E01 - How Google and Databricks scale (AI-driven) Product-Led Growth (PLG) | Jean-Mathieu Chabas

Jean-Mathieu Chabas (JM) is a Growth (Product) leader in Databricks. Previously, he led Google’s Ads $100M ARR Growth machine.

In this episode, JM shares lessons on how to build an algorithmic (AI-driven) growth engine to align between Product-Led Growth and Product-Led Sales, his approach to building rockstar Growth teams, and his journey to becoming an influential Growth Product leader.

My 15 learnings 🎓 from this episode:

1. At Google Ads (a $100B+ ARR business), Growth Teams operate by pulling the levers of Core Product and GTM. Growth Teams guide Core Product on what to build and GTM on which products to sell and to whom.

2. Google’s approach to ‘Growth work’ is algorithmic rather than manual. It’s 80% ML-based. 😎 Reaping the fruits of Google’s 20-year investment in its Ads ML model for 20 years.

3. The Growth guidelines of what to sell and to whom (per customer/segment) to GTM are packaged in a three-layer cake:

   1. Products that drive short-term success.

   2. Products that drive long-term success. [The highest priority 🟢]

   3. Foundational products.

4. GTM’s mission is to make customers successful by ensuring the adoption of the Ads products packaged in Growth guidelines (see above). GTM does so ( = driving Adoption) through PLG (in-product) and SLG (frontal sales). And, of course, GTM Incentives ($) are aligned accordingly!

5. The Google Ads Growth Flywheel:

   1. Driving ad products adoption →

   2. Campaign performance increases ( = customer is more successful) →

   3. Customers allocate additional budget to Google Ads, which leads to Adopting additional Ad Products. 💸

6. Customers want to spend (when there is an ROI-positive investment), and the Google Ads Growth team’s job is to provide them with enough ways to do so. Hence, if done correctly, Google Ads growth has no limits.

7. Google knows much better than any Performance Marketing agency how to create repeatable, high-performing campaigns at scale. Hence, Google is taking (and will keep taking) the campaign ‘Controls.’ One-click automation is how all of us will roll. 🤖

8. Only the best ideas win at Google. As a product leader, getting your opinion through the Google filter (all the way to execution) is an Art and Science. You have to learn how to do so to make it at Google. Otherwise, your impact will be limited. 😨

9. At Google, you are expected to have high GC abilities ( = Crystallized Intelligence). To do so, you have to continue working on self-improvement. Google will give you all the tools necessary, but it’s your responsibility.

10. Databricks follows the Google Ads approach to Growth Teams, meaning that Growth Teams pull the Core Product and GTM levers. Moreover, Databricks invests in building an algorithmic (rather than manual) growth engine, although it is quite early in its journey.

11. Databricks uses a ‘Propensity score’ to allocate customers the right support based on their propensity to spend money with Darabricks. The support level can vary from email to an in-product banner to a solution architect or senior seller.

12. At Databricks, PLG and SLG work together in sync. It’s hybrid all the way. Databricks thinks value first. ”We used to be commit-first, but this is not the case anymore. Our GTM has become much more efficient once we layered in PLG on SLG”.

13. I repeat myself, but this point comes a lot in this episode. Growth should be long-term, not short-term play: the next quarter ( = short-term), the next year (= long-term). 🤓

14. Leading Down principles:

    1. Allocate time with your team, think through problems together, and do it weekly.

    2. Genuinely support your team in achieving personal growth. 💡

    3. Place a high-quality level and operate transparently ( = we are all in the same boat).

15. Leading Up principles:

    1. You build credibility and trust by consistently delivering high-quality output. There is no other way.

    2. Leverage cross-functional leadership to strive for mutual wins and share those up.

In this episode, chapters 👀:

01:10 Jean-Mathieu Chabas background

04:45 The role of ‘Growth Product’ teams at Google Ads

23:15 The secret recipe for making it at Google

28:30 What Databricks is all about?

33:40 Shaping ‘Growth Product’ at Databricks

58:44 Leadership philosophy: Lead Up and Down

01:08:22 The quick questions round

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Where to find Jean-Mathieu Chabas?

• LinkedIn: https://www.linkedin.com/in/tomscottt/

Where to find Eugene Segal?

• LinkedIn: https://www.linkedin.com/in/ekaterina-syuma/

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