Overview of HEART Framework

Overview of HEART Framework

The HEART Framework is designed by Google to focus on a few primary user metrics and then quantify those metrics to evaluate them critically.

Need for the Framework

  • Evaluation of customer engagement on a wide scale becomes a non-rival challenge as more products and services are deployed on the web.
  • User-centered metrics for web applications are necessary to track the progress and direct the product decisions.

HEART Framework

H - Happiness

  • Describes metrics attitudinal in nature.

  • Relate to subjective aspect of user experience such as

    • User Satisfaction

    • Visual Appeal

    • Likelihood to Recommend

    • Perceived Ease of Use

E - Engagement

  • Describes the level of Engagement with the product / feature.

  • Metrics refers to

    • Frequency

    • Intensity

    • Depth of Interaction (over period of time)

  • Generally reported as an average, ratios or percentages.

A - Adoption

  • Describe the use of product / feature by the new user during a period of time.

  • Definition of use can change based on the nature of the goals, such as

    • Visiting the feature page

    • Completion of a specific task

R - Retention

  • Describe the use of product / feature by the users of a given period still present in some later period.

  • Can be measured over different periods of time such as

    • Week to Week

    • Monthly

    • 90 Day Period

T - Task Success

  • Describe traditional metrics of user experience such as efficiency, effectiveness, and error rate.

  • If an optimal path exists for a particular task, it is possible to measure how closely users follow it.

Goals - Signals - Metrics Process

Goals

  • Articulating the goals of the product / feature.

  • Every user centered metric is attached to the goal and can be used to track the progress for the same.

  • This step includes:

    • Identify goals of product / feature.

    • Identify what users need to accomplish.

    • What redesign is trying to achieve.

    • Use of HEART Framework for articulation.

Signals

  • Identifying signals that indicate the success of the goals.

  • Translate the success / failure of goals in terms of user behaviour or attitude, and identify:

    • Attitudinal / Behaviour signals.

    • Signals that are sensitive and specific to the goals.

Metrics

  • Building specific metrics to track on the dashboard.

  • Translate signals into metrics for tracking over time, and ensuring:

    • Use of stable metrics over time such as averages, ratios, and percentages

    • Accuracy of metrics based on application / web logs.

    • Additional metrics than the standard set for allowing products comparison with others such as competitors or within products.

Reference