Pirate Metrics for Product Marketers: How to Apply a Growth Framework to Feature Adoption
If your feature adoption is growing too damn slow, take note. You’ve got one of two problems:
- You built a feature nobody wants except you (you solved an interesting technical problem instead of a real customer problem)
- You built something people genuinely want but you’re not sure how to rev the growth engine
How do you solve problem number 1? Go talk to your customers.
How do you solve problem number 2? Pirate metrics, matey.
Dave McClure, 500 Startups founder, and all around growth master, needs no introduction. And, neither does his legendary growth framework, Startup Metrics for Pirates. But here’s a brief overview in case it’s not something you’ve crossed paths with:
Customer Lifecycle
Acquisition: Users come to your site from various channels
Activation: Users enjoy 1st visit
Retention: Users come back, visit site multiple times
Referral: Users like product enough to refer others
Revenue: Users conduct some kind of monetization behaviour
Cool. Simple enough. AARRR, like a pirate. Funny.
In practice, this framework applies well to growing a product as a whole—helping you move a ton of people from site visit, to sign up, to product usage, all the way down to $$$, while optimizing along the way.
But, can we apply this to your current customers and a new product feature?
How to get people to use the features you build
Acquisition
In general, acquisition, as defined by McClure, focuses on external acquisition channels: SEO, SEM, Paid, Social, PR, Biz Dev, and even TV ads (whatever those are). These channels are perfect for pulling in net new users to try a product. But, they make a lot less sense, strategically and fiscally, when you’re trying to grow feature adoption amongst your existing customers.
I mean, yeah, people buy products because they have features, and presenting those features when you present your product as whole is a no brainer. But, this is a super long-tail, roundabout way to grow feature usage—kind of backwards, ya know?
If you’re trying to get your existing customers to try a new feature, you’re better off acquiring them by getting in their PATH.
Strategic turnoffs, like exit ramps on your user highway, are the fastest way to acquire users and get them into your new feature’s funnel.
Here’s how it works:
Generally, people follow a path, some predefined set of interactions each time they use your product. Maybe it’s login, home screen, inbox, logout, in the case of a simple email app. You need to advertise your new feature in those places—get in their path.
Triggered email, blog posts, in-app notifications and banners are examples of how to get in a user’s path without destroying your UX.
Triggered emails: When a user completes an activity that in some way relates to, or creates a condition where, your new feature can solve a problem or make their experience better, trigger an email. This is about proper timing and proper messaging.
Blog Post: Tell people the feature exists. Duh. Announcing new features in blog posts has consistently given Shopify the biggest boost in new feature adoption.
In-app notification and banners: Same as triggered emails, timing and placement are key.
Notes for Google Analytics users: To understand the acquisition part of your funnel, you’ll need to rely heavily on UTM parameters (email and blog post CTAs) and Event Triggers (Notification and in-app banner CTAs) to understand your traffic.
Can paid ads play a role?
This depends on something that will get addressed in “Revenue”, if the feature is a paid feature or if feature adoption increases LTV by reducing churn, paid can play a role. Retargeting your customers with the feature announcement blog post, for example. Might be worth it—who knows?
Activation
Activation is similar whether you’re trying to 🚀 product adoption or feature adoption. Product activation might be an app download and an account signup, generally preceded by an “Ah-ha” moment, think Facebook’s famous “7 friends in 10 days” metric. Whereas feature activation might involve more granular interactions, like completing setup steps, followed by first feature use—whatever that might look like.
The fact that feature activation and product activation don’t differ that much leads to an interesting idea: Treat new features in the same way you would treat new products. They have their own funnel, their own datasets, their own UVP, and their own messaging. Launch them like you’d launch a brand new product.
What your activation funnel might look like:
- Spends x time on feature page in-app (understanding)
- Clicks x elements on that page (interaction)
- Completes feature setup (if applicable)
- Uses feature for the first time
Google Analytics notes: This is absolutely the right time to apply event triggers to important elements and draw out your funnel—check to see where people are falling out. Are they spending less time on the page than it takes to understand the feature? Your UVP might be weak, the page might be confusing, or whatever the case may be. Does everyone fall out of the funnel at a specific setup point? It might be confusing or unnecessary.
Retention
Building on the idea of “feature” as “product”, feature churn can, and should, be analyzed in the same way you would analyzed product churn—day 1, day 7, day 30, x times used—whatever makes sense for your product.
Do your customers continue to use the feature every day, week, or month? Do they drop off after first usage? After what point does churn become negligible?
Answering these questions informs your retention strategy—lifecycle emails, for example. When should you send them? What should they say? And, how do you get your users to the tipping point, the point at which their unlikely to churn out anymore (i.e. when they start to see the REAL value of your product).
Here’s an example of a retention email you might send:
Send a monthly email reminding customers of the value they get from your product. If your feature saves someone money or time, tell them exactly how much money or time they have saved this month.
Referral
Referral is interesting. Building a referral engine into your product as a whole makes sense, and is a huge part of ensuring the continued growth of your product—think Candy Crush and their annoying Facebook notifications. Getting referrals for a feature, however, is a bit different.
Do you get your customers to refer other customers to try a feature? Would they? What would that even look like? How do you incentivize that?
It’s a bit of a weird concept.
The other option is to use this stage of your customer lifecycle to start the Feedback Flywheel.
The Feedback Flywheel involves asking your current customers for feedback, taking their ideas and words, and then feeding it back into your acquisition funnel in order to get more people to try the feature.
Here’s a simple approach (courtsey of Sean Ellis):
- Pull the emails of all the customers that have tried the feature and split them into two groups
- For the first group create an open-ended survey
- Ask how your customer would feel if they could no longer use the feature. Anyone who answers “Very sad” is a “must have user”
- Ask your must have users what they think your products key benefit is and why it’s important, why they used the feature (intent)
- Take their open-ended responses and bucket them into multiple choice
- Survey the rest of your customers using the multiple choice survey
- Use their answers to refine your messaging and feed that back into your acquisition strategy
That was a lot of bullets. Go read the article to get the full picture.
Revenue
At this point in the funnel, a user should be generating some sort of revenue, usually a minimum, break even, and then surplus. When trying to grow a paid product, this is pretty easy: does the user actually pay for your service and does what they pay cover their cost of acquisition.
Measuring the revenue for feature usage isn’t always as easy. Most features are free to use once you sign up for a product, unless they’re only available on increasingly expensive plans (which does simplify the revenue model).
Let’s talk about free features (because it’s more interesting).
Calculating the revenue from feature usage can involve examining the overall affect the feature has on PRODUCT churn. Do customers stay longer after using the feature compared to those that don’t use the feature? Here’s we’re looking at features as a way to increase LTV.
Find the difference between previous LTV and new LTV and use that as your feature revenue. And then you can check your minimum, break even, and surplus revenue from the feature.
Final Review: Breaking down an example funnel
Here’s an example feature adoption funnel using pirate metrics and everything we’ve discussed:
Acquisition: visits feature page in-app
Activation: Spends 40 seconds on feature page
Activation: Clicks an element that starts the setup funnel
Activation: Completes setup (if applicable)
Activation: Uses feature for the first time
Retention: Uses feature five times in one month
Retention: Hits product adoption tipping point
Referral: Fills out survey
Referral: Is a must have user
Revenue: Hits minimum LTV increase to cover acquisition cost
Revenue: Passes LTV break even point and starts producing a return
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(Product Marketer? Come work with me at Shopify)
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