Senior Project Leader
Carsten holds degrees in Business Administration and Economics from the University of Kiel and earned his doctoral degree from Friedrich-Alexander University Erlangen-Nuremberg. His research focuses on patent and innovation analytics, patent valuation, and the role of intellectual property in investment decision-making. He serves as an editorial board member of Invention Disclosure and World Patent Information.
A patent landscape analysis can reveal where a technology is gaining momentum, which organizations are shaping it, and where competitive risks or partnership opportunities may be developing. When read at scale and against a defined question, patent filings provide an early view of where research effort is concentrating, which organizations are strengthening their positions, and where a field is becoming crowded or remains relatively open.
WIPO describes a patent landscape analysis as an overview of patenting activity and trends in a technological field. It typically aims to answer specific practical or policy questions. A detailed patent landscape analysis turns raw patent filing data into evidence that can inform R&D strategy, portfolio management, investment decisions, and market entry, provided the underlying data is reliable and usefully interpreted. At the same time, simply collating a large stack of patent records does not, on its own, produce insight. For R&D, corporate strategy, and IP leaders alike, the real work is building an analysis that ties patent evidence to specific, decision-critical questions. That requires a reliable combination of high-quality data, a well-designed and validated search, appropriate analytical methods, and results presented in a format that decision-makers can understand.
To conduct a patent landscape analysis analysts first craft a search query to identify patent documents tied to a defined technology, market, or policy question. They then study the patents retrieved from the search to answer questions like: who owns them, which technologies and applications they cover, how filing activity has changed over time, where protection has been sought, how often the patents are cited, and whether they remain in force.
What is the difference between a patent search and a patent landscape analysis?
A patent search retrieves documents; a patent landscape analysis interprets the patterns across them. The output in the latter case is typically a set of charts and visualizations that make those patterns easy to compare and explain. Unlike a freedom-to-operate (FTO) search, which checks whether a specific product or process risks infringing third-party patents in particular jurisdictions, a landscape analysis maps the wider field to inform business strategy or policy making decisions.
Let’s start with the data itself. A single company can surface under various different applicant names: subsidiaries, retired corporate identities, acquired businesses, and simple spelling variants, all fragmenting into what is, in reality, a single owner. The same invention may be represented by multiple related patent applications and patent publications across jurisdictions. Grouping these documents into patent families helps avoid counting every publication as a separate invention, although different family definitions can produce different results. Read our handbook on patent data quality, to learn more about the major issues that our data harmonization team identifies publicly available patent data.
The analysis itself also involves important choices. Raw patent counts treat every patent family alike, but not all patents hold the same commercial relevance or significance to the technology field. Patent citation-based indicators and legal-status information can provide a more differentiated view, but each metric answers a different question. In our approach, we leverage the LexisNexis Patent Asset Index methodology, which combines patent portfolio size with an average patent quality measure. This enables more meaningful comparisons between patent portfolios. No single metric proves commercial value. Patent indicators should therefore always reflect the decision the patent landscape analysis is intended to support.
Patent data is a rich source of business-relevant information. However, it is only useful after someone has rigorously cleaned the underlying records. They must also create a system to reliably compare patent portfolios across technologies and jurisdictions.
A patent landscape analysis converts complex patenting activity into evidence that technical and non-technical stakeholders can use. Detailed patent landscape analyses support several dimensions of business decisions. Operationally, it can show which competitors, technologies, and newly published patent applications deserve ongoing attention. Tactically, it informs where to sharpen R&D priorities, strengthen patent portfolios, or pursue licensing conversations. Strategically, it shapes decisions about market entry, mergers and acquisitions, and long-term technology investment.
Video: Portfolio Size or quantity (x-axis) vs. average patent portfolio quality as measured by Competitive Impact (y-axis) development of ten companies competing in the same technology space, tracked over a ten-year period. The size of the bubble represents the patent portfolio’s overall strength as measured by its Patent Asset Index.
Here is how you read the chart in the video above. The chart tracks the development of the patent portfolios of the top 10 companies in a technology sector over a 10-year period. For this reading exercise, imagine you work at Company G. At the start of the decade, your patent portfolio is not well-positioned: it is a fraction of the size of the market leaders, and by a simple patent count, your company would barely register in the conversation.
But this chart does not consider patent count alone. It also compares patent portfolios using a qualitative scale. Look back at the video around the middle of the decade. Your company’s patent filings maintain a modest pace. Yet the portfolio’s average quality, measured by Competitive Impact, increases by nearly 3x. Let us assume that you did not expand your patents’ coverage to wider geographies. Under this assumption, the disproportionate surge in Competitive Impact is mostly driven by an increase in Technology Relevance value. This is a direct result of others building on inventions you patented years earlier. At one point, your portfolio in this technology had a Competitive Impact value of 3. This means your portfolio was over 3x as relevant to the technology as the rest of the field.
By year 10, your bubble had drifted back down close to where it started. For a few years, in the middle of the past decade, your company’s patent portfolio mattered more than its patent portfolio size ever suggested. The trajectory of the pink bubble rising along the chart’s edge in the first 7 years of the decade indicates a significant increase in the patent portfolio’s average quality as again measured by Competitive Impact. This was a period when your company was well-positioned to pursue strategic partnerships and licensing negotiations. But then shortly after, towards the end of the decade, we can see the bubble move lower without a significant decrease in patent quantity. This suggests that the field may have moved on to whatever it next started citing. Throughout this 10-year period, the rest of the competitive field, except Company J, experienced changes in patent portfolio size. These changes involved minimal to no apparent gains or losses in quality. Your company had an advantage over the field for a few years. During that time, this knowledge could have helped your company make stronger strategic decisions. As patent portfolios grow in size and complexity, reliable, data-driven patent landscape analysis becomes increasingly important. It helps produce timely, actionable insights.
These comparisons are not only useful to a single company benchmarking itself against competition, though. Public authorities, international organizations, non-governmental organizations, and research institutions rely on the same underlying discipline to support technology transfer, evaluate research activity, inform funding priorities, and contribute evidence to policy discussions. WIPO reports illustrate this range. The 2022 landscape on hydrogen fuel cells in transportation found that patent filing activity had accelerated since 2016 and that the top 30 companies accounted for 40% of patent filings in the dataset. In 2024, a WIPO report developed in collaboration with LexisNexis Intellectual Property Solutions mapped 100 technology categories to the UN Sustainable Development Goals. Using PatentSight+ data, it found that 31.4% of active patent families worldwide, more than 4.7 million, are related to at least one SDG.
In practice, a rigorous patent landscape analysis begins with a defined business, research, or policy question. A database search follows that question. The process should be structured and iterative. It moves from scope definition and search design to data validation, analysis, interpretation, and reporting. Combining keywords, patent classifications, patent citations, known reference patents, and expert review generally yields more robust results. This approach is generally stronger than relying on a single search method. Where we see differences of opinion among analysts is in execution. There is no single internationally accepted methodology, so stakeholders such as patent searchers and patent analysts calibrate their approaches to their needs and their business questions at hand. There are advantages and disadvantages to different approaches. For example, a patent search tuned for maximum recall drags in noise, whilst one tuned for precision risks missing patents that matter. Different teams define patent families, patent filing or patent citation counts, and time periods covered differently, so two patent analysts studying the identical technology can arrive at meaningfully different results. This difference can become a risk when a polished chart obscures it.
A technology-scouting question entails a different approach: Mitsui & Co.’s Global Strategic Studies Institute in 2025 compared the patent positions of organizations across five long-duration energy-storage technologies, highlighting research institutes and companies that could shape future commercialization. A due diligence question requires another perspective. During its 2017 review of the Dow-DuPont merger, the European Commission used patent-based analysis as part of a broader assessment of competition and innovation in crop protection. The resulting commitments included the divestiture of relevant DuPont pesticide businesses and almost the entirety of DuPont’s global R&D organization.
Figure: A modeled merger scenario comparing two combined (post-merger) entities, Company A + Company B and Company X + Company Y, against Company W, a similarly sized participant not party to either deal.
Consider five companies that operate in a technology space: Companies A, B, W, X, and Y. The chart above illustrates how the competitive landscape would change if some of these companies were to merge. A merger between Company A and Company B will create a combined patent portfolio larger than Company W’s. However, its quality score will fall slightly below W’s. By contrast, a merger between Company X and Company Y would increase the combined portfolio’s size. It would also create a portfolio with nearly the same breadth and quality as Company W’s. Further analysis of these patent portfolios and their technologies is recommended. This would help ensure the merged entity holds no unfair competitive advantages resulting from the merger. Simply counting the patents in each portfolio will not help a government agency determine its policy direction here.
See how LexisNexis® PatentSight+™ turns complex patent data into insightful patent landscape analysis. Talk to an expert for a full demo.
Once the data, search strategy, and analytical framework are in place, the next question is how AI can make this process faster and more accessible without sacrificing transparency or expert judgment. AI can accelerate the process, but it does not make patent landscape analysis fully automatic. Even with curated data and repeatable workbooks, defining the question and validating searches against known cases still require human expertise. So do identifying omissions, refining results, and interpreting their commercial significance. What has changed is how quickly users can reach a transparent starting point. More business functions can also participate in the analysis.
In a conventional workflow, an analyst translates a business question into technical concepts. They construct Boolean and classification-based search criteria, then review the initial results. Finally, they refine the query to balance recall and precision. The analyst then applies relevant filters, metrics, and visualizations to answer the original question. This requires specialist knowledge that many colleagues in R&D, corporate strategy, sustainability, or leadership roles have never needed to develop.
With access to tools like LexisNexis® Protégé™ in PatentSight+™, analysts can now begin with a plain-language question such as “Which companies are strongest in solid-state batteries?”. Protégé in PatentSight+ interprets the question, identifies ambiguities, and builds an explained search strategy. The resulting query remains visible and can be transferred directly into LexisNexis PatentSight+ for further validation and analysis.
Protégé in PatentSight+ can then help structure the analysis around relevant patent owners, technology trends, and patent portfolio metrics. It produces visualizations, key findings, contextual explanations, and suggested follow-up questions, while leaving users in control of the search and interpretation.
In practice, this shortens the distance between a business question and an initial answer. It makes patent landscape analysis more accessible to colleagues in sustainability, M&A, R&D, or corporate strategy, while giving experienced analysts a faster way to explore alternative framings before tackling the essential work of validation and interpretation.
A reliable patent landscape analysis often goes beyond simple questions. For example: “Who owns the most patents in a technology?”. It often seeks answers to more consequential questions: “Which technologies are accelerating?” “Where are competitors strengthening their positions?” “Which emerging companies should be closely monitored?” “Where might we depend on third-party technologies?” “How does an acquisition target’s position compare with its strategic claims?”
Reliable patent landscape analyses are built on the same foundation across many uses. These include public policy reports, competitive intelligence, R&D strategy, sustainability benchmarking, and M&A due diligence. That foundation includes harmonized ownership information and patent filings consolidated into patent families. It also requires a validated search strategy and metrics suited to the question being investigated. Advanced tools like PatentSight+ with Protégé , purpose-built to solve complex analytical challenges, enable decision makers to act confidently and proactively.
The goal is not simply to collect more patent data. It is to connect the documented development of a technology to decisions about where to invest, what to monitor, whom to partner with, or which assumptions require closer examination. That is what turns a patent landscape analysis from a collection of records into decision-ready evidence.
What could patent data reveal about your next business decision? Request a demo of LexisNexis PatentSight+ with Protégé.
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