Mastering Meta Product Sense Interviews with the HEART Framework

What is the HEART Framework?

HEART stands for:

• Happiness: How satisfied are your users?
• Engagement: How actively are users interacting with your product?
• Adoption: How many users are trying your product for the first time?
• Retention: How many users keep coming back over time?
• Task Success: How effectively can users complete key actions?

Originally developed by Google, HEART is flexible—you can use all five dimensions or just the ones most relevant to your product or feature.

How to Use HEART in a Meta Product Sense Interview

1. Frame the Interview Question

Suppose you’re asked:

"How would you measure and improve the success of Meta’s new food delivery feature in Messenger?"

Start by clarifying the business and user goals:

• Are we optimizing for user satisfaction, growth, revenue, or something else?
• What does success look like for this feature?

2. Map Goals, Signals, and Metrics

For each HEART dimension, define:

• Goal: What do you want to achieve?
• Signal: What user behavior or feedback indicates you’re achieving it?
• Metric: What specific, trackable number will you use to measure progress?

Example for a Spiked Lemonade Delivery App (adapted for Meta’s context):

HEART DimensionGoalSignalMetricHappinessMaximize user satisfactionApp store ratings, NPS survey scoresMonthly change in app rating, % of perfect NPS scoresEngagementMaximize orders and order value# of orders per customer, order valueAvg. order value/day, avg. orders/user/dayAdoptionMaximize new users trying the feature# of users placing first order, app downloads% of new users who order, # of new users opening the featureRetentionMaximize repeat usageRepeat orders, returning users% of users ordering again this monthTask SuccessMinimize friction in orderingAbandoned carts, order completion timeAvg. time to checkout, % of incomplete orders

3. Prioritize & Ideate

Not every dimension will be equally important for every product or feature. For a new launch, Adoption and Task Success might be most critical. For a mature feature, Retention and Engagement could drive long-term value.

Brainstorm features or improvements for the highest-priority areas:

• If Task Success is low, streamline the checkout flow.
• If Retention is lagging, introduce personalized re-engagement notifications.
• If Happiness is low, gather user feedback and address pain points.

4. Define Success and Tradeoffs

For each metric, set clear targets and discuss possible tradeoffs. For example:

• Improving Task Success (faster checkout) might boost Adoption and Retention.
• Increasing Engagement (more orders) should not come at the cost of Happiness (e.g., by spamming users).

5. Communicate Clearly and Collaborate

Throughout your answer, explain your reasoning, ask clarifying questions, and check in with your interviewer. Show that you can work cross-functionally—using the Signals column to inform engineers about what to track.

Sample Answer Outline Using HEART

“To measure and improve Meta’s food delivery feature, I’d use the HEART framework. First, I’d define what success looks like for users and the business. For example, I’d want to maximize user satisfaction (Happiness), ensure users can easily place orders (Task Success), and drive repeat usage (Retention). I’d track signals like app ratings, NPS scores, order completion rates, and repeat orders. Based on the data, I’d prioritize streamlining the order flow and personalizing re-engagement, measuring impact with metrics like average checkout time and monthly retention. This approach ensures we’re building a feature users love and use often, while also driving business impact.”

Tips for Using HEART in Meta Interviews

• Be flexible: Use the HEART dimensions that matter most for the question.
• Focus on reporting, not exploring: HEART is best for tracking ongoing product health, not for one-off experiments.
• Pick the most relevant metric: Don’t try to use every metric—choose the one(s) that best measure success for your scenario.
• Link signals to tracking: Use the signals column to specify what engineers need to track in the product.
• Show product intuition: Explain why certain dimensions matter more for your product or feature.

Why HEART Works for Meta Product Sense

• User-centric: Keeps the focus on real user outcomes, not just business goals.
• Structured: Helps you break down complex problems and communicate clearly.
• Actionable: Translates goals into measurable, trackable results.
• Flexible: Works for features, products, or even whole platforms.

By mastering the HEART framework, you’ll be ready to impress Meta interviewers with your structured thinking, user empathy, and ability to drive real impact—helping you stand out in your next product sense interview.