BigQuery Analytics

Customer Lifetime Value Analysis in BigQuery

SQL-based customer LTV modelling and segmentation in BigQuery

Build customer lifetime value models in BigQuery. Analyse historical purchase data to predict CLV, segment customers by value, and optimise acquisition spending.

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Customer Lifetime Value (CLV/LTV) is the most important metric for sustainable ecommerce growth — it determines how much you can profitably spend to acquire a customer. We build CLV models in BigQuery: historical LTV by acquisition channel, cohort-based retention analysis, predictive LTV estimation using purchase frequency and average order value, and customer value tier segmentation. This gives you a defensible number to set CAC targets by channel.

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What's Included

Every deliverable you receive as part of this service.

Historical CLV calculation by cohort and channel

Repeat purchase rate and order frequency analysis

Predictive CLV model (probabilistic or regression-based)

Customer value tier segmentation query

CLV by acquisition source/channel

Payback period analysis by channel

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Common questions about Customer Lifetime Value Analysis in BigQuery.

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