Our internal data shows Claude is accelerating AI development—a possible path to recursive self-improvement, or AI autonomously building a more capable successor.
It’s happening faster than we thought, and the implications deserve greater attention. https://t.co/OVVPJO7VQx
Introducing two new ways to create with Claude:
A dedicated space for building, hosting, and sharing artifacts, and the ability to embed AI capabilities directly into your creations.
@thjmay Hey, thanks for reaching out. I think based on the date of the post I figured out which video it was. I reposted it here: https://t.co/TSySwldrdL Let me know if that is the right one.
Measuring product retention is easy 😌.
Improving it is hard 🥵.
Three analyses from @jwegan_com that helped Pinterest scale to hundreds of millions of MAU’s. 👇👇
John Egan spent 8 years on the growth engineering team at Pinterest and was most recently at Lyft. With each of these analyses, John and the team found a critical lever that helped improve overall retention for Pinterest.
Links to each artifact, the insights, and the surprise 😳 findings are below in the 🧵
🗺 Feature Retention Analysis 🗺
↳ Should you be driving more users to a feature?
↳Or should you steer the limited attention of your users elsewhere?
That is the fundamental question that Feature Retention Fit analysis helps answer. John says:
“I first learned this concept of feature-market fit from @onecaseman . It applies the same retention curve analysis to features that you’d do for a product.
We needed to understand whether this feature had reached “feature-market fit.” Were people using and getting value out of this feature regularly, or was it more of a novelty?”
📧 Cost of an Unsubscribe Analysis 📧
Notifications are a core lever to driving retention for many products. A few years into scaling Pinterest’s email program, the team was sending a dozen types of emails.
“We wanted to understand how unsubscribing impacted user retention. We needed to get some sort of feel for the cost associated with an unsubscribe to help us understand how many emails were too much, and how many unsubscribes were unhealthy”
✋ Churn Propensity and Intervention Analysis ✋
Finding the right intervention point to save someone from churning but also making sure it isn’t too late is tricky. John says:
“One of the primary questions we needed answered was, "When should we intervene to try and win someone back?" Ideally, you don't want to wait until someone's dormant and been gone for 30 days. Your chances of winning them back at that point are low.
But a very active user might still be in danger of churning after a few days of inactivity, whereas a light user might not churn after that same number of days inactive. So I was trying to understand, by usage, after how many days of inactivity should we get worried?"
More below ⬇️
New blog post:
How to design a referral program
https://t.co/Nak1D8WASE
- how did these programs become so popular in apps?
- what's the structure of a referral program?
- how do you optimize the ask, the incentive, and targeting?
- how do you judge success?
Details 👇
⚡️Excited to announce the full slate of 🍂Fall 🍂 @reforge programs ⚡️
14 cohort-based programs, build+led by top executives, focused on helping you learn, execute, and scale. New programs for Founders, Product, and Engineering
Full lineup -> https://t.co/NMCbszWJhO
👇👇👇
On June 15th Airtable is hosting a virtual meetup with a series of talks on user growth. I'll be chatting with @wendyluwho about scaling growth teams.
RSVP here: https://t.co/WEqt4ELWZf
Just published The Startup Guide To Managing Your Email Reputation (and avoiding the spam folder). Covers how to protect email reputation even at a scale of billions of emails per month.
https://t.co/4btPxS6msp
#email#GrowthHacking#startup#marketing
Finally getting back to blogging. This new post collects everything I've learned about product/market fit, including:
a handy chart to measure PMF more deliberately
an analysis of the common frameworks for building new companies
https://t.co/W15tmHhdJm
The Growth Engineering Meetup is holding our first virtual event with speakers from Pinterest, Lyft, and Coinbase. RSVP here: https://t.co/hTUgGTXQL6 #GrowthHacking#startups
In 2008 Facebook’s user growth hit a wall at 80M and we were having serious debates about whether any social network could ever reach 100M users. 2 years later we had doubled our user base and not long after that we reached 1B users. Here’s how we did it:
New post on @andrewchen’s blog about The Adjacent User Theory which was critical as I built @instagram’s growth team and we scaled to >1B users. Thx to @bbalfour@far33d@ElenaVerna for their contributions. https://t.co/ZGj9GavgdP