Calculate Survey Response Rate and Quality Metric in SQL

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Q: What difficulty level is this coding question?

This is a Medium difficulty Data Manipulation (SQL/Python) question, commonly asked during Technical Screen rounds at Meta.

Q: What role is this question designed for?

This question is commonly asked for Data Scientist candidates at Meta during technical interviews.

Question

survey_responses

+---------+----------+---------------------+---------------------+-------+
| user_id | survey_id| impression_ts       | click_ts            | score |
+---------+----------+---------------------+---------------------+-------+
| 101     | 555      | 2023-09-01 10:00:00 | 2023-09-01 10:05:12 | 4     |
| 102     | 555      | 2023-09-01 10:02:34 | NULL                | NULL  |
| 101     | 556      | 2023-09-02 09:15:20 | 2023-09-02 09:16:00 | 5     |
| 103     | 555      | 2023-09-01 10:10:00 | NULL                | NULL  |
| 104     | 557      | 2023-09-03 11:00:00 | 2023-09-03 11:02:45 | 3     |
+---------+----------+---------------------+---------------------+-------+

##### Scenario

SQL analysis of in-app survey effectiveness for the travel app.

##### Question

Write a query to compute the overall survey response rate, defined as total clicks divided by total impressions. Using the score column, calculate a survey-quality metric. Show two approaches:
(a) average every score available,
(b) average only the first score a user gave for each survey. Explain which you would choose and why.

##### Hints

NULL click_ts means no click; distinct user-survey pairs for first-score logic.

PracHub · Accepted Answer

This question evaluates SQL data-manipulation competencies such as aggregation, NULL handling, deduplication (first-per-group), and computing engagement and quality metrics from event logs.

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