Data, Distribution & Deals: How Money Is Made In Legal With Tech

Data, Distribution & Deals: How Money Is Made In Legal With Tech

Data, Distribution & Deals: How Money Is Made In Legal With Tech 1792 1024 Raymond Blyd

Around $40 Billion of business supporting legal relies on copyrights, complexities, and expensive distribution. Now that’s all in jeopardy.

TLDR: This is twice our usual length, so if you’re in a hurry, skip to the Recaps and Daybreak.

Premise: Any business needs a model for making money. A tech company model is to use software to solve problems and then sell this solution with a profit. The problems in legal usually involve complexity. So the business models for legal involved finding and fixing complexities. Now, this is tricky: Finding complexities in legal with tech is very lucrative. Fixing them, not so much. Well, guess what happened?

Data

Based on 2022 annual revenue, the three biggest companies supporting legal work arguably are:

  1. RELX (owner of LexisNexis) – $8.55 Billion;
  2. Thomson Reuters (TR) – $6.63 Billion;
  3. Wolters Kluwer (WK) – $5.45 Billion.

That is $20.6 Billion of revenue for 2022. They did not achieve this staggering feat overnight. Each company was founded in the late 1800s. They achieved gradual growth by accumulating essential legal content. Two key factors drove their model: Copyright on content and competency requirements for legal professionals. In essence, they monopolize the data that lawyers need. Eventually, RELX, TR, and WK diversified their product portfolio away from legal. Yet, the legal market made this model sustainable for over a century.

Historically, distributing legal data was expensive because it required printing on paper. The printing press was owned by publishers and allowed the monopoly. Lawyers also have a monopoly on legal work, which allows them to maintain complexities. For these reasons, the legal industry could keep raising prices and making profits. This flywheel effect resulted in ‘legal inflation‘ and years of wealth in the legal market.

Distribution

Non-Legal Data

With the internet and cloud, the distribution of legal data got cheaper. More legal professionals got smarter research portals and e-Discovery platforms for non-legal data. In particular, e-Discovery platforms managed enough revenue growth to go public. Here is a list of the ones we’re tracking:

  1. Open Text$3.49 Billion;
  2. Palantir$1.91 Billion;
  3. KLDiscovery$317.43 Million.
  4. Information Services Group$286.27 Million;
  5. Intapp$272.07 Million;
  6. Model N$219.06 Million;
  7. Nuix$152.31 Million;
  8. CS Disco$135.19 Million;
  9. Fronteo$73.17 Million;

That is $6.8 Billion of revenue for 2022 and remember that their revenue streams are also diversified. Why e-Discovery is the biggest cohort is due to a craze, we experienced in the early 2000. The Exit and Funding videos show this historic rise and fall in graphic detail. We’ll spare you the legal drama some encountered during their public run. Same for the earnings per share (EPS), an indicator of profitability.

Other Legal Data

Primary legal data monopolies prompted others to search for secondary legal data. They focused on areas like Practice, IP, Billing, and Government. Here are some we track that support legal professionals:

  1. Constellation Software$6.62 Billion;
  2. Dye & Durham$474.81 Million;
  3. PEXA$279.84 Million;
  4. Clarivate$2.66 Billion;
  5. Upland Software$317.30 Million;
  6. FiscalNote$113.77 Million.

That is $10.4 Billion of revenue for 2022 and about 60% goes to Constellation. Bear in mind, that Constellation has a bunch of businesses under their umbrella. So pure legal is a considerably smaller piece of this revenue pie. PEXA deals in real estate legal transactions.

Other Legal Stuff

Most of the models above rely on catering to legal professionals. Hence, they have slow but steady growth. Now, newer models offer faster growth. To achieve fast growth, you need a faster deal flow. Faster deals happen when you can cut out the middlemen. Therefore, these models did not sell directly to the profession, they sold to the business. Marketplaces, Tax, Cookies, and e-Signature were designed as a direct-to-legal-consumer business. Their model used the ‘land & expand’ method for growth. Here’s a list:

  1. Docusign$2.11 Billion;
  2. LegalZoom$619.98 Million.

That’s $2.7 Billion. All of the above is $40+ Billion in revenue for 2022, and we would be generous to say it is all legal. All links go to Google Finance so you can check, and track it yourself. Most stocks are trading way below their initial public offering. Meaning, they are not doing as well as expected. Hopefully, by the time you read this, they’re doing better.

Will there be more? We’re tracking about, 1033 private companies. They have raised more than $20 Million in total from investors. In June 2022, Clio announced it had reached $100 Million in annual revenue. Based on our calculation, Clio is not the only ‘Centaur’. We see a couple doing Tax or Cookies that should be near $100 million. Nope, Contract Tech isn’t there yet. Unfortunately, their outlook is not rosy either. Check out Deals and Daybreak to see why.

After decades of ‘innovation’, and about $118.58 Billion invested, just seventeen joined the traditional three. In any case, the rest have three options: raise again, get acquired, or go public. They can stay private forever if they have profits. Profits come from growth and growth comes from Deals. So what about Deals?

Deals

We did not include a list of publicly traded law firms, Reg Tech, and Tax Tech. Most law firms are doing well. How well? Twitter’s M&A lawyers effectively charged $122K an hour. While this may seem excessive, it represents just 0.2% of the $44 billion price tag paid by Elon Musk. These deals rely on connections or an effective M&A prospecting tool. In Capital & Conflicts, we addressed dynamics that drive deals in legal. Those dynamics were driven by the demand for legal solutions. Now, we have a supply issue. Specifically, an oversupply of legal solutions, and here is the cause.

First, large language models (LLM) will break data monopolies. Meaning, that all data will eventually disappear in a LLM. Most hope for some kind of copyright or regulatory arrangement. Well, search engines ignore copyright and cookie policies basically broke the web. Note Sarah Silverman’s AI copyright infringement lawsuit against Meta stumbled. In general, monopolies do not work well for consumers. Moreover, the main LLM providers offer a copyright shield. So regulation will be futile. This brings us to our second and bigger concern.

We enjoyed cheap internet and cloud to distribute our solutions to customers. Now we’re getting these expensive chip clusters to run LLM’s. Before, we only needed to write code and distribute it. Copilots are different. The biggest shift is that generative pre-trained transformers (GPT) will intercept most end-user interactions. There are only three Interceptors currently capable: Google, Microsoft, and Apple. They have the chips, brains, and devices to capture all questions. And they will monetize it, too. Due to these additional costs, legal solutions become more expensive. This will further dampen demand and deals. This decrease in demand and increase in supply is a perfect storm.

Daybreak

In 2020, we wrote, “Will lawyers be replaced by GPT? Yes“. Wonder why Sam was fired from OpenAI? Read the second sentence in ‘Universe Three‘ from the analysis. Well, if we saw that coming, here’s what we see next:

  • Transformers will vaporize copyrighted data monopolies;
  • GenAI will fix most legal issues they intercept;
  • Interception will not come as cheap as code and cloud;

Curious, who is eagerly funding Interceptions? Investors made their VC Legal Copilot so they may not be allies. GenAI is the new printing press, and no legal tech company owns a printer. That is why we called the Casetext acquisition a bargain. To protect $6.6 Billion in revenue, a $650 Million investment (9.8%) is reasonable. Not realistic but reasonable.

What Are Legal Agents, And The Next Stages Of Legal Services


Image Courtesy: DALL·E 3 by OpenAI based on the content of this analysis.

Close Cart
Back to top
Privacy Preferences

We created a unique video to explain our privacy policy. We hope more would follow in our footsteps. Meanwhile, feel free to reject or accept any of the settings below. 

Click to enable/disable Google Analytics tracking code.
Click to enable/disable Google Fonts.
Click to enable/disable Google Maps.
Click to enable/disable video embeds.
Our website uses cookies, mainly from Google. Check our unique privacy policy video to learn more.