How do you validate your deal screening assumptions?

1 Data sources

The first step to validate your deal screening assumptions is to find and use relevant data sources that can support or challenge your hypotheses. For example, you can use market research, industry reports, customer surveys, competitor analysis, and historical performance data to assess the size, growth, and attractiveness of the market and the startup's position in it. You can also use online platforms, databases, and networks to find and compare similar or complementary deals that have been done or are in the pipeline. Data sources can help you benchmark and validate your assumptions about the startup's traction, valuation, and potential return.

2 Feedback loops

The second step to validate your deal screening assumptions is to create and use feedback loops that can help you test and refine your hypotheses. For example, you can use your network, mentors, advisors, peers, and experts to get their opinions, insights, and perspectives on the startup and the market. You can also use your portfolio companies, customers, partners, and suppliers to get their feedback on the startup's product, service, and value proposition. Feedback loops can help you identify and address the gaps, risks, and challenges in your deal screening assumptions and improve your decision-making process.

3 Experimentation methods

The third step to validate your deal screening assumptions is to apply and use experimentation methods that can help you verify and measure your hypotheses. For example, you can use pilot projects, trials, tests, and experiments to evaluate the startup's performance, scalability, and sustainability. You can also use metrics, indicators, and benchmarks to quantify and track the startup's progress, impact, and outcomes. Experimentation methods can help you validate and demonstrate your deal screening assumptions and increase your confidence and conviction in your investment.

4 Assumption mapping

The fourth step to validate your deal screening assumptions is to organize and use assumption mapping that can help you prioritize and focus on your hypotheses. For example, you can use tools, frameworks, and templates to map out your assumptions based on their importance and uncertainty. You can also use categories, labels, and colors to group your assumptions based on their type, source, and level. Assumption mapping can help you visualize and communicate your deal screening assumptions and align them with your goals and criteria.

5 Validation process

The fifth step to validate your deal screening assumptions is to design and use a validation process that can help you manage and optimize your hypotheses. For example, you can use stages, phases, and checkpoints to structure your validation process based on your deal flow and timeline. You can also use feedback, data, and experiments to update your validation process based on your learning and results. Validation process can help you streamline and standardize your deal screening assumptions and ensure their quality and consistency.

6 Validation mindset

The sixth step to validate your deal screening assumptions is to develop and use a validation mindset that can help you learn and improve your hypotheses. For example, you can use curiosity, openness, and humility to question and challenge your assumptions and seek new information and perspectives. You can also use experimentation, iteration, and adaptation to test and refine your assumptions and respond to changes and feedback. Validation mindset can help you foster and embrace a culture of validation and innovation in your deal screening and investing.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?