Feature Adoption Rate measures the percentage of your customer base that actively uses a specific feature within your product. In B2B SaaS, this is a "Precision Health" metric—it's not enough to know people are logging in; you need to know if they are using the "Sticky" features that drive the most value and make the product indispensable.
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How is Feature Adoption calculated?
Adoption Rate = (Number of users who performed [Target Action] / Total Number of active users) during a specific period. You should track this for your "Core 3" features that define your product's value proposition.
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Adoption Depth vs. Breadth: What is the difference?
Breadth: How many people use it? Depth: How *often* do they use it? For power features (like reporting), "Depth" is the key loyalty signal. For administrative features (like MFA), "Breadth" (100% adoption) is the goal.
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How can CS teams drive higher Feature Adoption?
1) Contextual "In-App Nudges" when a user is in a related area. 2) "Release Webinars" showing real-world use cases. 3) Targeted email campaigns to users who *haven't* tried the feature. 4) Success "Playbooks" that show the ROI of using that specific feature.
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What does low adoption tell you about a feature?
If adoption is under 5% after 6 months, the feature is either: 1) Buried in the UI. 2) Not solving a real problem. 3) Too complex to set up. This data is the "Smoking Gun" the Product team needs to decide whether to "Fix it" or "Sunset it."
Knowledge Challenge
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