The metrics you can’t afford to ignore: What the best CEOs know

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The metrics you can't afford to ignore: What the best CEOs know
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Join Gen AI enterprise leaders in Boston on March 27 for an exclusive night of networking, insights, and conversations surrounding data integrity. Request an invite here.

This week’s guest is so good I wish there was an 1-800 number to call him when I had questions on company building. Ray Rike is a founding member of the SaaS Metrics Standards Board. His team runs the industry’s largest SaaS benchmarking Index —  with 18,000 unique SaaS companies and more than half a million data points.

He is the person you should know if you want to run a business with high discipline, efficiency and reliability.

In this CarCast, we cover growth, profit, customer acquisition, churn metrics and the five metrics you need to know to be an exceptional CEO and operator.

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We cover

VB Event

The AI Impact Tour – Atlanta

Continuing our tour, we’re headed to Atlanta for the AI Impact Tour stop on April 10th. This exclusive, invite-only event, in partnership with Microsoft, will feature discussions on how generative AI is transforming the security workforce. Space is limited, so request an invite today.

Request an invite

The rule of 40

The customer acquisition cost (CAC) ratio

The CAC payback period

Net revenue retention (NRR)/ gross revenue retention (GRR)

The CLTV:CAC ratio

I go “Warren Buffet” on Ray by asking to give his top 10 priorities, then tell him “trash 2 through 10 and let’s focus on just #1”.

Finally, you might want to check out the 8 steps in the latest McKinsey and Company research regarding setting up your generative AI tech stack. They include:

1. Determine the company’s posture for the adoption of gen AI.

2. Identify use cases that build value through improved productivity, growth, and new business models.

3. Reimagine the technology function.

4. Take advantage of existing services or adapt open-source gen AI models.

5. Upgrade your enterprise technology architecture to integrate and manage gen AI models.

6. Develop a data architecture to enable access to quality data.

7. Create a centralized, cross-functional gen AI platform team.

8. Tailor upskilling programs by roles and proficiency levels.

Bruno Aziza is a technology entrepreneur.



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