##### Question You work on a consumer calling product (think Messenger/WhatsApp-style voice) that currently supports only **one-to-one** voice calls. The team is considering whether to launch a **group calling** feature. You have access to the existing call logs and a daily-active-users table: **Table: `users`** - `user_id` BIGINT - `country_code` STRING **Table: `calls`** - `call_id` BIGINT - `caller_id` BIGINT (references `users.user_id`) - `recipient_id` BIGINT (references `users.user_id`) - `started_at` TIMESTAMP - `ended_at` TIMESTAMP - `status` STRING (e.g. completed, missed, failed) **Table: `daily_active_users`** - `activity_date` DATE - `user_id` BIGINT - `country_code` STRING Assume one row per call attempt, and that all date-based analyses use the `Europe/London` timezone. Using only these existing one-to-one call logs (no group-call feature exists yet), answer the following product analytics questions: 1. **How would you determine whether the product should build a group calling feature?** (i.e. is there unmet demand?) 2. **If group calling is launched, how would you decide whether the launch was successful?** In your answer, cover: - how to infer latent/unmet demand for group calls from one-to-one behavior - what proxy metrics you would build from call sequences and user networks - alternative explanations and confounding factors (selection bias, spam, network quality) - what success means across adoption, engagement, quality, and retention - the difference between launch (novelty) metrics and long-term value metrics - how you would design an experiment, including randomization challenges from social-network interference - guardrail metrics and failure cases - how you would interpret mixed or ambiguous results

A Meta Data Scientist technical-screen case: using only one-to-one call logs, decide whether to build a group calling feature and how to measure a launch's success. It tests product analytics, proxy-metric design, network analysis, causal inference, and experiment design under social-network interference.

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Should We Launch Group Calling? | Meta Interview Question

Question

You work on a consumer calling product (think Messenger/WhatsApp-style voice) that currently supports only one-to-one voice calls. The team is considering whether to launch a group calling feature. You have access to the existing call logs and a daily-active-users table:

Table: users

user_id BIGINT
country_code STRING

Table: calls

call_id BIGINT
caller_id BIGINT (references users.user_id )
recipient_id BIGINT (references users.user_id )
started_at TIMESTAMP
ended_at TIMESTAMP
status STRING (e.g. completed, missed, failed)

Table: daily_active_users

activity_date DATE
user_id BIGINT
country_code STRING

Assume one row per call attempt, and that all date-based analyses use the Europe/London timezone.

Using only these existing one-to-one call logs (no group-call feature exists yet), answer the following product analytics questions:

How would you determine whether the product should build a group calling feature? (i.e. is there unmet demand?)
If group calling is launched, how would you decide whether the launch was successful?

In your answer, cover:

how to infer latent/unmet demand for group calls from one-to-one behavior
what proxy metrics you would build from call sequences and user networks
alternative explanations and confounding factors (selection bias, spam, network quality)
what success means across adoption, engagement, quality, and retention
the difference between launch (novelty) metrics and long-term value metrics
how you would design an experiment, including randomization challenges from social-network interference
guardrail metrics and failure cases
how you would interpret mixed or ambiguous results

Question

Table: users

user_id BIGINT
country_code STRING

Table: calls

call_id BIGINT
caller_id BIGINT (references users.user_id )
recipient_id BIGINT (references users.user_id )
started_at TIMESTAMP
ended_at TIMESTAMP
status STRING (e.g. completed, missed, failed)

Table: daily_active_users

activity_date DATE
user_id BIGINT
country_code STRING

Assume one row per call attempt, and that all date-based analyses use the Europe/London timezone.

Using only these existing one-to-one call logs (no group-call feature exists yet), answer the following product analytics questions:

How would you determine whether the product should build a group calling feature? (i.e. is there unmet demand?)
If group calling is launched, how would you decide whether the launch was successful?

In your answer, cover:

how to infer latent/unmet demand for group calls from one-to-one behavior
what proxy metrics you would build from call sequences and user networks
alternative explanations and confounding factors (selection bias, spam, network quality)
what success means across adoption, engagement, quality, and retention
the difference between launch (novelty) metrics and long-term value metrics
how you would design an experiment, including randomization challenges from social-network interference
guardrail metrics and failure cases
how you would interpret mixed or ambiguous results

Should We Launch Group Calling?

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Should We Launch Group Calling?

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