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    Date submitted
  • 24-May-2018

Hugo Analytics

Abstract

HUGO Analytics leverages empirical methods and advanced data analytics to improve litigation outcomes. We apply social science insights and experimental testing to determine, rapidly and rigorously, what litigation strategies are most likely to succeed, value cases and help select jurors.

Our partners - three nationally recognized experts - began their collaboration publishing cutting-edge research in peer-reviewed academic journals. Attorneys, mediators, and judges quickly saw the value and began demanding services for pending cases

Additional Questions

Who is your customer?

We have two immediate types of customers, law firm trial attorneys and in-house counsel managing litigation. In the near future, we hope to begin persuading courts to adopt our tools for ADR purposes. Further down the line, we are considering whether to customize our tools to allow for self represented litigants to engage in a limited form of jury trial.

What problem does this idea/product solve or what market need does it serve?

Trial attorneys rely on myths, intuition, focus groups, and questionnaires, but these methods are slow, costly and, statistically speaking, useless. We can rigorously test trial tactics and value cases using crowdsourcing.

What attributes will make this idea/product successful? Why do you believe that those features will create success?

We execute randomized experiments, the most rigorous type of evaluation. We then deploy modern analytic techniques to understand the data. Our solution is scientifically more accurate, substantially less expensive and faster than traditional jury consultants.

Explain how you (your team) will execute to make this idea/product successful? What gives you (your team) an advantage over others already in the market or new to this market?

Our team is exceptional. It comprises three of the leading researchers in this nascent field. Collectively we have authored dozens of peer-reviewed papers; our work has been extensively covered in the media; and we have experience running experiments with hundreds of thousands of people. Our challenge is to scale without sacrificing the high quality analysis we provide.