Finest-5 Product reads #34
Difficulty of simple products, North star metric, etc..
Let’s start with DALL-E 2, one of the most interesting things I came to know about this week. This amazing product from OpenAI is just mind-blowing. And to know the way it works is just a treat to any engineer.
Supercharging A/B Testing at Uber
Uber has evolved from an old system of experimentation to a new one that is more generalised, scalable and trustful. The journey and parameters are complex, but important to understand.
Carefully constructing the building blocks of an A/B platform and ensuring the data collected is correct is critical to guaranteeing correctness of experiment results, but it’s easy to get wrong
Over the years, feature flagging has become the norm and the experimentation system became a required dependency for mobile apps and backend services.
At its core, an experiment comprises 3 key parts: randomization, treatment plan, logs
The Difficulty of Building Simple Products
Great products hide their complexities well. On the surface, we see the user experience and know what the solution is capable of, but we cannot fully understand the work that went into creating the product or what’s powering it.
Finding the right balance is challenging, and too often we’re encouraged to ship something suboptimal just to get it out the door.
What sounds like simple logic for the user, ends up being a complex diagram of decision points for the company
When discussing complexity, we can talk about two types related to product development: the complexity for the company to build the product and the complexity for the user to use the product.
Don’t Let Your North Star Metric Deceive You
The name “One Metric That Matters”, sends the message that you only need to focus on one metric to build growth into your product. However, there are many caveats to it.
NSMs are output metrics, output metrics represent results and input metrics represent actions.
No metric exists in isolation. To truly understand how one metric impacts growth, you need to see its effects on other metrics downstream.
Select a constellation of a few key output metrics that capture the full dimensions of the business.
Beyond Amazon.com: Amazon-as-a-Service
Amazon recently announced a “Buy with Prime” option. A pure play of how microservices will allow people to use prime membership off amazon’s website.
Microservices is an architectural style that structures an application as a collection of services that are: Highly maintainable and testable, Loosely coupled, Independently deployable, Organized around business capabilities, Owned by a small team.
Amazon has modularised this whole offering to enable other participating websites and apps to provide Prime member benefits to Amazon prime members
Amazon will slowly become a central model for many services through its built-up infrastructure. This will further reinforce the Amazonian Moat.
Solving Retention With Loops
Scaling a product looks like a growth thing for most business owners. However, a major concern can be retention.
The best approach to excellent retention is to start with design and then optimize using analytics.
The 3 phases of retention:
Start: Onboarding and value (wow-moment) discovery
Middle: Habit creation and dormant user reactivation
End: Churn prediction and delay
To increase retention, some form of “lock-in” is added besides habit loops.
Product of the week: mockoops
Convert your boring screen recording into life-like mockups. Just drag-drop and export with a click.