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We've worked with thousands of IP professionals spanning R&D, portfolio management, patent licensing, IP litigation, M&A and more. Many intellectual property professionals struggle to compare the many patent analysis platforms available in the marketplace because their features tend to sound the same. With this checklist, anyone considering a patent search, patent analytics, or intellectual property business intelligence toolset will get a solid head start to finding the right tool to meet your needs.

While the data sources seem to be similar, the way providers aggregate the data they choose to incorporate and how the software presents the analysis are very different. Decide what’s important to you and ask these questions. 

1) DATA COVERAGE AND QUALITY

Patent data is readily available from jurisdictions around the world, along with other patent-related information like patent sales, patent litigation, and patent-related literature. Each patent search or patent analysis software company will provide limited data sets, or limited jurisdiction coverage, or a combination of both. Questions to ask:

  • Which countries and/or jurisdictions are covered?
  • Is summary information or entire text provided in the results?
  • Is the data translated into English or only available in native filing language? Is the full text of the patent document translated or just a subset?
  • How much non-patent literature (NPL) is included within the dataset and does it cost extra to access? E.g. journals and conference papers, dissertations, pre-prints, abstracts, and technical reports.
  • Patent litigation, patent owner financials, trademarks, patent summaries – what more can your solutions provider supply you with than the typical reporting systems and coverages?
  • Some tools can search worldwide; others charge more for this feature and often leave important regions out of their basic capabilities. With China as an emerging leader in patent filings, it’s helpful to be sure your provider covers all relevant geographies of interest to you.

2) DATA QUALITY AND CORRELATION

Many patent documents have different spellings for the same company owner names and some patent data elements are simply entered incorrectly (See the IBM example). In addition, M&A activity is happening every day, and those changes need to be captured. Inaccurate or missing data makes for manual data cleanup and potentially incomplete analysis.

  • Does the data come ready for analysis or does it require manual fixing and combining of data sets to reach reasonable conclusions?
  • Are missing data elements “filled in” when possible, like historic classification codes?
  • How frequently is the patent ownership updated when a company buys another company?
  • How often is data updated to reflect the reassignments of patents?
  • Are databases regarding different data elements separate or combined i.e., do you have to go to different areas to get litigation data about a patent? Does it cost extra?

With the volume of data always changing worldwide on a weekly basis, no system can be 100% perfect every single moment. When you do find something that’s incorrect, having a process for reporting a correction within the platform is important. There are a number of data points that have to be accounted for, filled in, and reported, how confident will you be in the data process behind the scenes? Better data, updated data and more data give confidence to your analysis.


3) SEARCH METHODS

Every analysis starts with a search to find the relevant patents.  More and better search methods allow you to get to the relevant patents faster and more assuredly.  There’s nothing worse than missing a relevant patent because your IP analysis tool doesn’t support a certain type of search.

  • Will standard keyword searches return relevant and desired results?
  • Can I use a Boolean string to combine keywords with AND, NOT or OR, as well as proximity of words, looking for alternative words, using wildcards, to help narrow down a search and increases the accuracy?
  • Does the tool provide semantic search in order to search by concept rather than keywords? Does the semantic search use synonyms or is it truly concept-driven?
  • Can I search by metadata such as classification codes, citations, dates, company owners and inventors? How easy is it to search for all the patents currently owned by your top competitor?”
  • Does the platform allow for faceted navigation to explore information organised by various filters?
  • How easy is it to save searches and search results, so you can go back to them at a later time?

Flexible and fast search methods get you to the relevant patents much more quickly.  A broad array of search methods gives you the flexibility to use the best technique to get to the relevant patents whether known or unknown.

 

4) DISCOVERY TOOLS

If you’re looking into a new technology, one whose terminologies have evolved over time, or similar technologies in adjacent industries, discovery tools are necessary to discover the right terms and to organise the patents to understanding a landscape.

  • Can I discover relevant patents without using keywords, by starting with a single patent or document to find similar patents?
  • Can I uncover the right terms starting with a set of patents?
  • Am I able to discover groupings starting with a set of patents, classifying them into groups to see which are more prevalent, and also group interactions (such as “which companies are more prevalent in which groups?”)?


5) PRIORITISING RESULTS

When you get the set of relevant patents from a search, some tools will help prioritise the results for faster drill-down analysis. Without this prioritisation help, you’re stuck evaluating the entire list one by one, which could be hundreds or thousands.

  • What assistance in prioritising patents does the tool provide? How much time savings can you get if you want to examine just the highest-priority patents rather than the entire set?
  • How is the prioritisation done? (What confidence do you have that their approach generates the right patents to focus on?)
  • Am I able to establish or “program” my own prioritisation approach if I don’t like the established prioritisation approach or need a specific analysis?

 

6) RESULTS THAT ARE EASY TO UNDERSTAND

Graphics can convey insights hidden in analysis results and improve the look and feel of a report or presentation. Visualisations of results also aid in the absorption of data and help the reader uncover new insights and make well-informed business decisions.  The way information is presented can be just as important as the information itself.

Choose a solution partner who can communicate on the level you need them to in order for the entire team to best understand the report/results. Verbiage, the words utilised on reports, can crystallise or confuse the data itself:

  • Do you understand everything a potential vendor has written?
  • Are visualisations communicating clearly and are they interactive in order to get deeper into the result set?
  • How many visualisations are available and how fast can you access them for iterative analysis?

Interactivity can also help in the way data is presented and absorbed. The graphics and content can be perfect but if they are displayed in a way that confuses some users, the message can be lost. Ask for template samples as well as content and visualisation samples.

7) RESULTS THAT YOU CAN CUSTOMISE

A canned visual can be sub-optimal, even distracting.  Customising  a visual to convey the right insight clearly and without clutter is needed in some scenarios where the template doesn’t quite work. Examples of customisations include removing unnecessary groups of patents or categories in the visual, changing colors, or renaming groups into vernacular your audience uses.

  • What customisation abilities are in the tool?
  • If the tool doesn’t support a specific customisation, does it allow easy exporting into Microsoft Excel along with the underlying data?
  • Is the functionality easy to learn so that just about anyone can customise reports?

 

8) SOFTWARE USABILITY

Unnecessary clicks, poorly laid out interfaces and hidden features can frustrate users and affect the search experience tremendously. Depending on how savvy you expect the users to be, here are several things to consider when making a selection:

  • How easy is it to learn to do something new in the interface? Is there online help, client support from the vendor, and knowledge sharing with other users?
  • Can infrequent users “walk up” to the user interface and complete a task without getting frustrated, or do you need to be a highly trained tool expert?
  • Can power users get to their in-depth features easily? What ease-of-use features exist for efficiency?
  • Can your audience get to the results from any browser on any computer? From mobile devices too?
  • Have you conducted a speed test on the delivery of search results? Consider ranking the speed for each platform you are evaluating e.g. producing results within seconds gets top score, between 10-30 seconds gets medium score; anything over a minute would receive a penalty.

Time is money and for intellectual property professionals, minutes can translate to millions of dollars in lost – or won – opportunities. Easy to use software with accurate and quick delivery of patent search results means you can iterate and refine the analysis more, learn more, and get to a better answer, faster.

 

9) SERVICE QUALITY AND VENDOR REPUTATION

No matter how simple patent analysis software is designed to be, learning a new tool presents change to your team. It’s not unheard of to be chased and wooed during the selling process only to be left to figure out the tool by yourself once the ink is dry.

Even after you’re up and running, a good provider will check on you periodically even if there isn’t an issue. A great one will anticipate your needs and address them with immediacy. A key consideration in this area is the level of support you expect the users to require: how savvy are they with software tools in general and how knowledgeable are they about IP. Considerations related to service quality include:

  • How many people will need to be trained, how many will be your super-users or administrators or is it just you doing everything?
  • How much initial/ongoing training time is included with the software price?
  • What is the process for making product enhancement suggestions? What’s the vendor’s speed and frequency of updates to incorporate suggestions?  Do you have direct access to the product team? Is there a client advisory board for client-provided product input?
  • Does the vendor sponsor an online community for answering questions, suggesting product features, and networking?
  • Does the vendor have user conferences to learn about new features, network with other clients, and hear about the future roadmap? What’s the location and timing of the conference?  How many people typically come?
  • Sometimes there’s no substitute for someone showing you in person how to do something. Does the vendor visit customers and provide 1:1 or group training?  Does the vendor host training sessions near your location?
  • Is a firm’s client satisfaction rating important to you? It may be called Net Promoter Score (NPS), CSAT, or some other rating where the survey is conducted by a third party.


MAKING THE RIGHT CHOICE RESULTS IN YOUR ABILITY TO DO MORE

Saving time can add up to big dollars. A good partner and an effective toolset will help you and your teams save hours or days. Conducting estimates before shopping for a new patent analytics tool to create a business case that proves the tool will pay for itself quickly.

  • What are high-value tasks you can put your employees on if they’re able to do analyses in less time?
  • What additional, impactful analyses can your team perform in the same amount of time with a more efficient tool?
  • What strategic decisions (e.g., R&D, product, competitive positioning/marketing, acquisition, global expansion) can be improved by information from additional and timelier IP analyses?

If you have the time to perform current state analysis, measuring efficiencies that can be produced due to a new analytics tool, the cost-value ratio of the new tool can quickly present itself.

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