Data-Driven Venture Capital
For the data is valuable and full of insights (GoT 2.0)
When I first founded the Value Creation team at Glilot Capital a year ago (wow, time flies!), I was certain that the most valuable support I can provide our startups with is creating meaningful business opportunities.
To do so, we have built a network of C-level executives from 900 organizations worldwide and have managed to introduce our 12 portfolio companies to over 400 enterprises in a few months, resulted in millions of dollars worth deals (not to mention the strategic partnerships and follow-on investors introductions).
Until this day, generating business opportunities is without a doubt our #1 focus area. However…
In the startup world, where closing enterprise deals is king, data is the undoubted Queen of Dragons (yes, I’m way too excited about the upcoming season of Game of Thrones).
You Know Nothing Jon Snow (Oh, if you only had the data..)
In a constantly evolving world, data is a key element that helps to proactively adjust your product-market-fit and sales strategy. Businesses today look at data as a cornerstone in both their strategic and tactical decision-making processes (not to mention it can help predict who’s about to die in GoT).
Similarly, as the amount of data from our Business Development efforts increased, we realized that the data we collect is not a by-product, but a real deal “dragon glass”.
We realized that this data, if analyzed correctly, can get us from the opportunistic hunch-based sales approach to a scalable, structured, and effective machine.
Therefore, we created detailed sales pipelines for each of our portfolio companies and started keeping track of EVERYTHING — from the qualitative feedback provided by potential customers, to the lead-to-sale conversion rates over time.
The vast amount of collected data has allowed us to get a clear, objective and in-depth overview of the market sentiment for each and every early-stage company. It enabled us faster and more agile improvement cycles for both the product and the sales process, and became a reliable tool for fine-tuning the pitch and GTM (using A\B testing analysis).
But practically speaking..
Here’s a more practical deep-dive on what we’ve done:
We have defined a structured process that will generate the most reliable and valuable insights, and thank god Dorin Baniel, our analyst, has joined the team right on time!
Step 1: We selected the best sales-oriented, data-driven CRM we could find (a stand-alone project that deserves a separate blog post) and personalized it to our needs.
Step 2: We defined the type of data that will generate interesting and valuable insights and quantified it.
Step 3: We built a methodological and structured process for collecting the data and implemented the process across the fund, so that every business interaction is documented and no data is lost.
Step 4: Data gathered, now the fun begins
Once we had a good, clean database with real-time data, we created automated reports for various use cases and needs. For example:
- Product-Market-Fit reports for the early-stage companies that consist of data, such as: type of customers that they should be focusing on (industries, size), feedback after A/B testing the pitch and more.
- Business Development reports for the late-stage companies, which consists of data such as: most common reasons for deal loss, conversion rates over time, etc.
- Value Creation Optimization reports to improve our team’s efforts including best reach out methods, lead-to-call conversion rates, the effectiveness of conferences we attended, etc.
Since this is all automated, once a company faces a business dilemma, we can run a report and get a data-driven recommendation.
Becoming a data-driven VC has helped us in optimizing our own resources and having a better understanding of market trends, but most importantly — it enabled us to provide accurate, scalable support and market-oriented advice for our startups.
We hope this gave you some food for thought. Feel free to reach out for more info: firstname.lastname@example.org or LinkedIn