Data analytics are vital in developing effective IP strategies. — Espie Angelica A. de Leon 

Data analytics are vital in developing effective IP strategies. Espie Angelica A. de Leon reports from IP Week @ SG 2024 on how businesses use IP data to improve their portfolios, find new opportunities, stay competitive and more. 

At IP Week @ SG 2024, the 13th edition of the Intellectual Property Office of Singapore’s annual August IP event, Wendi Backler, the Toronto-based partner and director of global management consultancy firm Boston Consulting Group, shared the work they have done for one of their clients. 

Since working with the consulting firm, Backler said, the client has since made progress by leaps and bounds. Not only has it generated hundreds of millions of dollars annually and doubled its total shareholder return to 22 percent, but it has also made several acquisitions. The cherry on the top: It has zoomed to pole position in the biobanking industry to become a major player. 

What was the secret sauce to this success?  

The answer is data analytics. 

Analyzing innovation and intellectual property data, Boston Consulting discovered unexpected opportunities for the client in adjacent growth spaces. One such opportunity lay in the cryogenic tissue sample for biobanking space. Backler’s team believed the client could be competitive in this area in the future.

“So we went back to our innovation data, our innovation analytics, to help identify who should they partner with, where should they invest, etc. We used patents, scientific research and collaboration data to help us figure out and prioritize where they should make investments,” she said during the panel session, The Economics of IP: Costs or Benefits for Businesses and Policymakers. 

Data analytics reveals crucial information that will help shape key and informed business decisions. Such information includes technology development trends, market competition patterns, market and consumer demand, market trends and changes and others.  

Making informed business decisions through data analytics strengthens a company’s competitiveness in the market and improves its efficiency. Ultimately, it helps boost revenue growth while saving costs. 

“Business leaders can turbocharge revenue growth by leveraging IP and innovation data, enabling them to make data-driven decisions to optimize the management of their IP assets by identifying potential commercialization opportunities and to weed out underperforming or idle IP assets. Business leaders can also rely on IP and innovation data when conducting competitor benchmarking and analysis, allowing them to track emerging trends and technological advancements in their industry by monitoring new patent filings,” said Sher Hann Chua, TMT and IP managing associate at Linklaters in Singapore. 

As Boston Consulting demonstrated, IP data analytics also helps companies identify potential partners and collaborators, especially small- and medium-sized enterprises (SMEs) which have limited resources.   

It aids business enterprises in mergers and acquisitions as well. “By using IP data analytics, material insights into a target company’s value can be gained by looking at its past IP filings, IP commercialization track records as well as IP litigation records,” said Elisia Engku Kangon, senior associate at Shearn Delamore & Co. in Kuala Lumpur. 

Developing an IP strategy: The role of data analytics  

“The final thing we did was we were able to identify for them a very strong path to building a solid IP foundation,” Backler shared during IP Week.  

Indeed, data analysis using IP and innovation data can help develop a strong and future-proof IP strategy that will improve a company’s footing or sustain its leadership in the market. 

Bin Zhang, director of the legal department at CCPIT Patent & Trademark Law Office in Beijing, explained: “The application and benefits of data analytics in business decision-making are reflected in a number of areas, including improved market insight, product optimization, risk management and accurate implementation of marketing strategies. These applications are not only directly related to the daily operations and long-term development of enterprises, but also have a profound impact on the development of IP strategy. Through data analysis, enterprises can deeply understand the market and consumer demand, predict market trends and changes, and thus develop products and services that are more in line with market demand. This data-driven decision-making process helps companies identify and protect their innovations against the risk of infringement, thereby building a more robust IP system.” 

For example, data analysis using market data and consumer feedback will uncover potential risks and problems as early as possible. This will allow companies to take the necessary measures in a timely manner and avoid losses caused by infringement or legal risks. 

In particular, patent data can reveal which technologies are becoming crowded. Such information will allow enterprises to identify new areas of opportunity.  

“For example, in the electric vehicle industry, a company might use whitespace analysis to identify gaps in the existing patent landscape. For instance, there could be a lack of patents related to battery safety systems in extremely cold conditions. This gap represents an untapped opportunity, enabling the company to innovate in this space, file patents and establish a competitive edge in the market,” explained Manisha Singh, founder and managing partner at LexOrbis in New Delhi. 

The term “whitespace” refers to unpatented areas. Therefore, whitespace analysis is the process of studying existing patent landscapes to identify areas of technological innovation that are under-patented or unexplored. 

“A data-driven approach to IP strategy also helps businesses optimize their existing portfolios. Analytics can reveal which patents are high-value based on factors like citation frequency, geographic coverage or the number of claims. On the other hand, patents that are underutilized or no longer relevant can be abandoned or licensed to generate additional revenue. It [also] leads to organizations gaining more insights of potential inventive concepts at present unknown which mines out innovations and patents that are profitable for the organization,” Singh added. 

It is the same with trademarks. Say a company has multiple trademark rights in different countries. “It is usually the case that not all trademarks need to be maintained due to market or operational changes,” Kangon noted. “In such an instance, thorough data analytics of the trademarks based on qualitative metrics allows a business to optimize its trademark portfolio management resources by focusing on the relevant and essential trademarks.” Relevant qualitative metrics include market strength, current or previous litigation or enforcement history, financial performance and licensing potential of the mark.  

When deciding whether to use a certain term as a brand name and apply for trademark registration, a company can undertake data analytics using the data of its competitors. By studying these data, the company will know if the term it is considering to use as its brand name is frequently used by others in the industry. Frequent use may raise concerns about the term’s distinctiveness. 

Companies must consider other factors when building their brand. Among these are consumer acceptance and the strength of protection for the trademark. Data analysis can do the job of evaluating these factors to provide insights crucial to brand development. 

Analyzing IP and innovation data also helps in brand diversification. “For example, if a manufacturer of gaming computer equipment wants to assess expanding its brand from the gaming computer sector into lifestyle products for gamers, it needs to analyze gamers’ consumption patterns and daily behaviours. This analysis will enable them to accurately target products that gamers are particularly fond of, such as ergonomic chairs for prolonged sitting or energy-boosting snacks, thus facilitating effective brand diversification,” said Gary Kuo, a partner at Winkler Partners in Taipei. 

Citing another example, Chua said: “Businesses planning to launch a new product or brand can leverage litigation analytics focused on the ruling history of specific courts or gain valuable insights related to a specific industry to complement their trademark clearance and freedom-to-operate searches. This empowers them to make data-informed decisions, paving the way for smoother market entries.” 

By using predictive data analytics, a business can gain crucial foresight on future trends, possible risks and needs in terms of its IP portfolio based on historical data. 

Steps involved in data analysis 

Data analytics using IP and innovation data involves the following steps:  

• Determining the purpose of data analysis. Do you want to understand the latest development trend in a certain technology field? Do you want to evaluate the technical strength and market competitiveness of a target? The focus and angle of analysis will be different depending on the purpose.  

• Collecting relevant IP data (patents, trademarks, copyrights, etc.) and innovation data (research and development results). “This data should come from multiple sources, including internal databases, external patent databases, market research reports, etc. The collected data needs to be integrated to ensure accuracy and consistency,” reminded Zhang.  

• Establishing an efficient data storage and management system which can support large-scale structured and unstructured data and fast retrieval. Structured and unstructured data include text, images, videos, audio files and others.  

“The digital management system used in the analysis of IP data can also improve the effect of IP management, realize the automatic management of information, seamless docking of official data interface, automatic extraction and sorting of patent, trademark and other IP information, effectively reduce manual entry and repetitive work and improve work efficiency,” Zhang said. 

In the meantime, users can take advantage of professional data analysis tools or software. These will help them manage the analysis work and provide multiple analysis dimensions, such as applicant trend analysis and technology field distribution analysis. 

• Making use of big data analysis technology to conduct in-depth analysis of the collected IP and innovation data. This includes data mining and text analytics, among others. 

• Collating the results of the analysis into a report for easy sharing and dissemination. 

Analyzing data with the aid of AI 

Artificial intelligence (AI) is now everyone’s buzzword and the application of AI has found its way in various endeavours across multiple industries. Data analytics is one of them. 

“With AI, the enterprise can conduct more powerful data analytics, enabling it to more easily analyze vast amounts of patent data,” said Kuo. 

One of the global frontrunners in AI-powered patent analytics is Patsnap, headquartered in Singapore. According to Dian Guan, co-founder and APAC general manager of Patsnap in Singapore, AI has become increasingly critical in patent search and patent analytics due to its ability to process and analyze vast amounts of data quickly and accurately – resulting in increased efficiency and enhancement in search capabilities, data analysis and predictive analytics for IP professionals. 

“Traditionally, patent documents and scientific journal papers are very text-heavy and the users have to be trained and knowledgeable enough on the subject matter to be able to search through and make sense of the extensive data, in order to use them meaningfully. The patent information sector also presents high barriers to entry, with diverse and often poorly digitized systems across countries,” Guan explained. 

Patsnap recently became the first in the industry to develop its own large language model (LLM). The LLM is trained on innovation data within Patsnap’s comprehensive repository. It also benefited from domain-specific training, allowing it to generate accurate and reliable answers that are far less prone to hallucinations. Combined with Patsnap’s Hiro, an AI assistant for IP and research and development (R&D) teams, the company’s own LLM is capable of delivering actionable insights that increase productivity for IP tasks by 75 percent. Furthermore, it reduces R&D wastage by 25 percent.  

“For a global chemical enterprise, using Patsnap enables them to monitor competitive insights 10 times faster, allowing them to make proactive adjustments to their R&D plans and seize opportunities six months ahead of trends,” she added. The company was also able to mitigate 80 percent of risks, avoid redesign costs and speed up product launch. 

The uptake of data analytics in Asia 

According to Alison Wong, a partner at Bird & Bird in Hong Kong, more business enterprises in the jurisdiction are relying on IP data, innovation data and data analytics to make informed decisions and develop their IP strategies.  

“In addition, the Hong Kong government has been encouraging IP development and use of IP data, as demonstrated by several of its initiatives. For instance, it was announced in the 2024/2025 Budget Address that the government will pursue the establishment of the WIPO Technology and Innovation Support Centre or TISC. The TISC will provide specialized services such as patent search and analysis for the protection of scientific research results and provide greater support to the innovation and technology sector,” Wong said.   

Bird & Bird includes a team dedicated to providing legal advice, portfolio strategy advice, patent portfolio analytics and valuation. The team consists of lawyers, consultants, data analysts and software developers.  

The firm has likewise built a website with data analytics functionalities for a U.S.-based multinational clothing company. “The site is used to track enforcement actions taken against counterfeiters and copycats in China. The site processes vast amounts of data to identify patterns and trends, evolving threats and potential hotspots such as provinces with a high level of infringement activity, for IP enforcement. Visualization tools, such as dashboards and graphs, are used to provide real-time insights. This helps the company determine how to allocate their resources more efficiently,” revealed Wong. 

Meanwhile, India is seeing a trend of increasing reliance on IP data analysis by technology-driven sectors and startups to aid their decision-making.  

“Nowadays in this world of cost optimization and process enhancements, it is a given that without taking this step, the organizations are faced on one end with filing in areas wherein there is no return on investment (ROI) or filing patents that would be litigated upon leading to increase in costs,” said Singh. “Data analytics therefore serves as a vital cog in bringing an optimization of costs and resources in IP.” 

She shared that in the renewable energy sector, whitespace analysis has identified opportunities in smart grid technology and energy storage solutions. These are areas with relatively few patents. Therefore, the companies that used whitespace analysis and discovered these gaps are able to innovate and secure patents in these areas. Eventually, they gained a competitive advantage and were able to grow their business. 

To provide another example, Singh spoke about a client from the autonomous vehicle industry. Her team used whitespace analysis to analyze competitor patent portfolios. “Our analysis revealed that most competitors were focusing on general safety features, but there was little patent activity surrounding traffic safety in smart city environments. We recommended that the client focus on this untapped niche, which allowed them to file patents that positioned them as a leader in the market. This strategic alignment solidified their position in the industry,” she related. 

The same developments are happening in China where more and more business enterprises are turning to data analysis to achieve their goals.  

In Singapore, no less than the Intellectual Property Office of Singapore is offering advisory services on patent analytics involving large sets of patent data.  

Kuo believes the uptake of data analytics for IP will see an upward trend in Taiwan, particularly among players in the technology sector. “The technology sector, particularly the semiconductor industry, is one of Taiwan’s most advantageous industries. IP protection is crucial for the technology sector. Furthermore, AI, which is currently gaining global attention, will become an indispensable tool for future data analytics, and Taiwan holds a key position in the AI industry,” he said. 

Global patent applications have reached 3.5 million in the last 10 years while trademark filings reached the 15 million mark as of 2022. The onset of the Covid-19 pandemic pushed enterprises to step up their digitalization efforts and the public to use mobile apps and other digital systems more often. These developments have resulted in a huge body of data about IP and innovation-related initiatives from around the world.  

Businesses, including startups, ought to take advantage of these data and unleash the power of data analytics for their own success story.