Growth Product Management

The roadmap process is no different from any other product manager. They work closely with marketing, engineering, design, and data science to create the roadmap. There are sprints & prioritization processes for all features. They are focused on continuous experimentation and learning - which is an input into the prioritization process. 

By far the best material you could read to learn about PLG has nothing to do with PLG. PLG is based off of the Scientific Method you learned in grade school. Go back and reread the fundamentals of how to go through the Scientific Method. Lessons around experiment design/methodology are highly valuable and should not be glossed over. There are other parts though that are more focused around experiment logistics and team dynamics that the Scientific Method won't cover. But in my opinion, a good book around logistics is "The Goal" by Eliyahu M. Goldratt. I unfortunately don't have any recom...

A traditional product manager is responsible for a specific set of features and functionalities in an application. They focus on building the functionality with great UX. A Growth Product manager looks more end-to-end and identifies opportunities to deliver incremental growth. Let's take an eCommerce website application. A feature product manager might be responsible for the checkout experience. They will be thinking more about building capabilities in checkout (like supporting new payment types). A growth product manager will take more of an end-to-end customer journey perspective and thin...

Great question.  1. One important piece of knowledge is that EVERY PM is responsible for having a growth mindset. Growth PMs are NOT the only PMs responsible for growth.  2. Growth PMs are defined differently from company to company, and some companies don't have titles called Growth PMs. The most common Growth PM team that I've seen is usually responsible for user acquisition. This means they own the product features that help users have a smooth onboarding experience.  3. Sometimes the responsibilities go deeper in the growth process where they are responsible ...

I've wrestled with this over the course of ten years now. I used to think Growth PMs and Core PMs should just be one in the same and every Core PM should be able to do Growth work. However, I don't really believe that anymore. From my experience, there's a place in the business to do optimizations (Growth) and a place to do exploration (Core) work.  Core PMs generally have a stronger skillset around taking big bets which require a lot of coordination and patience. Growth PMs require high analytical acumen and rapid development, but much smaller bets, and not as much coordination. 

Growth product teams are primarily responsible for incremental revenue in consumer applications. They are also accountable for internal metrics that directly correlate to revenue. Examples would be engagement metrics on a page, conversion metrics, user acquisition, retention metrics etc. It's hard to define the most critical metric. A lot of that depends on what the growth team is responsible for. Incremental revenue is a good metric a growth team should own.

Personally, I've always used pirate metrics. * Acquisition - Getting the user to sign up * Activation - Getting the signed up user to realize the value of the product * Revenue - Getting the user to pay for the product * Retention - Getting the user to stick around * Referral - Getting the user to refer someone else to sign up These are solid high level metrics to measure the overall effect of a team. However, when running a specific experiment, these metrics aren't always the best to choose when measuring whether the experiment was effective. If you have a lot of traffic, then it's ...

This is a tricky question. Lots of program managers struggle with prioritization and impact analysis. They also struggle to get alignment on the prioritization across among the stakeholders. Some of the best program managers are good at understanding customer cohorts, their behavior on the application, and what they like & dislike. Not understanding customer behavior leads to bad (or gut-based) product decisions. Almost always, it comes down to first principles. Good product managers invest time learning the customer.

Avoid artificial growth! A good growth PM or a good PM, in general, will only look for sustainable growth opportunities. There was this one time at Yahoo when a bad growth PM said to me, "let's grow video consumption by auto-playing every video on every page." This is a horrible idea because you will grow video consumption at the expense of user satisfaction, and time spent. Doing these types of trade-offs is NOT "growing," it's "trading". A good growth PM would say "hmm let's find real opportunities where videos are not present but should be." 

The number one thing first time growth PMs get wrong is only focusing on wins and not involving their team. When creating a Growth squad, your number one enemy isn't not making the number bigger, it's xfn attrition. Designers and engineers who are new to Growth have historically been rewarded for releasing new features. When joining a Growth team, you have to be able to prepare them to launch something and then delete it. This is very new behavior and goes against what they are used to doing.  So what do you do? You have to redefine how they value themselves. Essentially get them to unle...

The areas I index the most when hiring someone: * Partial - Do they fall in love with their own ideas? If so, then I don't believe they will be a strong Growth PM. Given so many experiments fail, you want someone who is focused on answering questions about the user and the science of it all. * Analytical - They don't have to be a statistician, but they need to understand how to read the data and extrapolate user behavior from it * Collaborative - This is probably the most important part. A person shouldn't be hired based on their ability to generate good ideas. Even if th...

If you're trying to measure the results of an experiment, assuming they're under a binomial distribution, you just need the numerator and denominator (people exposed to the experiment) for the control and treatment. Then just throw it into your favorite chi square significance calculator (I'm a big fan of the Evan Miller calculator). In regards to other product tools, it's the same as usual. You can use Amplitude to look into user behavior. StatSig or Optimizely or all the other ones for running experiments. Really any out of the box feature flagging tool has experimentation capabilities.

I mentally use the ICE (Impact, Confidence, Ease) framework when prioritizing experiments. Impact = How many people does this affect? Confidence = How sure are you that this will work? Ease = How easy is it to implement? Impact and Ease are pretty simple to calculate. However, I find that most people don't know how to accurately assess "Confidence." This is likely because your ideation strategy consists mainly of throwing things at the wall and seeing what sticks. Or just working off of best practices. This strategy works well for the first six months to a year of an experimentation stra...

Ideally, you design experiments in a way that seek to answer a question regardless of the result. For example, "do users not adopt this feature because of discoverability or usability?" is a great question to be answered with an experiment. If the exeriment execution puts that feature front and center of the main page when a user logs in, and the experiment is flat, then you could be pretty sure it's a usability issue. If it's stat sig positive, then you can be sure it's a discoverability issue. What's important is what you do after you've identified this finding. This new information ca...

Good at data and insights Ability to identify growth opportunities Ability to quickly test hypothesis Ability to hack through and come up with exciting ideas (big & small) Relentless focus on execution & results Good at product design and User experience Strong team player as this is a heavily cross functional role

Off the top of my mind... 1. You MUST understand the difference between artificial growth and sustainable growth. For example, if you ran a publisher site like CNN, and your growth PM idea was to grow revenue by plastering the entire page with Ads, that's not sustainable. You might see revenue initially jump but your users will eventually leave your site.  2. Data-minded - you have to be comfortable with data and have the curiosity to seek more data.  3. Understanding digital marketing is a plus but not a must. You should know some common business sense like if y...