For many large companies, inventions are a way to stay ahead of the competition. Businesses like Amazon and Google have tens of thousands of patents for various inventions. Some of these inventions have become the namesake of the business, such as Amazon’s 1-click ordering.
Other inventions might be more silent, working beneath the large structures of the company, providing small edges against the competition. Regardless of the type and nature of the patent, all of them have to be registered at one of the many offices.
Due to the purpose of patents, all information about them must be made publicly available, as knowing whether an invention already exists would otherwise be impossible to acquire. All of these factors make it easier to keep up with the competition.
In the past, getting access to patent data would have been significantly harder. While it is unlikely that they were ever private, one would have to get to the physical office and make a request.
Additionally, other companies have stepped up and developed meta-engines, which can find patent data from nearly any office in the world. Large-scale patent data acquisition has been made accessible, enabling inventors and businesses to find the newest developments within industries.
Collecting all that data manually, however, is a challenging task due to the sheer number of patents being issued every day. While small companies might only get from several to a dozen a year, industry giants can often run the numbers up to a thousand or more.
Not all of the patents will be relevant to a particular business, either. As mentioned, some patents are absolutely fundamental to the competitive edge, while others play a more modest role. Figuring out what magnitude of influence one particular invention might exert will take some time. Couple that with several large competitors, and the issues start compounding.
Scraping search engines
Web scraping provides an opportunity to automate one of the most time-consuming parts of any data analysis—collection. While patent data might be less frequently updated than in other web scraping applications, automation is still evidently useful as it reduces resource costs.
Both meta-engines and dedicated patent office search engines can be scraped as long as automated access—or anything of the like—is not forbidden. As always, consulting with legal professionals before engaging in any scraping activity is highly recommended.
There are some additional ease-of-use factors included in patent data. Most companies, if an invention has been created under their umbrella, will be considered the patent owner with individuals being credited as inventors.
As we are only interested in following the development of competitors, not those of inventors, search functions can be heavily refined to include company names only. Additionally, it may help avoid getting involved with personal data, the collection of which is fraught with challenges and, in almost all cases, shouldn’t be attempted.
Since it is in the best interest of companies to become patent owners, such refined searches are unlikely to ever miss important data. After all, without ownership, businesses would be unable to enforce patent rights against competitors.
Making use of patent data
Finding out what the R&D departments of competitors have been up to is certainly interesting. Interest, however, isn’t motivating enough to spend resources on web scraping infrastructure or any outsourced data acquisition.
An important part of patents is the description and claims. Both of these give admittedly vague outlines of what the proposed invention does and through what means it does it. While these are intended to protect the exact details, impact, and make the patent apply to a broad number of implementations, some useful information can be gleaned through large-scale data acquisition.
With enough historical and recent patent data, an overall strategic direction for your competitor’s R&D department can be reverse engineered. In almost all cases, developing and testing out new inventions is prohibitively expensive, so companies have to narrow down their focus. Inventions constantly popping up in a single field or direction will indicate strategic decisions.
On the other hand, some inventions might be front-facing and have clear appearances within business operations. Hearkening back to Amazon’s 1-click patent—its appearance on the website was obvious. With historical data at hand and constant monitoring, one would have been able to evaluate the impact such an addition might have had on Amazon’s sales performance.
Finally, inventions have some merit as grounds for inspiration. Competitors in the field might be working on slightly different issues, however, it may illuminate previously unforeseen circumstances. In such a way, patents of competitors enable companies to discover a greater picture of the routes a particular industry can take when moving forward.
In the end, patent data is relatively easy to obtain due to its open nature and simple discovery process. At the same time, it provides numerous advantages for those who are tech-savvy enough to unearth the hidden insights it contains.