Translate 'increase engagement' into a technical measurement plan
This tests your ability to translate a vague business goal into a structured, measurable technical plan. Clarify the goal with the PM, define a primary metric and supporting metrics, then create an instrumentation spec.
What's really being asked
This question assesses your ability to bridge the gap between product and engineering. It's not a quiz on metric definitions. The interviewer is looking for a structured, collaborative process. Can you take a fuzzy business request like 'increase engagement' and translate it into a specific, actionable, and measurable technical plan? They want to see you think like a product-minded engineer who connects technical work directly to business outcomes.
The full answer
A strong answer follows a clear, three-step framework. First, COLLABORATE and CLARIFY. Ask the PM questions to define 'engagement' for this specific feature. What is the ideal user journey? What specific action signifies success? Is it clicking a button, completing a flow, or returning daily? Second, DEFINE THE METRICS. Propose a metric hierarchy. Start with one primary or "North Star" metric (e.g., % of users who complete action X at least once a week). Then, add 2-3 secondary, diagnostic metrics (e.g., time to complete action X, error rate in the flow). Also include counter-metrics to watch for negative side effects (e.g., does this feature decrease engagement elsewhere?). Third, PLAN THE IMPLEMENTATION. Detail the specific events that need to be instrumented (e.g., feature_viewed, action_x_started, action_x_completed) and the properties to include with each event (e.g., user_id, session_id, time_taken_ms).
The mistakes people make
The biggest red flag is jumping straight to solutions or generic metrics. A weak answer immediately says "We should track DAU and MAU." This is a poor response because it doesn't relate to the new feature specifically and shows a lack of critical thinking. Another mistake is suggesting technical implementation details (e.g., "We'll use Segment to send events to Amplitude") before defining what needs to be measured and why. The tool is irrelevant until the goal is clear. Finally, failing to mention counter-metrics is a miss for a senior candidate, as it ignores potential negative product impacts.
What usually comes next
Be ready for "How would you set a goal for this metric?" (Answer: Establish a baseline first, then set an incremental goal like a 20% increase in feature adoption, similar to the Housing.com example). Another follow-up is "The metric went up, how do you know your work was the cause?" (Answer: Discuss correlation vs. causation, mention A/B testing as the gold standard for proving impact, and analyze segmented data).
A concrete example
For a new 'Save for Later' button on an e-commerce site, 'engagement' is vague. I'd clarify with the PM: is the goal to save items, or to eventually buy saved items? Assuming the latter, my primary metric would be "Weekly Saved-Item Purchase Rate" (% of users who purchase an item from their saved list each week). Secondary metrics would be "Save-to-Purchase Time" (median hours from save to buy) and "Save Action Rate" (% of product viewers who click save). A counter-metric would be "Overall Conversion Rate" to ensure we aren't just shifting purchases. The instrumentation plan would require events like product_page_view, save_for_later_click, and checkout_item_purchased with a source: 'saved_list' property.
Interview question
A product manager asks you to help "increase engagement" with a new feature. What is the most effective first step to take?
- a.Select an analytics tool and draft a technical spec for instrumenting user interaction events.
- b.Propose A/B testing several different UI designs to see which one users prefer.
- c.Ask clarifying questions to define what specific user action constitutes 'engagement' for this feature.Correct
- d.Begin tracking generic metrics like Daily Active Users (DAU) and session duration to establish a baseline.
Why? this is the answer
The first step is always to collaborate with the PM to clarify the vague business goal into a specific, measurable user action. Jumping to generic metrics like DAU is a common mistake as it doesn't provide specific insight into the new feature's performance.
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