounter recommendation engines all the time. Even in a manual sense, the supermarket checkout snacks are a physical example of recommendation engines. Amazon’s recommended products have increased its sales – and Netflix’s film and TV recommendations have ensured a tailor-made customer experience for its users.
The data collected from recommendation engines provides the business with valuable marketing intelligence. It can dictate what products or items are recommended the most, as well as identify gaps in the consumer market; providing space for improvement and innovation in the services/solutions provided.
How would a recommendation engine benefit a customer?
With individual insurance products becoming more commonplace and not seen as ‘niche’ as they used to be, there’s an appeal for customers to take control over what and how their property is insured. Customised cars, for instance, may require their own policies where a blanket car insurance policy might not cut it for the customer.
Insurance can be complicated – and it’s never particularly enjoyable to renew or get a new policy. This is because historically, insurance sales are full of complicated jargon which the common customer isn’t expected to understand. With recommendation engines, customers can be reassured that they’re buying a product that’s relevant to them – not just for a legal obligation, but because it’s in their best interests for peace of mind.
Insurers want to bring home the message that insurance is for peace of mind – recommended products tailored to their needs can enforce that very message for the customer.
How would a recommendation engine benefit an insurer?
Insurers can utilise their customer’s data to ensure a relevant and efficient product is sold – increasing both customer acquisition and retention. Using recommendation engines, insurers can calculate which existing customers have similar portfolios to detect which products both new and existing customers would be interested in. We’ve all seen “customers like you also bought…” on sites such as Amazon – why should insurance be any different? With customers increasingly more comfortable managing insurance online, recommendations can empower them further.
For insurers moving their systems towards the cloud, recommendation engines can bring that data with them, as well as update it in real-time. “Productised insurance” is a trend that’s being favoured by lots of insurers; recommendations can swiftly assist in defining areas in which this strategy will drive the most revenue. Updating their back end systems can have a direct effect on front end transactions for the customer. These solutions make the business case for digitisation easier. Not only is the architecture and systems behind the curtain sped up and more efficient, but the customer experience is enhanced in parallel.
What do insurers need to do to get to this point?
For many, it starts with thorough planning, both from a business and technical aspect. IT and the commercial business (i.e. sales and marketing) need to be heavily aligned in order for recommendations to be fruitful. Other areas that insurers need to examine would be;
- Current business roadmap and strategic objectives (with a timeline)
- Audit and understanding of current and future IT architecture
- Internal resource (talent) to maintain and support the IT infrastructure
- The capacity to act on the results of real-time audience data insight
We can assist in ensuring the correct architecture is suited for your strategy. Get in touch if you’d like to explore these business benefits further.