AXS case study - growing ticket revenue using dynamic pricing
The way we live and work is changing dramatically. It’s only natural that the way we make decisions is colored by world events. Consumers are prioritizing peace of mind and are naturally gravitating to brands that can offer a safety net for their lives. This is particularly true when it comes to large value purchases such as tickets and events, which are often booked far in advance and carry some risk of interruption, especially if you want to check off seeing your favorite artist on your bucket list.
It’s no surprise that protection of assets is more important than ever to today’s risk-conscious consumer. We’ve seen studies from our industry’s thought leaders like McKinsey and our own BrightWrite team that point to a significant and sustained increase in take-up of protection. These have been driven partly by the pandemic and supply chain uncertainty, but also by the rapid adoption of leading-edge technologies and deprecation of traditional integrations and legacy platforms.
Consumers want protection options at the right time and place, namely at the same time they’re buying. Where locking down Super Bowl tickets might once have seemed like a no brainer, our signals overload with what-ifs. Our BrightWrite data analytics team recently examined data from our partner AXS, an online ticket sales platform, to compare volumes prior to – and post – integration to see what best practice means for live events companies looking at add-on alternatives.
A tech-led approach to protection
AXS powers the ticket buying experience for over 350 worldwide partners including teams, arenas, theatres, clubs and colleges – to maximize the value of all their events and create joy for fans. In response to the need for a more scientific approach to pricing and the technical capability to deliver growth (as encouraged by Oliver Wyman), they’ve integrated the XCover distribution platform and jettisoned traditional models. Legacy systems of those traditional models have led to offline processes that restrict the live event industry with fixed rate pricing, poorly performing creative and an inability to bundle their products with what customers actually need (for instance, travelers to an event might need basic travel, medical and cancellation protection to cover their whole stay). This leads to slow or no growth.
By integrating XCover, all AXS customers can now buy tickets and book events with confidence knowing that if something forces a change of plan, their bank account won’t suffer the same blow. By bringing an insurtech approach and tailored protection offerings, our XCover platform has delivered average growth in attach rates of 200% within a few short months of replacing an incumbent insurer.
Tiered pricing extracts more revenue
Our data scientists examined AXS’ historical sales data and identified opportunities to increase yield. We work with partners to determine what yield metric to target and then optimize to it using XCover‘s native analytics platform, BrightWrite. Typically, partners choose to optimize Average Ancillary Revenue Per Quote or Average Revenue Per Quote (i.e., Total Transaction Value / Quotes), with most focusing on the latter to improve their core conversion rates.
The analysis often uncovers the limits of traditional models that, beset by legacy systems, have failed their end customers across a range of industries and failed to keep up with the growth ambitions of the world’s largest digital companies.
Here’s what we found when we looked under the hood…
1. Protection is charged at a flat rate. It should accommodate cognitive bias
We always start with certain hypotheses based on our experience – whether in the same industry or another – and principles of data science. In the case of AXS, they were previously charging a flat rate on protection with a fixed premium to be earned from each sale. Our team looked at the different price bands that existed for historical ticket purchases and created a hypothesis on tiered pricing using cognitive bias, otherwise known as anchoring.
Working closely with AXS, our BrightWrite data analytics platform was deployed to run synthetic tests on anchoring. Customers in almost all industries are very open to paying a rate for protection that’s relative to the price they’re paying for the underlying item, this being especially true as we move up through higher price bands and customers value increased protection for greater spending/greater risk.
Utilizing the dynamic pricing capabilities of XCover, AXS has extracted a previously untapped source of additional revenue, with increased margins at the higher price points. On average, higher rates for higher prices has tripled yield
2. Activity-based pricing
As a global insurtech with licenses or authorizations in 60+ countries and 50 US states, we are required to understand the regulatory environment vis-a-vis dynamic pricing. Typically our first step is to establish floor prices that are adjusted in real time by adding a target premium to the loss ratio. In markets where pricing discretion is available, we then run multiple experiments based on attributes retrieved from partners who integrate the XCover API.
For retail pricing we do not use demographic data and instead rely on behavioral data, especially the decisions made by the same customer (or fingerprint ID if the user is anonymous) on prior visits. Our analysis of attributes for the ticketing industry showed the attribute with the highest correlation to price inelasticity was TTV (total transaction value, as described in the above section), followed by the event type. For instance, music concerts have high price elasticity while sports events have low price elasticity (from an insurer’s perspective there is often higher risk too given the travel requirements and longer lead times).
While we also apply advanced machine learning tests that never sleep, price testing like this has delivered AXS a 78% increase in yield in 14 weeks.