LTV Overview

Launching Technology Ventures (LTV) is a second year MBA course at Harvard Business School designed for three types of students interested in the Internet, mobile, and enterprise software sectors:
  1. Those who will join startups (typically in a PM, biz dev, sales, marketing or growth role)
  2. Those who will work at large, established tech companies (in a similar range of roles)
  3. Those who are interested in starting their own companies

The course focuses on the pre-product market fit stage of a technology startup. Through case studies and conversations with startup founders, LTV will examine management challenges in early stage startups and the range of experiments that are conducted during this phase of development, such as:
  • Customer Value Proposition Experiments. How to determine whether a startup has achieved product-market fit and how to avoid premature scaling? What are the right analytical techniques to derive insight into product-market fit, such as cohort analysis and churn analysis? How can modern, flexible product development techniques, such as agile and continuous deployment, be utilized to enhance the chances that product-market fit can be achieved. 
  • Go to Market Experiments. When should a seed stage startup recruit its first sales professional and what hiring criteria should they use? What is the right mix of direct and indirect selling efforts and at what phase in the startup's lifecycle should each be employed? How can founders themselves be the most effective sales engine for an early stage company, even though it clearly does not scale as a go to market approach? What is the optimal mix of different customer acquisition methods, such as growth hacking, SEO, SEM, email and affiliate programs? How can a team protect the startup's interests in the face of asymmetric bargaining power with powerful partners? What are the best practices for attracting and managing developers who can leverage a platform's API?
  • Business Model Experiments. When is the best time to trigger monetization experiments and how should a freemium model be best executed? What are the different pricing and business model approaches that a startup can take, particularly when trying to deploy an innovative model and drive adoption in the context of a network effect-based business opportunity?

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