Cross selling, gap analysis, whitespace review. Call it what you will, spotting your customers’ next insurance need is key to top notch broking. The best in your business do it consistently, driving not only sales but also customer satisfaction and deepening relationships. But how do you get everyone behaving like the best?
Experience matters
Brokers with experience know which extra products benefit their clients and are worth discussing. They have dealt with similar customers time and time again and know the signs to look out for. These conversations show customers the value you provide. But it’s not so easy for those new to broking who don’t have that well of knowledge to draw from. Experience is difficult to pass on, and is costly and time consuming to build.
Can we shortcut that long road to experience?
Moving into new markets
Insurers constantly work hard to build out their product offerings to stretch across customer requirements. However, brokers will go to familiar insurers for products they know. For an insurer, launching a new product is risky, but promoting the right products at the right time can change habits and the status quo of the market.
Can we speed up that process of change?
Cross selling benefits
To answer these questions, the Data Science Team at Acturis analysed thousands of cross sold policies. We wanted to quantify the benefits of cross selling, and see if there was potential to improve the success rates for brokers and insurers using Acturis.
As you’d expect, clients that held multiple policies had higher lifetime values on average. What was unexpected was the scale of the difference – clients that held multiple policies had a lifetime value six times higher than single policy clients.
Of course more policies mean more money. It also means more loyalty. Those clients with multiple policies had retention rates just over 12% higher than single policy clients. Successful cross sell has big knock on effects to the future relationship with the client. Clients who were cross sold stayed with their broker a third longer.
An obvious question arose from such a stark difference – is it cross sell that drives the relationship or vice versa?
To answer we focussed on those clients that were in their first year with their broker. Clients that had been cross sold with no prior relationship also had 10% higher retention, showing that cross selling clearly strengthens the relationship.
Sharing experience with AI
Machine Learning evaluates past data and discovers complex patterns. We can use this to identify like-minded customer segments and predict the policies they need.
In other words, we can use machine learning to quickly and automatically pass on the experience of good, established account executives to every account executive in your businessThis allows them to successfully offer the client the products they are likely to need.
To prove this, we trained an AI across cross sold clients, identifying the key characteristics that could predict cross selling needs.
Our new AI had to be put to the test. We took clients that had purchased multiple policies and passed their profiles to our AI. We compared the AI suggestions to actual subsequent purchases. 4 out of 5 clients had indeed purchased at least one of the AI suggestions.
And there is plenty of opportunity. The AI identified that most customers have potential cross sell options waiting to be sold.
Keeping up with the Jones’
There are lots of different machine learning techniques.
A commonly used algorithm is called k-nearest neighbours. This is a way of comparing one data point (e.g. the data describing a client) with others that most closely resemble it.
We use a form of this within our cross sell AI – comparing a client’s profile to others and spotting potential insurance products that similar clients have on cover but are missing from the current client.
This allows the AI to spot the patterns in which clients buy which products together.
Data driven broking
Using data to suggest cross sell opportunities is one thing, but how does that data positively drive behaviour and how can you improve the data available in the future?
We believe there is huge benefit in using AI to improve how people interact with the Acturis system. By using the cross sell AI to automate the creation of opportunities within Acturis you can ensure an audit trail for the opportunities that have been discussed with the client and what the outcome was.
This can influence and help mould the future suggestions from the AI, and helps with understanding where the cross sell process is working and where it isn’t. Know where to focus energy to update processes or what is being offered.
The ethos of practical AI
The Acturis Data Science Team have an ethos of ensuring the AI services we are developing have practical application. We want our AI to enable and empower people to do their job better. This tenet is central to how we build and test our AI models.
We believe this is a core reason why we have seen excellent results from our initial partner implementations of the cross sell AI. As a team of advocates for AI technology, we are enthused by each and every success we have seen as we apply our AI services to tackle real world problems. It’s good to know the technology works as well for real customers as it does when we test the theory.
If you would like to talk further about our cross sell AI, or AI and machine learning at Acturis in general, please contact DataScience@acturis.com.
You can also find some information in our brochure, which can be found here.
Gordon Jenkins is the Acturis Data Science Product Manager, and has been working with data at Acturis since he joined us back in May 2008.