81 topics found for:

“product assessment”

Ratio Bias

A cognitive bias where people judge the likelihood of an event based on its relative size rather than absolute probability. Important for understanding user decision-making biases and designing systems that present information accurately.

Smoke Testing

A preliminary testing method to check whether the most crucial functions of a software application work, without going into finer details. Important for identifying major issues early in the development process and ensuring the stability of digital products.

AARRR

Acquisition, Activation, Retention, Referral, and Revenue (AARRR) is a metrics framework for assessing user engagement and business performance. Important for product managers to understand customer lifecycle and optimize business growth.

Empirical Rule

Also known as the 68-95-99.7 Rule, it states that for a normal distribution, nearly all data will fall within three standard deviations of the mean. Important for understanding the distribution of data and making predictions about data behavior in digital product design.

ROI

Return on Investment (ROI) is a performance measure used to evaluate the efficiency or profitability of an investment or compare the efficiency of different investments. Crucial for assessing the financial effectiveness of business decisions, projects, or initiatives.

Turnover Rate

The rate at which employees leave a company and are replaced by new hires, often used as a measure of organizational health and stability. Essential for understanding workforce dynamics and designing strategies to improve employee retention.

Optimism Bias

A cognitive bias that causes people to believe they are less likely to experience negative events and more likely to experience positive events than others. Crucial for understanding user risk perception and designing systems that account for unrealistic optimism.

Staffing Ratio

A strategy used to determine the proportion of various SMEs needed to support a pipeline of work. Important for optimizing resource allocation, enhancing efficiency, and ensuring teams have the appropriate support based on design demand and complexity.