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Sales and Customer Success

Sales and customer success teams must understand usage patterns well when revenue is strongly coupled with consumption, like usage-based pricing models. For example, in the early stages of the customer lifecycle, sales teams face the unique challenge of quoting new users for annual contracts based on minimal usage history. This requires a delicate balance of predictive analytics and an intuitive understanding of potential usage patterns.

Uncovering Hidden Revenue Opportunities

As customers evolve, so do their needs. Customer success teams are crucial in identifying when a customer is ready for an expansion or needs to transition from a fixed-period contract due to increased usage. Here, OpenMeter's data insights are invaluable, offering a clear view of usage trends that signal opportunities for upselling or contract modifications. By analyzing this data, teams can identify untapped areas for growth and develop strategies to capitalize on them. OpenMeter surfaces opportunities directly in Salesforce, HubSpot, or other CRMs without involving data engineers.

Evaluating the Impact of Customer Support

Customer success is more than just resolving issues; it's about understanding the impact of those resolutions. Did customer usage increase positively after support? OpenMeter helps answer these questions by tracking changes in usage patterns post-customer support interactions, offering a tangible measure of the effectiveness of customer success efforts.

In a data-rich environment, distinguishing between seasonality, noise, and actionable trends is crucial. OpenMeter provides the tools necessary for revenue teams to filter out irrelevant data and focus on the trends that will drive decision-making and strategy development.

Converting Data into Actionable Insights

Usage-based pricing impacts every team, from engineering to RevOps and product. The core strength of OpenMeter lies in its ability to convert raw usage data into actionable insights. These insights empower teams across the organization to make data-driven decisions that align with customer needs and business objectives, ultimately driving growth and enhancing customer satisfaction.

Last edited on February 23, 2024