Benchmarking Survey – Key findings

January 24, 2024

Patent owners understand the importance of benchmarking patent portfolios and 98% adopt this approach in support of their patent strategy. Over half, however, complain about the time and expense of benchmarking, and almost the same number state that there is a lack of objective and reliable data. This is more than a coincidence, it’s causation. Make a task hard enough and it’s human nature to avoid it.


Benchmarking is at an inflection point where over half of organisations have access to the data and analysis they require to support evidence-based decisions. The other half still struggle with an information deficit largely attributable to obstacles that machine learning and process improvements can eliminate.

Key findings

98% of patent owners use Benchmarking to support their patent strategy and 89%, for Competitive Intelligence

Hear all four Key Findings from the Report on Benchmarking your Patent Portfolio

Understanding your competitors is a fundamental requirement of benchmarking

88% of patent owners report that benchmarking involves a comparison to competitors. Most use Portfolio Size, Geography, Quality and Age as metrics.

However there is a growing trend towards combining this data with other sources of business data to increase relevance to executives across finance, technology and other business functions. This is a topic explored further in our article Beyond Portfolio Optimisation (IAM 100, 2020).

Benchmarking at the technology level is best practice

Benchmarking patent portfolios must be conducted at the right level of granularity to be actionable. 75% of patent owners report that benchmarking is conducted at the technology level and there is consensus that this delivers more valuable and actionable insight.

What granularity do you benchmark?

The main obstacles to benchmarking are cost, lack of objective & reliable data and time

While benchmarking is regarded as critical to patent strategy, 53% of respondents state that the primary challenge is that it is too expensive or time consuming. Other challenges include a lack of objective and reliable data (48%) and a lack of industry standards (42%). Efficient access to the data you need is key and Machine Learning solutions offer a step change in this area.


Those who are not taking advantage of this capability risk being at a significant competitive disadvantage. Benchmarking is at an inflection point where over half of organisations have access to the data and analysis they require to support evidence-based decisions. The other half still struggle with an information deficit largely attributable to obstacles that machine learning and process improvements can eliminate.

Abstract, Grid Pattern, Vector, Wire Mesh

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