How to set adoption goals for a new feature launch
Still guessing when setting goals for new features? Here’s three strategies to set adoption goals you actually believe in.
50% of customers by next month? No problem. All you need is a miracle.
When you introduce a new product or feature, how should you pick goals for customer adoption? Let's say that "Overnight success" is not a good answer.
How do you set goals for a brand new feature?
When you make something brand new, making up metrics can feel like a guessing game. “We want to reach 500 customers within 30 days” – is this realistic? Unclear, but we still have to set goals (SMART or otherwise). This leaves product marketing and PM’s discovering how realistic these numbers are after launch.
You don't need a data science degree to pick a good adoption goal for the upcoming feature launch. Below are three simple strategies you can use at any stage. They will help you discover useful starting point for measuring success, without guessing.
Strategies and frameworks for setting product launch goals
Three frameworks to help you think about goals after your product announcement.
#1. “Day One” Eligibility (DOE)
Day One Eligibility is the maximum number of people who you can reach on launch day. It is how many people are on plans or have already set up prerequisites to use a feature. For example, if you have a new interaction in a Slack or Team integration, your eligible audience on day one customer adoption is everyone who already has one of those two integrations configured.
Eligibility doesn’t have to be the ceiling for your goals, but it should inform your ambitions. By framing as eligibility, you’re able to get straight to the point of “How many people can actually use this thing?” regardless of interest or awareness. If your eligible customer % is lower than expected, it might be time to change plan tiers or run a customer campaign to get folks ready for launch day.
Why segment by feature eligibility?
It’s easy to fall into a trap of thinking that a new feature will trigger excitement and finally spark the adoption of neighboring features (integrations, etc) once people see it. The ripple effect from feature launches is where growth marketing can shine, but DOE is one way to make sure you pick a useful starting point.
The reason why DOE is a useful input is that it anchors to the reality of how people already use the product. It is useful for launches that rely heavily on external integrations or gated for specific plan tiers (think: Free vs Pro vs Enterprise).
Example: A new feature requires your Enterprise plan, which represents 30% of your customers — the "day one eligible" audience. This is a way of focusing on 1st or 2nd order impact, vs. “This feature will cause people to upgrade, and then use it” which complicates the feedback loop by adding another variable – budgeting, timing, etc.
#2. Benchmarking performance vs best adopted feature
If your best adopted feature reaches 60% of eligible customers, you should think twice before setting a launch goal to reach 80% of customers within 60 days. This is the same as saying “This will be our best adopted feature of all time!” Before you ask someone to break a company record, it’s worth knowing what the most successful attempt has been so far.
Total customer eligibility will vary between features, so you may need to scale benchmarks (think: % of, instead of absolute #) to match the total eligible customers for your launch.
Example benchmarks:
Pacing: How long did it take for each feature to reach 10% of your audience?
Pacing: How many of your customers had adopted the feature within 30 days?
Total Reach: What’s the total adoption rate among eligible customers today?
Keep a leaderboard of new feature adoption. What’s the best feature you ever launched for total reach? Fastest to 10% of customers? Highest reach after 30 days? Not only does this celebrate success, it also gives you a sober benchmark for what’s proven possible.
#3. Early Adopters
Who will be the first 10 customers to adopt this feature? By describing traits of who you believe will be the earliest adopters, you can get a sense of your potential audience. It can also help you understand how to change your communication strategy to reach more folks and keep your product announcement simple.
Why focus on such a small group? It forces your team to be honest about who will be an initial adopter instead of who should or could use the new feature eventually. Be specific, and name likely candidates.
This exercise is also useful for identifying customers who WON’T be in the early adopters, and possible areas of improvement. Example: “We don’t expect customers with low mobile adoption to change their behavior because of this feature…”
Wrap Up
Each of these strategies can help find a useful target, while helping internal expectation management. Even if you have a brand new product, you can ground everyone in reality by asking the right questions. Remember to aim high and skew towards ambitious — people have a funny way of rising to the occasion.
50% of customers by next month? No problem. All you need is a miracle.
When you introduce a new product or feature, how should you pick goals for customer adoption? Let's say that "Overnight success" is not a good answer.
How do you set goals for a brand new feature?
When you make something brand new, making up metrics can feel like a guessing game. “We want to reach 500 customers within 30 days” – is this realistic? Unclear, but we still have to set goals (SMART or otherwise). This leaves product marketing and PM’s discovering how realistic these numbers are after launch.
You don't need a data science degree to pick a good adoption goal for the upcoming feature launch. Below are three simple strategies you can use at any stage. They will help you discover useful starting point for measuring success, without guessing.
Strategies and frameworks for setting product launch goals
Three frameworks to help you think about goals after your product announcement.
#1. “Day One” Eligibility (DOE)
Day One Eligibility is the maximum number of people who you can reach on launch day. It is how many people are on plans or have already set up prerequisites to use a feature. For example, if you have a new interaction in a Slack or Team integration, your eligible audience on day one customer adoption is everyone who already has one of those two integrations configured.
Eligibility doesn’t have to be the ceiling for your goals, but it should inform your ambitions. By framing as eligibility, you’re able to get straight to the point of “How many people can actually use this thing?” regardless of interest or awareness. If your eligible customer % is lower than expected, it might be time to change plan tiers or run a customer campaign to get folks ready for launch day.
Why segment by feature eligibility?
It’s easy to fall into a trap of thinking that a new feature will trigger excitement and finally spark the adoption of neighboring features (integrations, etc) once people see it. The ripple effect from feature launches is where growth marketing can shine, but DOE is one way to make sure you pick a useful starting point.
The reason why DOE is a useful input is that it anchors to the reality of how people already use the product. It is useful for launches that rely heavily on external integrations or gated for specific plan tiers (think: Free vs Pro vs Enterprise).
Example: A new feature requires your Enterprise plan, which represents 30% of your customers — the "day one eligible" audience. This is a way of focusing on 1st or 2nd order impact, vs. “This feature will cause people to upgrade, and then use it” which complicates the feedback loop by adding another variable – budgeting, timing, etc.
#2. Benchmarking performance vs best adopted feature
If your best adopted feature reaches 60% of eligible customers, you should think twice before setting a launch goal to reach 80% of customers within 60 days. This is the same as saying “This will be our best adopted feature of all time!” Before you ask someone to break a company record, it’s worth knowing what the most successful attempt has been so far.
Total customer eligibility will vary between features, so you may need to scale benchmarks (think: % of, instead of absolute #) to match the total eligible customers for your launch.
Example benchmarks:
Pacing: How long did it take for each feature to reach 10% of your audience?
Pacing: How many of your customers had adopted the feature within 30 days?
Total Reach: What’s the total adoption rate among eligible customers today?
Keep a leaderboard of new feature adoption. What’s the best feature you ever launched for total reach? Fastest to 10% of customers? Highest reach after 30 days? Not only does this celebrate success, it also gives you a sober benchmark for what’s proven possible.
#3. Early Adopters
Who will be the first 10 customers to adopt this feature? By describing traits of who you believe will be the earliest adopters, you can get a sense of your potential audience. It can also help you understand how to change your communication strategy to reach more folks and keep your product announcement simple.
Why focus on such a small group? It forces your team to be honest about who will be an initial adopter instead of who should or could use the new feature eventually. Be specific, and name likely candidates.
This exercise is also useful for identifying customers who WON’T be in the early adopters, and possible areas of improvement. Example: “We don’t expect customers with low mobile adoption to change their behavior because of this feature…”
Wrap Up
Each of these strategies can help find a useful target, while helping internal expectation management. Even if you have a brand new product, you can ground everyone in reality by asking the right questions. Remember to aim high and skew towards ambitious — people have a funny way of rising to the occasion.
50% of customers by next month? No problem. All you need is a miracle.
When you introduce a new product or feature, how should you pick goals for customer adoption? Let's say that "Overnight success" is not a good answer.
How do you set goals for a brand new feature?
When you make something brand new, making up metrics can feel like a guessing game. “We want to reach 500 customers within 30 days” – is this realistic? Unclear, but we still have to set goals (SMART or otherwise). This leaves product marketing and PM’s discovering how realistic these numbers are after launch.
You don't need a data science degree to pick a good adoption goal for the upcoming feature launch. Below are three simple strategies you can use at any stage. They will help you discover useful starting point for measuring success, without guessing.
Strategies and frameworks for setting product launch goals
Three frameworks to help you think about goals after your product announcement.
#1. “Day One” Eligibility (DOE)
Day One Eligibility is the maximum number of people who you can reach on launch day. It is how many people are on plans or have already set up prerequisites to use a feature. For example, if you have a new interaction in a Slack or Team integration, your eligible audience on day one customer adoption is everyone who already has one of those two integrations configured.
Eligibility doesn’t have to be the ceiling for your goals, but it should inform your ambitions. By framing as eligibility, you’re able to get straight to the point of “How many people can actually use this thing?” regardless of interest or awareness. If your eligible customer % is lower than expected, it might be time to change plan tiers or run a customer campaign to get folks ready for launch day.
Why segment by feature eligibility?
It’s easy to fall into a trap of thinking that a new feature will trigger excitement and finally spark the adoption of neighboring features (integrations, etc) once people see it. The ripple effect from feature launches is where growth marketing can shine, but DOE is one way to make sure you pick a useful starting point.
The reason why DOE is a useful input is that it anchors to the reality of how people already use the product. It is useful for launches that rely heavily on external integrations or gated for specific plan tiers (think: Free vs Pro vs Enterprise).
Example: A new feature requires your Enterprise plan, which represents 30% of your customers — the "day one eligible" audience. This is a way of focusing on 1st or 2nd order impact, vs. “This feature will cause people to upgrade, and then use it” which complicates the feedback loop by adding another variable – budgeting, timing, etc.
#2. Benchmarking performance vs best adopted feature
If your best adopted feature reaches 60% of eligible customers, you should think twice before setting a launch goal to reach 80% of customers within 60 days. This is the same as saying “This will be our best adopted feature of all time!” Before you ask someone to break a company record, it’s worth knowing what the most successful attempt has been so far.
Total customer eligibility will vary between features, so you may need to scale benchmarks (think: % of, instead of absolute #) to match the total eligible customers for your launch.
Example benchmarks:
Pacing: How long did it take for each feature to reach 10% of your audience?
Pacing: How many of your customers had adopted the feature within 30 days?
Total Reach: What’s the total adoption rate among eligible customers today?
Keep a leaderboard of new feature adoption. What’s the best feature you ever launched for total reach? Fastest to 10% of customers? Highest reach after 30 days? Not only does this celebrate success, it also gives you a sober benchmark for what’s proven possible.
#3. Early Adopters
Who will be the first 10 customers to adopt this feature? By describing traits of who you believe will be the earliest adopters, you can get a sense of your potential audience. It can also help you understand how to change your communication strategy to reach more folks and keep your product announcement simple.
Why focus on such a small group? It forces your team to be honest about who will be an initial adopter instead of who should or could use the new feature eventually. Be specific, and name likely candidates.
This exercise is also useful for identifying customers who WON’T be in the early adopters, and possible areas of improvement. Example: “We don’t expect customers with low mobile adoption to change their behavior because of this feature…”
Wrap Up
Each of these strategies can help find a useful target, while helping internal expectation management. Even if you have a brand new product, you can ground everyone in reality by asking the right questions. Remember to aim high and skew towards ambitious — people have a funny way of rising to the occasion.
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