Growth Hacking for Litigation Support Services

on Business Intelligence and Development, Legal Data API, Legal Tech

Growth Hacking for Litigation Support Services

UniCourt as a Business Development Tool

In 2010, Josh Blandi discovered that there was a huge number of consumers who, while being sued by their creditors, really needed the kind of help his company CountryWide Debt Relief could provide. The trouble was that, back then, it was nearly impossible to track these consumers down. In the ensuing months and years Josh set out to develop a platform that could aggregate and organize court data and help him find consumers who needed help. This was how UniCourt was founded.

UniCourt has always been more than a tool for case research or for streamlining internal processes in law firms to help attorneys work together more efficiently on a case. UniCourt was designed to be a powerful customer development tool from the very beginning.

In this post, we’ll walk through how litigation support providers like court reporters can track down relevant court records and documents to use UniCourt for smarter business development.

Aggregating Actionable Business Intelligence

A court reporter seeking more corporate clients or more business from their current corporate clients should be using the following information:

  • In order to proactively offer their services, they need to know whenever a current client or potential client is involved in a lawsuit.
  • They need to know how often their current clients are involved in litigation over a given period, say the last quarter, last year, or the last five years in order to ascertain how frequently those clients are engaging them for court reporting services.
  • They need to know what law firms their corporate clients are engaging. These firms are potential clients. Law firms and lawyers will often employ their own court reporters rather than using a corporate client’s preferred vendor, as they prefer to work with court reporters they know.

Court reporters will also be interested in the litigation history of law firms that are current or potential clients. They’ll want to find out:

  • Which law firms are handling the largest volume of lawsuits in jurisdictions that are relevant to their court reporting business. What types of cases are those law firms handling, who are their corporate clients, and where do they overlap with the court reporter’s clients.
  • What types of cases are more likely to make it to trial. With this information a court reporter can target law firms that specialize in the most promising areas of law.
  • Which jurisdictions are most inundated with cases. Discovering which jurisdictions have the most active dockets will allow a court reporter to target the jurisdictions that are most likely to increase their market share.

Let’s Look at an Example

Let’s consider the simple example of a court reporter who wants to discover the most recent cases filed against Bank of America in the greater Los Angeles area. The first step would be to search for “Bank of America” through UniCourt’s simple search. Using UniCourt’s search filters to sort by jurisdiction, case type, and by a date range will allow a court reporter to narrow down their search so they only see the most relevant cases.

Even a simple search on UniCourt’s platform can deliver actionable business intelligence that a court reporter could use to find new clients or to pursue more business from their current clients. When combined with UniCourt’s Legal Data API, court reporters can further layer court data to match parties (corporations), attorneys, and law firms with their contact and accounts in their CRM system.

How UniCourt Works

UniCourt continuously aggregates both state and federal court data and utilizes AI technology to normalize and organize this data. Machine learning technology ensures that when a court reporter searches for a company like Bank of America they’ll also find data pertaining to Bank of America, N.A., Bank of America, a National Association, Banks of Americas, and many other variations of the company’s name that are likely to appear in court records. UniCourt’s normalization technology also clusters these variations together as a single entity, producing meaningful legal analytics and providing deeper insights into the parties, attorneys, and judges involved in litigation.

UniCourt’s search filters make it easy for anyone to find the precise court data they need without having to wade through extraneous records and data, while UniCourt’s scheduled search feature automates the process of finding relevant court data. A professional seeking new cases for business development will receive automated alerts whenever a new case that fits their search criteria is filed.

Business Development and Legal Tech

Law firms often focus on how legal technology can transform the way they operate internally, but what is less emphasized is how big data is providing solutions for more than just internal problems. While it’s true that UniCourt makes finding court records and documents and sharing research simple and easy, the platform was originally designed as a business development tool. UniCourt makes finding new clients easy and provides wholly new opportunities for client retention and increasing market share.

The development of machine learning along with the digitization of court records is providing litigation support professionals with a business growth hack. Using court data to keep track of potential and current clients is a key component for business intelligence and development.