The TMT industry continues to transition to virtual agent interaction.
As this transition accelerates, companies must adapt their pricing strategies to remain competitive and to avoid cannibalizing existing revenue streams. Our client, an agentic AI solution provider, felt the need for an optimal packaging and pricing strategy to facilitate growth. The company typically used a usage-based subscription model for pricing. Despite the simplicity of this metric, customers had expressed concerns about cost predictability, making a new approach critical.
With our help, our client aimed to remove pricing friction, encourage product usage, and develop a monetization model for long-term business growth.
We assessed the client’s strengths and customer-perceived ROI to ensure pricing was in line with value delivered.
Our goal was to promote platform adoption while maximizing and safeguarding revenue. To do this, we identified the product's key competitive advantages and designed an optimal package structure aligned with customer needs.
We followed this up by introducing a hybrid pricing model that enhanced revenue capture through an effective consumption and outcome-based pricing metric. This helped ensure that pricing was fair, measurable, and scalable. Finally, we built a formal discounting framework for various deal types.
Our new pricing and packaging model helped the client identify 20%+ of incremental revenue.
Additionally, the company adopted this structured, value-led approach to apply across its platform and use the monetization strategy for ongoing, sustainable growth.
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