Reducing churn risk through tenure‑based recognition

NRMA Insurance faced growing customer dissatisfaction among long‑tenure customers who felt undervalued by loyalty mechanics.

The challenge

  • Research showed that loyalty in insurance is interpreted as tenure and trust, not spend or product count
  • Product-count bonuses create dissatisfaction among long‑standing, low‑policy customers
  • Existing loyalty constructs unintentionally overlook long‑tenure customers, increasing churn risk and eroding emotional loyalty

The problem to solve

I led discovery to reframe the business problem, align executives on risk‑aware scope, and define a phased, evidence‑led approach that prioritised fairness, visibility, and trust.

  • Reached agreement on framing the problem, business risks, guardrails, and decisions
  • Led product feature ideation workshops, journey mapping, and feature prioritisation
  • Prioritised feature roadmap by impact and downside risk using Kano analysis
  • Tested assumptions quickly without over‑investment using AI-accelerated design

Key findings

Based on key findings from the ideation and Kano study research, I gave the following advice on the relative value of a range of loyalty experiences, from highest to lowest:

  • My discounts design uplift
    Make the value of loyalty explicit by clearly showing real dollar savings by tenure and policy, especially during policy renewal.
  • Lifetime tier discounts and benefits
    Protect long‑tenure customers from losing earned status as life circumstances change, reframing loyalty around trust rather than product count.
  • Loyalty-protected excess
    Automatically reduce claims excess for long‑tenure customers, embedding recognition into service and and reducing at vulnerable moments.
  • Relationship dashboard
    Provide a clear, persistent view of tenure, benefits, and milestones to reinforce recognition without promotional mechanics.
  • Priority assistance
    Long‑tenure customers access specialists, empowered to deliver long-tenure specific service outcomes, translating loyalty into services rather than extra perks.
  • Portfolio health check
    Reduce risk of disappointment by accessing a personalised portfolio check anytime to make sure you’re not overpaying and you’re not underinsured, based on your history and policies.
  • Personalised and individual rewards
    Remove loyalty “Gold/Silver/Bronze” labels and personalise recognition. This concept was deprioritised, with learnings feeding into more concrete recognition mechanisms.
  • Safer driving monitoring
    Gamified driver behaviour monitoring showed mixed responses from long‑tenure customers, with some actively disliking it. It was not a primary lever for managing long‑tenure dissatisfaction.