The brokered patent market in 2018

“The patent market has fully stabilised and prices are rational,” said no one ever. During 2018 total dollars transacted in brokered deals increased while prices of single-asset deals have dropped significantly.

Last year we told the story of a patent broker who said: “This market keeps on getting worse; the case law keeps on coming out against patent owners; the prices keep dropping. This job keeps getting harder.” We replied: “Our data says that you did pretty well last year.” “Right,” the broker conceded. “Last year was our best year ever…”

This is truer now than ever before. Many of the metrics by which we analyse the patent market have been focused on the price of a single patent, a patent family or even a group of patents in a package. But this leaves out a key market statistic: volume. As the market matures, we see prices stabilising across listings, buying and selling programmes becoming more streamlined and more transactions overall. The market is up with more sales and more participants than ever before. While average asking prices dropped again, this fall was mostly due to prices for single-asset deals normalising to the pricing of the rest of the market. Meanwhile, listings, sales and dollars transacted have all increased. The market continues to grow.

This is our seventh year reporting on the secondary patent market. Every year we find the market changing in different ways, but the big transformations of the last two years have been increasingly positive. When digging into the details, the impact of these developments becomes more pronounced. This article covers the broader market factors, including:

  • an increase in sales to $353 million from just shy of $300 million;
  • a staggering fall in initial asking prices of 30% – although much of this drop can be attributed to single-asset packages;
  • the continuing domination of software sales, which accounted for 57% of 2018 brokered market sales;
  • old deals are continuing to sell – multiple packages sold even though they had been on the market for three or more years;
  • litigation threats from sold packages continue to rise – if you have not considered a defensive aggregator, you should; and
  • more consistent price expectations are improving the market’s function and transparency.

This year, we wanted to put our analysis in perspective and try to look at the numbers from the viewpoint of a particular participant in the brokered patent market, where possible. Of course, these statistics are valuable information to all participants, whether you are a buyer, seller, broker or simply observing and trying to optimise and value your own patent portfolio. In all cases, every participant should be looking to optimise and systematise their approach to participating in the patent market.

If you are a buyer and receive five packages every business day, you need to know what is in each package, who delivered it, what conditions were associated with the sale and then quickly determine if there is a strategic case for purchasing it. If you are a seller, you want to track what is selling, to whom and at what price in order to maximise the sales potential of your packages and efficiently contact buyers. Using market data, you can also make intelligent and economic decisions on patent strategy (eg, buy versus build or monetise versus abandon).

This is why we started tracking the entire market. Our desire for efficiency prompted us to look for optimisations. We have built systems that track over 160,000 assets across more than 7,300 deals. These assets are from 2,700 sellers and represent filings across 80 jurisdictions. There is a lot of data to review.

Market size

Figure 1. Cumulative sum of asking prices ($ billion) – brokered and tracked private market

Figure 1. Cumulative sum of asking prices ($ billion) – brokered and tracked private market

Adding up the asking prices of all the assets in our database leads to $16.7 billion of patent assets. We have written programmes to parse the assignment records and have identified $5.3 billion of that market as sold. Last year, we predicted that through the third quarter of 2018 we would observe at least $3.75 billion transacted: the market blew those numbers away.

Figure 1 shows the market we have tracked for the past seven years. We have included both private and public packages and have tried to determine an overall total dollar value for the patent market. Our visibility into private packages is limited to packages on which we have worked. That said, the dollar value of the market is surprisingly large and diverse.

Figure 1 also shows an extrapolation of the market through to the third quarter of 2019. Between about $1.5 billion and $3.75 billion in new potential packages enter the market every year. The sales data as of the third quarter of 2018 includes only sales for which we have identified an assignment document. Projecting through 2019, we expect cumulative total sales to reach over $6 billion.

The remainder of this article follows the flow of a typical purchase process, covering sourcing, asking prices, diligence steps, purchase closing and litigation. It concludes with our estimate of the market size.

Patent brokers

If you are looking to buy patents, you must first determine who has them and then who is willing to sell them to you.

In many cases, this is where patent brokers come in. They are consistently able to find the most diverse sets of patents from a variety of sellers. However, like the real estate market before the advent of multiple listing services (eg, Zillow and Redfin), each broker only has visibility into its own listing portfolio. Only those who know multiple brokers, have non-disclosure agreements in place with each of them and have the money to buy patents can access the full market information including thousands of patents for sale; otherwise you can only see what your broker does. But, as in real estate, brokers experienced in the market bring a substantial value to both buyers and sellers – particularly for those companies with less experience participating in the patent market.

Brokers offer a unique skill set, including:

  • filtering patent assets to identify which ones to sell;
  • selecting viable sellers and buyers;
  • screening patents and identifying those which are important, as well as their claims (this can be crucial for cutting diligence costs by allowing buyers to focus on the most important parts of a package first);
  • providing pricing guidance;
  • providing guidance for sellers with regard to sales terms and timelines;
  • defining the process for diligence, bidding and sales;
  • developing evidence of use (EOU) materials; and
  • negotiating on pricing.

Brokers also bring another invaluable skill to the table: an unashamed ability to get deals done. Many have networks of potential buyers numbering well into the hundreds and will actively seek out assets for a buyer’s specific buying needs. While for sellers, a good broker can manage the sales process when only a small portion of potential buyers may have any interest. When we help a client evaluate whether they should work with a broker or sell directly, we look to see if that client’s skill set and experience are similar to those of brokers. Often, these are skills found in a company’s corporate development department.

Tools and process used to analyse the data

As the brokered patent market matures, access to data has increased. However, the market remains fairly opaque. Therefore, to analyse the market we pull data from many sources, combining this with a proprietary set of tools that we have designed in-house.

Our data sources include our proprietary patent package database, the USPTO patent data (Public-Pair), the USPTO Assignment database, Derwent Innovation, PatSnap and litigation data from DocketNavigator and Darts-IP.

This data is then combined on both a per patent and per package basis, using tools we have developed over the last five years. The result is a proprietary database of hundreds of thousands of records across nearly 500 fields. These tools are programmed in SQL, R, Ruby, AppleScript and VBA using ODBC to retrieve up-to-the-minute live data from our database. We also use business intelligence tools such as Tableau. We continue to expand our capabilities to sort, sift and visualise the data.

We also internally track asking prices, bidding dates and clients’ specific diligence decisions and maintain a list of unique entities which are buying and selling with standardised names. We even classify these entities by entity type which means we have our own internal list of companies we believe to be NPEs. Though this process is quite time-consuming, we believe that using real data to back up our conclusion is the best way to provide accurate analyses to our clients and lower the barrier to entry for companies joining the market.

Brokers with five or more packages

Figure 2. 2017 broker sales rates by number of listed packages – brokers in the green circle are doing better; brokers in the red circles are experiencing challenges

Figure 2. 2017 broker sales rates by number of listed packages – brokers in the green circle are doing better; brokers in the red circles are experiencing challenges

The total number of brokers this year remained consistent with last year at 56 (last year, the figure stood at 54). Two years ago, when there were 74 brokers, we predicted that some would leave the market and that the concentration of packages across brokers would increase; this did happen, but the number of brokers seems to have stabilised. On average, brokers listed 9.9 packages each, up from 8.7 last year. This year, “for sale by owner” listings have also decreased and now account for 5.9% of the packages on the market. It is possible that some private buying programmes, such as Allied Security Trust’s IP3 programme, are forming a larger share of the marketplace for individual inventors who do not use a broker.

While the number of brokers has remained fairly consistent, the concentration of market share has continued to skew towards a handful of them. A small group of brokers continues to bring the majority of the packages to market: 14 brokers brought 10 or more packages to market, up from 11 brokers last year. This year 83% of the packages were brought by brokers who listed five or more packages (up from 78%). The top four brokers accounted for 50% of listed packages, which is a large increase from 41% last year (35% in 2016). It is unclear how much further the market share can concentrate.

As in previous years, we see little technology specialisation among brokers, with the exception of some brokers affiliated with semiconductor reverse-engineering houses and others that focus more on hardware.

Figure 2 shows the relative success of individual brokers (each broker being a dot). The X-axis represents the number of packages brought to the market during the measurement period. We used the 2017 calendar year for this analysis in order to allow sufficient time for sales to close and be recorded. The Y-axis represents the sales rate or closing rate for that broker (how many packages sold). Up and to the right is better. As shown in Figure 2, there were a few brokers who were particularly successful (green circles) or unsuccessful (red circles). Unlike last year, one broker who brought a large number of packages to market was able to sell those packages at an above-average sales rate.

Simply put, selling patents is not easy, but some brokers are having more success than others. Of packages listed in the 2017 calendar year, 13.5% have sold, showing an increase from last year in the same timeframe (10.9%). When looking across multiple years, overall sales continue to climb (see Figure 3). The sales volume for the 2018 market year is significantly above average. (Note our 2018 market year runs from June 2017 through May 2018.) And, the number of sales occurring in 2018 may grow further due to delays in the recordings of assignments (second quarter of 2018, in particular). The best sales quarter since we began tracking the market was easily the third quarter of 2017 (the second quarter of the 2018 market year). We will discuss sales rates in further detail below and continue now by looking more at the 2018 market year.

Other market opportunities

Figure 3. Actual sales by market year of sale

Figure 3. Actual sales by market year of sale

There continue to be new ways to buy or sell patents, some combining the current skills of brokers with platforms, with others being completely new models:

  • IAM Market is a market provided by IAM where sellers can list their patents and anyone can browse the packages, contact the sellers and close patent purchases.
  • IP3 by Allied Security Trust (AST) is a fast-close patent buying programme run by AST. Sellers list their assets for a set price and AST member companies decide whether to purchase, all on an accelerated schedule.
  • UP3 by Uber Technologies is a programme similar to IP3 but run by Uber.
  • Provenance Asset Group sells exclusive licences to patent families from a large pool of patents Provenance controls. The licenses are annual and allow companies to counter-assert against large corporate patent asserters. Provenance is also selling a large number of packages (2,300).

None of the packages listed through these programmes were included in our overall dataset. IP3 and UP3 are private buying programmes. The IAM Market data and Provenance’s packages for sale were included in Figure 1 but were excluded from any further analysis – as were any large packages (200 or more assets).

Packages

Figure 4. Worldwide distribution of assets from 2018 market year

Figure 4. Worldwide distribution of assets from 2018 market year

At 591 packages (502 last year), listings have increased by 17.7%. The only year in which we saw more listings was the 2016 market. If the assets from Provenance Asset Group were included in these numbers, the numbers would show an all-time high. The number of total assets and of US-issued patents also increased (see Table 2). We have benchmarked our deal flow with that of other large corporations and defensive aggregators and have found that the number of brokered packages we received is generally similar, so we are confident that our numbers reflect the market. Compared to previous years the total number of US-issued assets listed in packages increased twice as fast as the number of packages listed. Notably, the total number of assets listed increased even more than the US-issued assets. This signifies the continued importance of international assets and an elevated level of focus on elements of a package other than US-issued assets. However, US-issued assets are still the focus in most listings (see Figure 4). While we limit the types of package included in this dataset to the more common types (eg, quasi-public/brokered packages containing 200 or fewer assets), we also track larger bulk deals and private deals.

Figure 5. Package distribution by technology group

Overall, the market continues to provide packages that are relevant to a diverse range of technologies, products and focus companies. With a healthy number of varied packages, there are assets available to fill business needs in almost any high-tech category. When we receive a package, we use the package materials – and any asset highlighted by the seller – to categorise it according to our taxonomy of technical areas. We have developed a two-tiered classification taxonomy with 18 general technical categories and 108 sub-categories, which we continue to modify as new technologies come onto the brokered market.

As illustrated by Figure 5, the distribution of general technologies continues to skew towards software. There has also been significant growth within certain software technologies, including increased listings relating to the Internet of Things, internet-scale data management, and content and consumer software such as video and image processing. Additionally, for the first time, the ‘other’ category has now overtaken hardware as the second most common category. This is due to increases in listings in a variety of different areas and increased diversity in technologies listed. Last year there was a rise in listings in the energy and automotive sectors including solar-power, charging, autonomous driving and connected cars; and these areas continue to be popular. This year, we are seeing significantly more medical device packages and some moderate increases in imaging packages.

Table 1. Brokers listing five or more packages 2018 market year

Adapt IP Ventures
AQUA Licensing LLC
Blackhawk Technologies LLC
Dynamic IP Deals LLC
Huang Partners IP Advisory
ICAP
Iceberg
IPInvestments Group
MiiCs & Partners
Ocean Tomo LLC
Quinn Pacific
Red Chalk Group
Reliance Capital
Rui Zhi Ventures Limited
Tangible IP
TransactionsIP LLC
Tynax

Table 2. Brokered patent market contents

Market year201820172017-2018 % change
Packages59150218%
US issued5,4984,09934%
Total assets9,9946,99143%
Figure 6. Word cloud of hot companies, technologies and products

Figure 6. Word cloud of hot companies, technologies and products

The word cloud in Figure 6 provides another way to visualise the focus of the brokered patent market. The relative size of the words highlights the hot companies, technologies and products identified in the summaries of EOUs provided as marketing material from the broker or seller of the packages. Focusing on the word cloud, one gets a sense of how most packages were marketed in the 2018 market year. It should come as no surprise that the biggest technology companies (eg, Microsoft, Apple, Samsung, and Google) continue to be the favourite targets of patent sellers’ EOUs. For the second straight year we have seen an increase in references to Facebook, which is now as prevalent in EOUs as the others. Additionally, we are seeing more references to Chinese companies such as Huawei and ZTE, thereby highlighting the importance of these companies globally. Finally, there is an increase in the prominence of the terms ‘3GPP’ and ‘LTE’; we have seen twice as many wireless infrastructure and standards listings as last year.

Table 3. Asking prices in the 2018 market

Asking price $Top and bottom five data points from each set removed 2018
 Per assetPer US issued
Average$123,000$176,000
Median$83,000$143,000
Minimum$13,000$16,000
Maximum$500,000$675,000
Standard deviation$107,000$143,000
Numerical data403395

Package sizes

The distribution of package sizes (see Figure 7) has historically been one of the most consistent attributes of the brokered market. This year we have observed two interesting traits. For the first time, single-asset packages are the largest group of packages on the market at 27%. Despite this, the slow and steady shift to smaller packages seems to have reversed. This year, 63% of packages contained 10 or fewer assets. This reverses the trend we have seen in the previous three market years where the numbers rose from 66% to 69%. Despite the reversal, the 2018 market still focuses on smaller packages that are more marketable. Further, there was a fall in the percentage of packages in both the two to five and six to 10 asset ranges, as well as an increase in all of the package asset ranges larger than 10. It appears that the marketing strategy for sellers may be moving towards listing either extremely small packages or slightly bigger packages that may appeal to more buyers. Alternatively, this could be representative of the increased focus on marketing the international counterparts thereby listing more assets when filing was done in multiple jurisdictions. We will continue to monitor this to determine whether any new trends appear. Despite the increased percentage of single-asset packages, the total number of assets listed increased significantly due to the number of larger packages. This increased the average number of assets per package in 2018 to 16.9. Although this is the highest average package size we have seen since 2013, the median package size is still only five assets.

Additionally, Provenance Asset Group has listed more than 2,300 single-family packages for sale – the IP3-style programmes, designed by the buyers, also tend to focus on smaller packages. So, the trend towards smaller packages does appear to be consistent across both buyers and sellers.

Figure 7. Distribution of package sizes (total assets)

Pricing

In any market, pricing is where the rubber meets the road. As a buyer, you will not be taken seriously if you significantly underbid, yet you want to get a fair price. Conversely, if you are a seller who will not negotiate near the market price, it will be almost impossible to close a deal. We understand that patents are definitionally unique, have varying relative strengths and market applicability, and also that the demand for patents varies by technology area and many other factors. However, when it comes down to it, you have to start somewhere. This is where average pricing statistics become useful. To every seller who says: “My patents are not average, so average pricing should not apply to me,” we respond by saying: “We will accept that as true, you just have to show us why.” In the vast majority of cases, starting with the average price and moving up or down from there is an effective way to set a price for buyers and sellers.

Figure 8. Per asset price by package size

We believe that the availability of pricing data creates liquidity in the market and that the more visibility there is into pricing, the easier it is for new and established participants to take part in the market. The average asking price is a guide, not an absolute rule. We have helped clients buy patents priced at around $1 million per asset, which is well above the average market price, and have also negotiated deals for a small fraction of market price. In both of these cases we think the prices were justified. Importantly, the deviation from the average was supported by business models, market data and other factors that were specific to that deal.

In 2018, the average price per asset shifted significantly, falling by 30%, from $176,000 per asset to $123,000. The asking price per US-issued patent also dropped by 30% from $251,000 to $176,000. If you are a seller and these were the only facts you had, it would look like it is time to panic. But this is not the whole story. The fall was primarily due to an adjustment in the asking price for single-asset packages. For most package sizes, the asking price did not change at all. Figure 8 shows the asking prices per asset across packages of different sizes. In the 2017 market, there was a massive premium on single-asset packages. In 2018 the price for single-asset packages dropped by 56% and came more into line with the pricing for other package sizes. This drop in single-asset prices accounts for 48% of the overall drop in per-asset prices. The asking price in the 26 to 50 asset range also dropped significantly, while the price for packages of between six and 10 assets went up.

Additionally, among the single-asset packages listed in 2018 that have already sold, a small subset have an average asking price of $272,000 as opposed to $129,000 for unsold, a price difference of $142,000 per asset. In 2017 that price difference was only $56,000. It appears that buyers are still willing to pay a premium for some single-asset packages, while sellers have dropped the price on others where they could not reasonably support the premium.

Figure 9. Distribution of package asking prices (top and bottom 5% removed)

Our takeaway from this pricing data is that the premium for single-asset packages seen in all of the previous market years has fallen rapidly, possibly as a result of increased interest in international counterparts, which single-asset packages do not have. This price drop also caused standard deviations in the asking price per asset to drop by 24% (to $107,200) for per-asset asking prices and 23% (to $143,100) for per US-issued assets, thereby normalising pricing data further.

Figure 9 shows the distribution of asking prices. The data shows a continued focus on packages priced between $250,000 and $2 million; 60% of packages fall into this range, down from 69% last year. Here, brokers are able to be profitable, as packages are sufficiently expensive for them to make a significant commission while still keeping purchases within buyers’ budgets. But we also see a large increase in the sub-$250,000 listings, which corresponds to the drop in single-asset package prices that now fall into this price range.

We also continue to track the sub-$250,000 price range separately; we began doing this three years ago. This price range is interesting in that it represents low margins for the brokers. Assuming a 25% commission for brokers, a maximum $62,500 commission is possible for these packages. Additionally, when one takes into account the overall low sales rate of packages (more on this below), the margins look thin, which is prompting brokers to find ways to lower their costs.

EOUs were delivered for only 13% of packages priced at or below $250,000, in contrast with 61% of packages priced above $250,000. In the 2017 market those numbers were 44% versus 50% respectively. Brokers are spending much less on the marketing of these lower-priced packages than in the past. In buying these types of packages, we advise clients to scale down the resources used in diligence and negotiating the patent purchase agreement, unless the buyer has significant plans for the patents (see below for further discussion of EOUs).

Packages with pricing guidance

We saw that 76% of packages came with pricing guidance, down from 78% last year. We believe that pricing guidance clarifies expectations for both buyers and sellers. Additionally, 48% of packages with pricing guidance had precise asking prices; this is up from 34% last year. Clear pricing guidance helps buyers to make decisions – without guidance, the risk of no decision (meaning no sale) is higher simply because the seller is signalling a potential lack of understanding of where the market is.

Figure 10. Average asking price per asset by technology group

Per-asset pricing by package size

We analysed the interaction between pricing guidance and the number of assets in a package (see Figure 8). On average, asking price per asset drops significantly as the size of the package increases – from $172,000 all the way down to under $19,000. This is consistent with last year’s data, although the fall-off is far less without the single-asset premium. Last year, the smallest packages were asking $384,000 and the largest packages $17,000 per asset.

If you are a seller, in most cases it makes sense to take the time to find and highlight key patents and to group those into smaller packages in order to increase the overall price per asset (Figure 8). However, this can be time consuming if you have a very large portfolio, while breaking up a group of patents into smaller package may leave a pile of unrelated, undifferentiated and, ultimately, unsellable assets. In these specific cases, bulk packages may provide a better selling opportunity. This calculation continues to be difficult and benefits from up-to-date knowledge of the market and in-depth knowledge of the specific portfolio. If you are a buyer and presented with a bulk package, do not assume that you have to accept the package as is. It is likely that the seller will allow you to cherry-pick assets out of the bulk lot, although the price for such differentiated assets may go up. When approached by a buyer looking to purchase one family from a large lot, we have seen sellers say that they have a minimum package price to make a deal worthwhile. In these cases, the parties often add assets to the deal in order to make the price per asset palatable to both sides.

Figure 11. Importance of sequencing patent buying by diligence

Asking price by tech category

Technology categories continue to drive asking price variations, but less so than in the past. We are starting to see technology areas fall into the category of ‘selling or not selling’ rather than price adjusting. When it comes to top asking prices, software has regained its throne as the top pricing area and ‘other’ has dropped from the top price down below hardware. But overall, there is less price variation between hardware, software and ‘other’ technologies than in previous years. Notably, communication packages have fallen farther behind that pack. The lowest priced tech category was imaging, demanding only 39% of the average asking price. Financial patents had the highest asking price at 170% of the average.

Surprised? So were we. Last year, the automotive category demanded 365% of the asking price per asset. As with other factors, it appears that the variation in price across technology categories is decreasing.

Alice-affected technologies

Sellers never stopped listing Alice-affected technologies, but the price for technology areas relating to internet computing finally dropped to market average in the 2017 market. That drop – combined with buyers getting over their fear of Alice – created a boom in sales relating to these technologies (discussed further in the sales section below). Due to increased sales, the per-asset asking price for these technologies in 2018 is back to a 10% premium above the market average, $135,000 versus a market average of $123,000. In 2017 the price was $177,000, which was effectively the market average of $176,000.

Package purchasing diligence prioritisation

The goal of this process is to identify the 1% to 2% of patents with high value to a particular buyer’s business needs – the thin sliver of green in the furthest left column of Figure 11. The first diligence stage tests the package for general technology fit (eg, automotive safety systems). The entire brokered patent market is subjected to the test, and the majority will fail. The area in stage 1 with a red X signifies a large part of the market that is immediately eliminated. Patents falling into the area with the check move on to the next stage of diligence and can be seen expanded in the stage 2 column. Stage 2 tests if the technology described is something of specific interest to the client (eg, follow distance and automatic braking). In order to avoid falling into an expensive quality analysis, at this stage buyers should ask themselves the following: “If I assume that the patent is perfect, would I actually want to buy it?” The answer is “no” about 70% of the time. Again, the area with the check moves to the next diligence stage.

The process continues with multiple diligence phases and two more rounds of diligence. Quality analysis does not enter the process at all until this point, after most packages have been eliminated. Stage 3 includes inexpensive tests such as remaining life of the patents, bid due dates and pricing to eliminate even more packages. Finally, in stage 4, expensive diligence is applied to around 3% of the overall market.

Asking price and impact of EOU

As discussed above, there are ways that a seller can show that their package should fetch a higher price than average. EOUs are a great way to do that. Overall, the percentage of deals with EOU was consistent, with 42% in 2018 versus 43% last year. And we observed a 43% price premium over the average for packages with a seller-supplied EOU. This is the largest premium we have seen. We also know that sales rates are much higher for deals with EOU so the value of writing an EOU is compounded. We did not see a premium for EOU packages last year, but we did all other years, so we believe 2017 to be an anomaly.

Key diligence data

When discussing potential patent purchases with buyers, we find the phrase ‘low quality’ used to broadly characterise rejected patents unhelpful and push buyers to be more specific. We often hear that there are junk, low quality or weak patents on the patent market. Clearly, there are some patents that we can objectively agree are low quality, just as there are in most portfolios. However, buyers with an efficient buying programme should never test the majority of patents for quality metrics (eg, enforceability) simply because this is too expensive. Sophisticated buyers create targeted buying programmes rather than general ones. When buying, you should have a use case in mind and analyse the value of the patents in that particular context. If you want patents to counter-assert against Qualcomm, do not waste time and money evaluating clean-energy patents. The quality of anything in the clean-energy area is irrelevant.

Buyers also tend to conflate quality and value when discussing packages. A package with no value to you for your particular business use should be rejected from your buying programme – again, this is not a comment on the quality. It is easier and cheaper to reject a patent for lack of value that to analyse it for quality. Necessarily, a well-run buying programme has visibility into the quality of only a small set of the available packages on the market – it will have no visibility in the quality of the remaining packages because they were rejected before any quality metrics were evaluated.

Based on our data, a small percentage of all packages on the market will fit a company’s specific business needs. We have proposed that this highly concentrated distribution of value in the patent market is different for each buyer and has a lognormal distribution, an extrapolation of Suzanne Harrison’s analysis of multiple corporate patent portfolios in her book Edison in the Boardroom.

Based on this assumption, we have created a tiered diligence process (see Figure 11) to highlight the importance of eliminating ill-fitting packages quickly.

Table 4 shows the specific reasons that our clients gave for passing on packages when using the diligence process described in the sidebar. Before we present a package to our clients, we perform the stage 1 and some of the stage 2 analysis from Figure 11 and only present packages with technology fits and matching the client’s specific buying programme metrics. Therefore, for our clients, the diligence process starts in stage 2.

Assuming that a package passes through the initial technology filtering, the number one reason for passing on a package in the next stage is that it does not fit the client’s specific buying criteria (56%; 25% last year). These buying criteria are usually factors such as a minimum requirement for years of remaining life, a specific group of unlicensed companies or a requirement for a German counterpart. This type of criteria can be applied as a light diligence step and can be performed with fewer resources than later stages. The next two reasons for passing require a bit more diligence. ‘Evidence of use fails to map properly’, 15%, requires the manual review of claim charts, while ‘actual market adoption is too small’, 14%, requires evaluating the market adoption of the technologies described in the listed packages and confirming they were not broadly adopted. These two categories, along with ‘unresolved prosecution concerns’ and ‘unresolved prior art’, are the most expensive diligence categories. They account for approximately 30% of the failed diligence at this later diligence stage, but because they are applied at the end of the filtering process, they are only performed on 5% of the packages on the market. Many packages can be filtered out before our clients even see the assets. This saves time and money in the diligence process.

If you are a new buyer, you might have thought that pricing or the timing of bids would cause a lot of issues. However, these factors rarely cause problems. Pricing tends to be more rational, especially when a broker is involved. Additionally, the market is still relatively thinly traded so although there is an advantage to bidding and closing early, early bidding is not critical to success (it is a good practice). Buyers know that the price and due dates are typically fluid and that good communications on both sides can help here.

Table 4. Reasons for passing on a package where there is a good technology fit

Reason for passing after performing technology filteringScaled % of 2018 marketScaled % of 2017 market
Client-specific buying criteria56%25%
Evidence of use fails to map properly15%18%
Actual market adoption is too small14%36%
Pricing8%7%
Remaining asset life is too short6%7%
Unresolved prosecution concerns1%1%
Unresolved prior art0%3%
Bids are due too soon0%2%

Sales

The number of transactions continues to grow. We tracked more transactions last year, 191 packages sold, than we have seen in any previous market year. In the 2017 market year 125 packages transacted – our previous high-water mark was 2015 with 160 packages transacted. Additionally, we see sales of older packages exceeding our projections. For example, we are still seeing sales from packages listed in 2012 – 30% of the asset’s life is over and they are now just selling. Generally, highly sought-after packages move fast, followed by a long tail of additional sales. As a seller, patience can pay off.

Figure 12. Cumulative sales by years from package listing

We began tracking sales in order to avoid presenting already sold deals to our clients. We wrote code to parse the USPTO assignment data and to identify deals that were no longer on the market. This enables us to analyse what was selling and who bought it. Our methodology considers a package to have sold if at least one patent in that package is found to have an assignment corresponding to a sale. We then use the execution date of assignment for the earliest transacted patent in the package as the date of the sale (data is limited to packages received by 31 May 2018 and to sales recorded with the USPTO by 15 August 2018). When discussing sales, we switch to a different dataset which includes 3,251 packages, with 797 identified sales, and is measured on a calendar year basis. This sample set includes packages that were analysed in our previous papers and goes back to packages listed as early as 2011.

Our sales rate for 2017 listings within a year of listing currently stands at 13.9%, which is higher than last year’s rate of 10.3% for the same period. Both the number of sales from 2017 calendar listings and the number of sales regardless of listing year are up from last year’s data. Taking this into account, we predict the sales rates of 2017 listings to be higher than the rates observed for 2016 (Figure 12). We estimate that for 2017 listings the sales rate for packages on the market for one year will be approximately 15%. We also created a projection of the future sales for 2017 listings for an additional two years. Additionally, we observed older sales that we had not predicted. An additional 0.54% of packages listed in 2014 sold this past year, and a few packages sold from earlier years. This suggests that buyers are reviewing a back catalogue of deals as their buying needs change. The ability to do this is a sign of sophistication and a good sign for the market as a whole.

Please note that due to the time from listing to sale, all sales data lags behind the listings market by 18 months (and potentially longer).

Figure 13. Cumulative percentage of sales by months from receipt date (2017 listings)

Sales by package size

We analysed the sales rate based on the size of the package listed and found that with the exception of a spike in sales among packages in the two to five asset range, the larger the package, the more likely it was to have sold (see Table 5). The sales identification methodology skews towards identifying sales of larger packages because if any asset in the package sells, the package is considered sold. This year, the sales rate of packages correlates to the package sizes more so than other years. This implies that cherry-picking assets from larger packages is likely occurring more often. However, if package size was the only driving factor, the sales rates should be much higher for large packages. A package with 50 assets is nowhere near 50 times as likely to sell as an individual asset package; therefore, buyers are still generally focusing on assets in smaller packages. Using this framework, packages in the two to five asset range continue to sell extremely well, with the rate of 11% (same as last year).

Figure 14. Percentage difference between Alice-affected sales rate and total market sales rate

Sales by receipt date

When buying a package, it is an advantage to move quickly. We know that corporate decisions include a lot of sign-offs, which take time. So, how fast do you need to be? We analysed how quickly the sold packages listed in the 2017 calendar year transacted in order to estimate how much time buyers have to bid. We may be hitting the limit of how fast companies can reasonably source, do diligence and negotiate a deal, but buyers were able to increase their speed slightly over last year. Figure 13 show that 80% of the sales from that for 2017 listings occurred between six and seven months from the receipt date of the package (down from just over eight months last year). But the fastest movers were not able to pick up the pace; around 44% of the packages sold in the first four months (up from 40%). Accelerated decision making continues to be an advantage. If it is possible, getting a budget for patent purchase pre-approved by the board can help you to buy quickly and get access to the widest variety of packages.

The numbers above only look at 2017 calendar year listings, which have had at most 18 months on the market. As time moves on and additional packages sell, the earliest sales will definitionally make up a lower percentage of the total sales. When we look at an older dataset, 2014 listings, we see that 58% of the sales occur in the first year. While moving fast is still important, there is also a long tail of later sales showing that a slow trickle of sales exists for years after packages are listed. As buying programmes become more sophisticated and as more tools are used to analyse the market, it is becoming easier to act fast and to re-examine packages when buying criteria changes. A quick flurry of buying and review occurs on new packages, followed by a slower second wave of sales starting around 18 months after listing.

Sales by EOU provided

This year, we continued to see an increased sales rate for packages which have a seller-provided EOU: packages listed in the 2017 calendar year with EOUs were 51% more likely to sell than packages without. We hear buyers say that the broker EOU is not helpful, but the data suggests otherwise. It acts as a reality check that the technology is adopted. These EOUs also act as a guide, directing potential buyers to the value drivers, and identifying the applicable technology and product market. By combining the increased likelihood of a sale and the 43% sales price premium associated with EOUs (discussed above), the expected value of a package with an EOU is more than twice that of packages without EOUs (116% greater).

Life after Alice

Alice-affected software and financial packages are back. As discussed above, the prices rebounded but the sales rates have also rebounded above the market average. As can be seen in Figure 14, packages from Alice-affected technology categories listed in 2016 are 48% more likely to sell than packages in the overall market. The trend has continued to a lesser extent for 2017 listings, at 26% more likely to sell. It seems that the broader fear of Alice has subsided, but when we look at the tech area most likely to be affected – fintech – it is a little less clear. While fintech now has the highest asking prices, the sales rates vary widely; 2016 listings were 60% more likely to sell, whereas 2017 listings were 18% less likely. We will continue to monitor this technology area to see if a trend emerges.

Table 5. Sales rate by package size 2017 listings

Number of assetsSales rate – 2017 listings
16%
<=511%
<=109%
<=2519%
<=5022%
<=10028%
<=20038%

Sellers

As a buyer, tracking the behaviour of sellers – both in aggregate and individually – allows you to operationalise your buying activities. This is especially true for repeat sellers, who account for 41% of the transactions for packages listed in calendar years 2017 and 2018. Knowing who the regular sellers are, often companies with a large portfolio, allows you to contact sellers to create a private deal. Keeping track of a seller’s listings, package sizes and asking prices can also help you in negotiations because you know their negotiation parameters at the outset.

Table 6. Repeat sellers (sold in 2017 or 2018)

Sellers
Aaron Emigh
Alcatel Lucent
Allied Security Trust (AST)
ATT
Bell & Howell, LLC
Clifford Sweatte
Concert Technology
Foxsemicon Integrated Technology, Inc
Hewlett Packard Enterprise (HPe)
Hewlett Packard Inc (HP Inc)
IBM
Intel Corporation
Intellectual Ventures
IP Cube Partners (ICP) Co, Ltd
KT Corporation
Mirai Ventures LLC
MITRE Corporation
Nokia Communications Company
Panasonic Corporation
Pendrell Technologies
Seiko Epson Corporation
Sony Corporation
Xerox

Similarly, if you are a seller, it is important to get out the word that you are selling. Listing packages on your website, through the IAM Market, or working with brokers attracts buyers to you rather than you having to spend the time and effort to find them.

For the analysis of current sellers, and buyers, we are analysing all of the packages that that sold between 1 January 2017 and 31 May 2018 (assignments were last checked on 15 August 2018) regardless of their listing date. Sales continue to be made mostly by operating companies, which is not surprising as they file the majority of patents. Operating companies were the sellers in 67% of transactions. This is remarkably consistent at 66% in the previous two papers.

Last year’s analysis had 20 repeat sellers accounting for 42% of the sold packages; this year, 23 repeat sellers account for 41%. These sales also accounted for 53% of sold assets and 54% of sold US-issued patents – down from 56% and 62%, respectively, last year.

Figure 15. Distribution of seller type by sale year 2016-2017

Figure 15. Distribution of seller type by sale year 2016-2017

Similarly, if you are a seller, it is important to get out the word that you are selling. Listing packages on your website, through the IAM Market, or working with brokers attracts buyers to you rather than you having to spend the time and effort to find them.

For the analysis of current sellers, and buyers, we are analysing all of the packages that that sold between 1 January 2017 and 31 May 2018 (assignments were last checked on 15 August 2018) regardless of their listing date. Sales continue to be made mostly by operating companies, which is not surprising as they file the majority of patents. Operating companies were the sellers in 67% of transactions. This is remarkably consistent at 66% in the previous two papers.

Last year’s analysis had 20 repeat sellers accounting for 42% of the sold packages; this year, 23 repeat sellers account for 41%. These sales also accounted for 53% of sold assets and 54% of sold US-issued patents – down from 56% and 62%, respectively, last year.

Figure 16. Distribution of buyer type by sale year 2016-2017

Figure 16. Distribution of buyer type by sale year 2016-2017

Buyers

Buyers are the natural counterparts to sellers. Just as buyers should track sellers, sellers benefit from tracking buyers. Additionally, buyers who track buyers can gain a competitive advantage by knowing what other operating companies of concern (including competitors) are actively buying in the market.

Like last year, the percentage of packages purchased by NPEs has increased and they have retaken the title of largest buyers at 42% of packages, up from 36% last year. Defensive aggregator purchases seem to have followed and increased their buying share to 19%, up from 13% (see Figure 16). Operating companies, on the other hand, have decreased their buying and now make up only 37% of the purchases, down from 47% last year.

Even though NPE buying activity increased, Intellectual Ventures’ (IV) buying dropped to two packages. This likely completes its buying wind-down, as the number of packages it has purchased on the brokered market has decreased from 40 to 13 to 6 in the previous three years, and IV has announced that it has stopped its buying programmes. It is noteworthy that NPE purchases increased despite IV terminating its buying programme.

During this period, 138 buyers purchased 261 packages, while 30 buyers purchased multiple packages (see Table 7). Last year’s analysis had 34 repeat buyers accounting for 57% of the packages purchased; this year 30 repeat buyers accounted for 59% of the packages purchased.

Provenance Asset Group, Uniloc Luxembourg SA and Uber Technologies, Inc purchased a combined total of 18% of the deals. Defensive aggregators AST and RPX Corporation slowed their open market buying, though each purchased 4% of the packages. Like the rest of our analysis, these numbers include only the brokered patent market and do not include private purchases.

Table 7. Repeat buyers (sold in 2017 or 2018)

Buyers
Akoloutheo, Llc
Allied Security Trust (AST)
Blackbird Tech Llc
Brunoco, Inc
Cria Inc
Didi (Hk) Science and Technology Limited
Etsy Inc
Fiver, Llc
Fluence Automation Llc
Google Inc
Innobrilliance, Llc
Insight Interfaces Llc
Intellectual Ventures
Jlp United States Patent Solutions, Llc
Knapp Investment Company
Nokia Communications Company
Open Invention Network, Llc
Pathunt Ip Management Limited
Prosper Technology, Llc
Provenance Asset Group
Red Dragon Innovations, Llc
RPX Corporation
Samsung Electronics Co, Ltd
Scenera Technologies, Llc
Servicenow, Inc
Spectrum Patents, Inc
Uber Technologies, Inc
Uniloc Luxembourg SA
Wi-Fi One, Llc
WSOU Investments Llc

Litigation

For operating companies, the brokered patent market represents a large pool of litigation risk. Purchased patents do not sit unused. Of the packages that sold, 16.3% had at least one US patent litigated after the listing date. While some of the increase from last year’s 14.3% rate can be attributed to more time having passed for older packages, it appears that the litigation rate of brokered market sales keeps going up. Additionally, 91% of the sold packages that were litigated after the listing date were litigated by an NPE and the average number of NPE filed litigations for these packages was 11.4 lawsuits. It is important to note that we only have visibility into filed cases and that the numbers do not include private assertions and licensing deals that were settled before litigation was filed. Overall, NPE litigation campaigns regularly use patents bought off the brokered market.

Rates of inter partes reviews for sold packages have similarly increased. Sold packages were six times more likely to be reviewed after listing than unsold packages. Not surprisingly, if the patents were litigated, the patents were subject to an inter partes review 33% of the time. Sold packages are being asserted and inter partes reviews are the tool for punching back.

This year, in order to analyse international litigations, we worked with Darts-IP. They helped us to search over 14,000 international assets from the brokered patent market dataset and found that only 15 patents were litigated across 16 litigations. These litigations were spread out across six jurisdictions – Canada, China, Germany, Spain, Japan and at the EPO. Possible reasons for the much lower litigation rates relative to the United States include:

  • far fewer international patents are transacted;
  • individual market size and impacted revenue are lower; and
  • loser-pays rules in many other jurisdictions may lead to greater caution in bringing a suit.

Litigation trends may change rapidly as China’s patent system continues to mature and if the European Union moves to a unitary patent.

For those interested in changing the balance of negotiations, the international assets make a greater difference today than they did five years ago. Our clients regularly ask about international assets. However, with relatively low litigation rates, it is still too early to predict what will happen with these assets.

Table 8. Litigation and inter partes review frequency

 Litigations (2012-2018 market year packages)Inter partes reviews (2014-2018 market year packages)
Package typeBefore listing dateAfter listing dateEverBefore listing dateAfter listing dateEver
Sold packages6.6%16.3%21.1%0.8%6.0%6.8%
Unsold packages3.9%3.9%7.0%0.4%1.0%1.3%
All packages4.6%7.0%10.4%0.5%2.2%2.7%

Full market size

Despite falling average prices, this year the market grew fast. We estimate the 2018 market size to be $353 million, up from last year’s estimated $296 million. The 2016 market slump (estimated $165 million market) is, hopefully, a thing of the past.

In order to make this estimate, we use the observed sales that occurred in the 2018 market year and used their actual asking prices to determine the market size. As is consistent with the previous two years, if no pricing guidance was provided, the average asking price per asset for the market year of the sale (eg, $123,000 for 2018 market year sales) was multiplied by the number of assets to determine the expected asking price. In the 2018 market year 210 sales were identified, accounting for a total asking price of $527 million. Due to recordation delays, we assume that we have not yet seen 3% of the sales that occurred in the timeframe, so we multiplied this total asking price by 1.03 before applying our standard 35% discount between asking price and expected selling price. Thus, our expected total market size for the 2018 market is $353 million, indicating that the market has increased by 19% since last year and 114% since the 2016 market.

Table 9. Summary of the data

Summary of 2018 results
Annual sales$353 million
Asking price per US-issued patent$123,000
Asking price per patent asset$176,000
Package sales rate (cy projected)23%
Number of people employed as brokers181
Sold package litigation rate (tt)16.3%
Unsold package litigation rate (tt)3.9%
All package litigation rate (tt)7.0%
Packages listed591
US-issued patents5,498
Patent assets9,994
Average number of assets per package16.9
Median number of assets per package5
Packages with 10 or fewer US-issued patents63%

As a check on our methodologies, we looked at the updated sales data to recalculate last year’s market size. We now calculate the 2017 market to have been $299 million, as opposed to our estimate of $296 million in last year’s article, confirming our approach to estimating market size.

By applying an average commission rate of 20%, the revenue from this market for brokers is $54 million per year (we eliminated ‘for sale by owner’ listings). We dropped the average commission rate from 25% last year to more accurately represent the types and structure of packages listed this year. By estimating the average loaded labour rate per broker ($300,000 a year), we calculated that there are 181 full-time equivalent employees working as brokers. Assuming that three brokers work in each brokerage, this results in approximately 60 brokerages. Our data shows 56 brokerages that listed packages in the 2018 market.

Action plan

When buying patents:

  • state the business case for buying – identify the specific problem that you are trying to solve;
  • model a return for your buying programme;
  • arrange your buying operations to reflect that over 90% of the patents will not fit your needs – eliminating those patents from consideration early will greatly reduce your costs; and
  • operationalise your buying programme as much as possible – this is becoming more common and is, therefore, more important for all buyers.

Programme parameters include:

  • timeline – packages that are selling continue to sell quickly;
  • budget;
  • buying team authority and responsibilities;
  • buying criteria;
  • listing of acceptable sources of patent packages; and
  • special requirements, such as a whitelist of unlicensed companies.

The following is a fail-fast triage process for eliminating undesirable packages quickly:

  • Extract criteria from the business case to identify interesting markets and technologies, and then define the diligence needs.
  • Undertake a multi-part analysis of markets, technical knowledge and legal analysis where a failure in any one area eliminates the package from further review.
  • Track basic information about your programme so that you can learn from your past.

Tips for bidding and buying:

  • Build a valuation model to determine a maximum bid price.
  • Assume that diligence will take longer than planned.
  • Consider adding a consulting agreement with the inventors if they are available.

Opportunities, conclusions and reflections

Two years ago, the cover of IAM Magazine showed a beaten boxer stumbling to his feet, representing a patent market struggling to recover from the brink of disaster. With asking prices down 30%, each punch is no longer as strong as it was. But the boxer is nimbler and with 53% more transactions than two years ago, he is landing a lot more punches. The overall market grew by nearly 20% this year and is more than double our 2016 estimate. As the market continues to mature, our fighter has had to become more versatile and adaptable. Litigation continues to increase for sold assets and, in response, so do inter partes reviews. Brokers continue to sell patents, some at a much higher rate than others. NPEs are still buying. EOUs still matter. With the increasing importance of international assets, he may have even started training as a southpaw.

We can confidently say that the market is moving forward and operating well. The market continues to change and transform. For those, like us, who participate in it, we will continue to take our punches (eg, lower prices for single-asset deals), but there is more than enough fight to win. Further, the benefits of multiple years of greater pricing transparency are starting to show, with the standard deviation in prices contracting again this year. With more data at our disposal we can rely on analysis and prepare ahead of time using data analytics, diligence optimisation and strategy development. Our overall advice is not that far from that of a boxing coach: if you want to win in this market you have to put in your hours at the gym.

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