Calculating LTV Using Rockerbox Attribution Data
While Rockerbox does not explicitly provide LTV calculations, Rockerbox's attribution reporting paired with your internal customer data can be used for LTV calculations that help to answer a variety of LTV questions, including
- What channels are driving the highest LTV customers into the funnel
- Ex: are users who have TikTok on their path to conversion higher LTV than users with Facebook on their path to conversion
- What types of users (based on their marketing exposure) have the highest LTV
- Ex: do users in Facebook's Female 25-35 audience pool have higher LTV than those reached from broad targeting
- Are our retention channels successful at driving up a customer's overall LTV?
- Ex: how does clicking on an SMS message impact a customer's overall LTV?
How to use Rockerbox reporting for LTV calculations
- Start with Rockerbox's user level log file, which shows all of the marketing touchpoints against each individual purchaser.
*You will likely need Rockerbox data synced to your data warehouse to execute the joining and analysis
- Join Rockerbox's attribution data to your internal customer data using the conversion_key field, which should represent a customer's Order ID
- Cohort revenue or purchase history by user (ex on email or a persistent customer id)