Grow WhatsApp Business Adoption

Easy

Metrics

Asked at 1 company1North Star MetricKPIsAARRR Framework

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Problem

Business Context

Meta wants to increase the number of businesses actively using WhatsApp Business and the WhatsApp Business Platform. Leadership is less interested in raw signups and more focused on durable business adoption that leads to customer conversations and repeat usage.

Metric Scenario

In the last quarter, WhatsApp Business app registrations grew from 8.4M to 9.6M (+14%), but 30-day active business accounts only grew from 3.1M to 3.2M (+3%). First-week message send rate fell from 62% to 55%, and 90-day retained business accounts stayed flat at 34%. The Growth team also launched new onboarding surfaces in Ads Manager and Facebook Pages, but PMs are unsure whether the issue is acquisition quality, onboarding friction, or weak retention after setup. You have access to Meta’s standard growth framework and are expected to define the KPI stack using an AARRR funnel, not just one top-line metric.

Requirements

Define the north-star metric you would use for “businesses using WhatsApp” and explain why it is better than registrations.
Propose the core KPI tree across the AARRR funnel: acquisition, activation, retention, referral/virality, and revenue-proxy if relevant.
Identify the leading indicators you would track in the first 7 days that predict 30-day and 90-day retention.
Show how you would decompose the gap between signup growth and active-business growth.
Name guardrails and data-quality checks you would review before trusting the metrics, including any risk of Sample Ratio Mismatch if these metrics later support an experiment.

Data Available

wa_business_accounts: business_id, created_time, account_type, country, linked_fb_page_id, linked_ig_account_id
wa_business_events: business_id, event_time, event_name, catalog_created, profile_completed, message_sent, reply_received
ads_manager_referrals: business_id, referral_source, campaign_id, click_time
fb_pages_links: page_id, business_id, page_category, follower_count
business_retention_daily: business_id, ds, active_flag, conversations_started, conversations_replied

Problem

Business Context

Metric Scenario

Requirements

Define the north-star metric you would use for “businesses using WhatsApp” and explain why it is better than registrations.
Propose the core KPI tree across the AARRR funnel: acquisition, activation, retention, referral/virality, and revenue-proxy if relevant.
Identify the leading indicators you would track in the first 7 days that predict 30-day and 90-day retention.
Show how you would decompose the gap between signup growth and active-business growth.
Name guardrails and data-quality checks you would review before trusting the metrics, including any risk of Sample Ratio Mismatch if these metrics later support an experiment.

Data Available

wa_business_accounts: business_id, created_time, account_type, country, linked_fb_page_id, linked_ig_account_id
wa_business_events: business_id, event_time, event_name, catalog_created, profile_completed, message_sent, reply_received
ads_manager_referrals: business_id, referral_source, campaign_id, click_time
fb_pages_links: page_id, business_id, page_category, follower_count
business_retention_daily: business_id, ds, active_flag, conversations_started, conversations_replied

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Next question

Metric Scenario

Requirements

Define the north-star metric you would use for “businesses using WhatsApp” and explain why it is better than registrations.

Propose the core KPI tree across the AARRR funnel: acquisition, activation, retention, referral/virality, and revenue-proxy if relevant.

Identify the leading indicators you would track in the first 7 days that predict 30-day and 90-day retention.

Show how you would decompose the gap between signup growth and active-business growth.

Name guardrails and data-quality checks you would review before trusting the metrics, including any risk of Sample Ratio Mismatch if these metrics later support an experiment.

Data Available

wa_business_accounts: business_id, created_time, account_type, country, linked_fb_page_id, linked_ig_account_id

wa_business_events: business_id, event_time, event_name, catalog_created, profile_completed, message_sent, reply_received

ads_manager_referrals: business_id, referral_source, campaign_id, click_time

fb_pages_links: page_id, business_id, page_category, follower_count

business_retention_daily: business_id, ds, active_flag, conversations_started, conversations_replied

Metric Scenario

Requirements

Define the north-star metric you would use for “businesses using WhatsApp” and explain why it is better than registrations.

Propose the core KPI tree across the AARRR funnel: acquisition, activation, retention, referral/virality, and revenue-proxy if relevant.

Identify the leading indicators you would track in the first 7 days that predict 30-day and 90-day retention.

Show how you would decompose the gap between signup growth and active-business growth.

Name guardrails and data-quality checks you would review before trusting the metrics, including any risk of Sample Ratio Mismatch if these metrics later support an experiment.

Data Available

wa_business_accounts: business_id, created_time, account_type, country, linked_fb_page_id, linked_ig_account_id

wa_business_events: business_id, event_time, event_name, catalog_created, profile_completed, message_sent, reply_received

ads_manager_referrals: business_id, referral_source, campaign_id, click_time

fb_pages_links: page_id, business_id, page_category, follower_count

business_retention_daily: business_id, ds, active_flag, conversations_started, conversations_replied