David Smith, Chief Data Officer at TheVentureCity – Interview Series

David Smith, a.k.a “David Data,” is the Chief Data Officer at TheVentureCity, a venture capital platform that invests internationally in software-driven startups and provides operational support.

Could you describe your role as the Chief Data Officer at TheVentureCity and what this entails?

I lead a team of people that evaluates investment opportunities using data provided by startups; manages live data pipelines from our portfolio companies and the tech stack that supports them; conducts bespoke analysis for portfolio companies; advises portfolio companies on tech stacks and analytics; and builds products that automate and extend our analytics capabilities.

When performing investment due diligence what are some of the variables that are considered?

We evaluate engagement, retention, customer lifetime value, revenue distribution, and growth dynamics, and compare them to industry benchmarks. To do this we get user-level event and transaction data to measure:

• Average days active in the last 28; 
• month-over-month user and revenue retention; 
• 6+ month user retention; 
• month 12 net revenue retention; 
• cohort-level user retention and customer lifetime value; 
• marketing-spend payback periods; 
• monthly user and revenue growth rates and quick ratios (which measure growth efficiency); 
• revenue distribution across the customer base;
• And perhaps other metrics particular to a given case.

The weighting of how much we consider each metric listed above depends on the situation. 

For VCs what is the most important is how fast a company can scale, what are the most important metrics to identify this?

The most important metric is retention, both user and revenue. Retention can be measured several ways: month-over-month or after 6 months for a longer term view. Good retention signals product-market fit and makes efficient growth possible. It’s much easier to grow if you don’t have to replace most of your users from one month to the next. If you have a product in a large market that fits with that market and can grow efficiently, you are poised to scale quickly.

Could you share some details on the Growth Scanner, a tool to help founders know how well they’re growing?

Growth Scanner allows any founder with a product in market to get an assessment of product-market fit and growth effectiveness. We turn raw data provided to us by the startup into a report that presents the metrics described above, their industry benchmarks, and commentary from our team. We’ve looked at hundreds of startups this way and know what to look for and highlight. By looking at their business through our growth accounting lens, founders frequently learn something about their business that they didn’t previously see.

Venture capital firms are notorious for still using Excel and other antiquated methods to organize investment data, how does TheVentureCity tackle this challenge?

We have invested in our data team and its stack to automate the ingestion and transformation of product and transactional data from multiple sources into a standardized analysis framework.

How can VCs leverage good data to take a more personalized approach to working with startups?

The granular product data we get from our portfolio startups allows us to understand exactly what’s happening with each company. With such data at our fingertips, we can go beyond our standard dashboards and dive deep into the data where necessary. We’re able to have very specific conversations with our startup teams around what the data is saying and how to proceed.

With hallucinations being one of the most significant downsides of using Generative AI, how should start-ups that are reliant on LLMs tackle this issue?

They should hire the right people that know about curating high quality training data, fine-tuning and validating the model, and human-in-the-loop approaches. 

What is your vision for the future of AI and how VCs will invest in the space?

We should expect to see exponential advancements in AI capabilities in general, and transformer driven models in particular, for the foreseeable future. We will go beyond making current products and processes more efficient, and start learning about new products and processes that were not possible before.

Thank you for the interview, readers who wish to learn more should visit TheVentureCity.