Consumption-Based Business Models Growing and Product Managers Leaning Increasingly on Usage Data to Make Strategic Decisions
Flexera, a demonstrated leader in software installation, open source software scanning, and software monetization, released the Flexera Monetization Monitor: Usage Management & Insights report.
“Our research shows considerable growth of usage-based monetization models and high-performing product teams leveraging usage data to improve software and provide customers more value,” said Nicole Segerer, Director of Global Enablement at Flexera. “It doesn’t matter if software is in the cloud, on-prem or embedded on devices, or how it’s licensed today: usage data is essential. Without usage intelligence, product teams aren’t armed with the right data to make strategic decisions, have issues to align price with value and risk falling behind.”
Usage insight is more than knowing if software is being used or not. It includes how much of a certain metric is being used, whether utilization is increasing or decreasing, versions and features in use, and trends. Usage data is valuable in far more contexts than just usage- or consumption- based monetization models. It can help product teams make better roadmap decisions; understand which features are most valuable and price them accordingly; monitor patterns of software usage to improve customer experience; and improve compliance by monitoring usage limits and licenses.
Highlights from the Flexera Monetization Monitor: Usage Management & Insights report include:
- Usage Insight Important Across Deployment Models: As reported in Flexera’s previous report, Monetization Monitor: Monetization Models and Pricing, software suppliers often use a hybrid approach with a mix of deployment models. They leverage usage-based monetization models for on-premises, SaaS and embedded applications. SaaS-based companies lead the way in collecting usage data, while on-premises vendors remain exposed when compared to the competition.
- Interest in Usage Data Is Growing: Almost Half of Respondents Plan to Increase Usage-based Monetization: Software suppliers’ interest in usage-based monetization models indicates that the need for accurate usage data will continue to grow. SaaS-based companies are leading this trend. Overall: 43 percent of all respondents and 48 percent of largest software vendors (those with more than $100 million in revenues) expect to increase the use of usage-based monetization in the next 18 months.
- Challenges Remain in Understanding Usage Data: While the interest in usage data is clear, responses show that companies have varied access to and interpretations of software usage data. Overall: Among all respondents, only 51 percent said they could see if customers are using software at all; 45 percent said they can see which product version a customer is on; 43 percent said they can see which features are being used; and 42 percent said they can see if usage is increasing or decreasing. Significantly, a full 15 percent are essentially flying blind, indicating they can’t see any usage or utilization metrics.
- One Third Cite Insufficient Usage Insights as Reason for Pricing Challenges: When asked for the hurdles that make it hard for software suppliers to align their pricing with customer value, the struggle to understand usage shows up as the biggest inhibitor; 33 percent of all respondents claim the biggest hurdle for aligning price with customer value is insufficient insights into data usage.
- Usage Data Builds Pricing Confidence: Understanding usage helps ensure that software pricing is correctly aligned with value. This is an absolute must for usage-based models and a best practice for all monetization models. Overall: 53 percent of all respondents felt they are confident their pricing is aligned with the value they provide customers; among companies already good at collecting data, 63 percent feel that pricing is aligned with value.
- Understanding Usage Can Help Prevent Revenue Leakage: Forty percent of all respondents indicate they experience unintentional overuse in user or usage-based monetization models. Usage data can deliver great insights in unintentional overuse, unexpected usage patterns and more.