Do not index
Do not index
Type of metrics to measure a product's impact
To get the best result, focus on a mix of quantitative and qualitative metrics that reflect both user behaviour and business outcomes. Here are some key metrics you might consider:
1. User Engagement
- Active Users (DAU/MAU): Daily and monthly active users show how often people use your product.
- Session Length: How long users spend on your product during each session.
- Retention Rate: Percentage of users who return after their first use (i.e. 1-day, 7-day, 30-day retention).
- Churn Rate: The percentage of users who stop using your product over a specific period.
2. User Satisfaction
- Net Promoter Score (NPS): Measures customer loyalty by asking how likely users are to recommend your product.
- Customer Satisfaction (CSAT): Direct feedback on user satisfaction (often done via surveys).
- Customer Effort Score (CES): Measures how easy or difficult it is for users to accomplish their goals using your product.
3. Business Impact
- Revenue Growth: The amount of money generated from your product (i.e. sales, subscriptions, or other revenue).
- Customer Lifetime Value (CLV): How much a customer is likely to spend over their lifetime with your product.
- Conversion Rate: The percentage of users who complete a desired action (i.e. sign up or make a purchase).
- Customer Acquisition Cost (CAC): How much it costs to acquire a new customer.
4. Usability Metrics
- Task Success Rate: How many users successfully complete a task in your product.
- Time on Task: How long it takes users to complete key tasks—indicate ease of use or friction.
- Error Rate: How many users fail to complete a task in your product—highlight usability issues.
5. Product-Specific Metrics
- Feature Usage: How often key features are being used—can help prioritise future development.
- Adoption Rate: How quickly users are adopting new features or product updates.
How to pick the right metrics?
The impact you decide to measure is also dependent on your goals; answer these questions to pick the right metrics:
- Did you achieve your desired outcome?
- Did you prove your hypothesis right or wrong?
- Is this data telling the whole story? What’s the why behind it?
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