Why Customers Kept Choosing the Cheaper Contract: How a Gas Turbine Service Provider Used IDIs and Analytics to Understand a Premium Contract Tier Nobody Was Buying

Long-term service agreements are central to how gas turbine service providers generate predictable revenue, and a well-designed premium tier should, in theory, sell itself to customers running plants where unplanned outages carry serious financial consequences. The gap between what a premium offering should logically appeal to and what customers actually buy, however, is often wider than providers expect, and the reasons are rarely obvious from the outside.

The client had built its premium long-term service agreement tier for customers operating critical power generation assets, reasoning that faster response and guaranteed parts availability would be an easy sell to anyone exposed to high outage costs. Adoption came in well below target. The sales team’s working theory was that price was the barrier, but several high-risk customers had still declined, which did not fit a simple price-sensitivity explanation.

Without understanding the real reason customers were declining a tier that appeared to match their risk exposure, the client risked making the wrong adjustment, cutting price and margin without actually addressing whatever was really holding adoption back.

Key Challenges

• No direct research into why customers who evaluated the premium tier ultimately did not purchase it.
• A sales team assumption that price was the barrier, contradicted by several high-outage-risk customers still declining.
• No analytics connecting customers’ outage cost history and utilisation patterns to their actual contract tier choice.
• Risk of cutting price and margin without addressing whatever was actually driving the low adoption.
• No structured way to separate customers declining for cost reasons from those declining for a different reason.
• Commercial leadership pressure to fix adoption quickly, creating risk of an uninformed pricing change.

A premium service offering that looks like an obvious fit on paper can still fail to sell if it is structured around a commitment customers are not willing to make, even when they would clearly benefit from the service itself. Direct customer research is usually the only reliable way to tell a pricing problem apart from a structural one.