Redefining Feature Adoption: From Usage to Value
Redefining Feature Adoption: From Usage to Value
Redefining Feature Adoption: From Usage to Value
Redefining Feature Adoption: From Usage to Value
Adoption that doesn’t deliver outcomes is just noise.
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Adoption that doesn’t deliver outcomes is just noise.
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Adoption that doesn’t deliver outcomes is just noise.
Usage without outcomes is the biggest vanity metric in SaaS. A dashboard full of logins, clicks, and time-in-app might look impressive. But I’ve seen plenty of cases where “adoption” meant nothing more than a workaround. Customers exported data because the built-in reporting fell short. They used a feature once because they had no alternative. On paper, adoption looked strong. In practice, the problem remained unsolved.
Usage without outcomes is the biggest vanity metric in SaaS. A dashboard full of logins, clicks, and time-in-app might look impressive. But I’ve seen plenty of cases where “adoption” meant nothing more than a workaround. Customers exported data because the built-in reporting fell short. They used a feature once because they had no alternative. On paper, adoption looked strong. In practice, the problem remained unsolved.
Usage without outcomes is the biggest vanity metric in SaaS. A dashboard full of logins, clicks, and time-in-app might look impressive. But I’ve seen plenty of cases where “adoption” meant nothing more than a workaround. Customers exported data because the built-in reporting fell short. They used a feature once because they had no alternative. On paper, adoption looked strong. In practice, the problem remained unsolved.
Why Usage Alone Falls Short
Take reporting as an example. A product team sees “85% of customers used Feature X.” Success, right? But ask why, and you find they exported data because the built-in view didn’t cut it. The adoption metric disguised a gap. Without that context, Product may double down on exports instead of improving reporting itself.
Why Usage Alone Falls Short
Take reporting as an example. A product team sees “85% of customers used Feature X.” Success, right? But ask why, and you find they exported data because the built-in view didn’t cut it. The adoption metric disguised a gap. Without that context, Product may double down on exports instead of improving reporting itself.
Why Usage Alone Falls Short
Take reporting as an example. A product team sees “85% of customers used Feature X.” Success, right? But ask why, and you find they exported data because the built-in view didn’t cut it. The adoption metric disguised a gap. Without that context, Product may double down on exports instead of improving reporting itself.
The CS Lens on Adoption
This is where CS adds depth. We can connect usage to outcomes in ways analytics can’t. Adoption has real weight when it:
Drives renewal (customers stick with the feature because it matters).
Supports expansion (it sparks demand for more seats or modules).
Solves a business problem (compliance, onboarding, efficiency).
The way to uncover this is by asking why. Why did usage stop after the first try? Why do some segments thrive while others ignore it? Why do workarounds keep showing up?
“ If the feature disappeared tomorrow, what problem would our customers lose the ability to solve?”
The CS Lens on Adoption
This is where CS adds depth. We can connect usage to outcomes in ways analytics can’t. Adoption has real weight when it:
Drives renewal (customers stick with the feature because it matters).
Supports expansion (it sparks demand for more seats or modules).
Solves a business problem (compliance, onboarding, efficiency).
The way to uncover this is by asking why. Why did usage stop after the first try? Why do some segments thrive while others ignore it? Why do workarounds keep showing up?
“ If the feature disappeared tomorrow, what problem would our customers lose the ability to solve?”
The CS Lens on Adoption
This is where CS adds depth. We can connect usage to outcomes in ways analytics can’t. Adoption has real weight when it:
Drives renewal (customers stick with the feature because it matters).
Supports expansion (it sparks demand for more seats or modules).
Solves a business problem (compliance, onboarding, efficiency).
The way to uncover this is by asking why. Why did usage stop after the first try? Why do some segments thrive while others ignore it? Why do workarounds keep showing up?
“ If the feature disappeared tomorrow, what problem would our customers lose the ability to solve?”
Closing the Loop with Product
When CS brings these insights back, framing matters, instead of “Customers aren’t adopting Feature Y,” it becomes:
“Customers try Feature Y once, then drop off because it doesn’t solve their reporting needs.”
“Segment A ties Feature Z directly to compliance outcomes, while Segment B ignores it — here’s why.”
That reframing turns adoption into a signal Product can act on.
Closing the Loop with Product
When CS brings these insights back, framing matters, instead of “Customers aren’t adopting Feature Y,” it becomes:
“Customers try Feature Y once, then drop off because it doesn’t solve their reporting needs.”
“Segment A ties Feature Z directly to compliance outcomes, while Segment B ignores it — here’s why.”
That reframing turns adoption into a signal Product can act on.
Closing the Loop with Product
When CS brings these insights back, framing matters, instead of “Customers aren’t adopting Feature Y,” it becomes:
“Customers try Feature Y once, then drop off because it doesn’t solve their reporting needs.”
“Segment A ties Feature Z directly to compliance outcomes, while Segment B ignores it — here’s why.”
That reframing turns adoption into a signal Product can act on.
Takeaway
Adoption isn’t activity. Its outcomes.
For CS: Before you report adoption back to Product, ask why. Does this usage solve a problem, or is it just activity?
For Product: Look beyond the dashboard. What problem does adoption solve — and what problem does it fail to solve?
The real test is this: If the feature disappeared tomorrow, what problem would our customers lose the ability to solve?
Takeaway
Adoption isn’t activity. Its outcomes.
For CS: Before you report adoption back to Product, ask why. Does this usage solve a problem, or is it just activity?
For Product: Look beyond the dashboard. What problem does adoption solve — and what problem does it fail to solve?
The real test is this: If the feature disappeared tomorrow, what problem would our customers lose the ability to solve?
Takeaway
Adoption isn’t activity. Its outcomes.
For CS: Before you report adoption back to Product, ask why. Does this usage solve a problem, or is it just activity?
For Product: Look beyond the dashboard. What problem does adoption solve — and what problem does it fail to solve?
The real test is this: If the feature disappeared tomorrow, what problem would our customers lose the ability to solve?
Delivering Outcomes
Delivering Outcomes
Delivering Outcomes
Customers
© 2025 Planhat AB
Customers
© 2025 Planhat AB
Customers
© 2025 Planhat AB
Customers
© 2025 Planhat AB