Reporting

NOTE: The reporting functionality described on this page is for new reporting functionality, not for the reporting currently available in the Foxy admin.

All timestamps in generated reports are for the store's configured timezone.

All

Note that some of these reports may not be available when this functionality comes out of beta.

1. Transactions
2. Voided Transactions (deprecated; to be combined with Transactions)
3. Payment Method Summary by Month
4. Daily / Weekly / Monthly Summary
5. Items (ie. Transaction Items aka Products)
6. Summary by SKU by Month (where “SKU” is the code value on an item)
7. Subscription Forecast by SKU by Month (assuming no cancellations except for what already has an enddate, and no new subscriptions)
8. Coupons Used

Generally, the exported data matches what is available via the Foxy API. There are some columns that are new, however:

• product_subtotal_one_off: The subtotal (pre-discounts and coupons) of non-recurring products.
• product_subtotal_new_subscriptions: The subtotal of subscription products starting in the time period.
• product_subtotal_renewing_subscriptions: The subtotal of subscription products renewing in the time period.
• product_subtotal_future_subscriptions: The subtotal of subscription products with a start date in the future.
• product_subtotal_new_mrr: The new monthly recurring revenue. We do some math here to convert the frequency (if it's not 1m) to a monthly value. For instance, a 1y value will be divided by 12, while a 30d or 4w subscription will result in a monthly value using an average of 30.45 days per month.
• product_subtotal_cancelled_mrr: The subtotal amount of subscriptions that were cancelled in the time period. Note that if you deactivate subscriptions via the admin or API (without setting an enddate), those won't be counted here.
• one_off_count: The number of transactions that have non-recurring products. NOTE: A transaction can include a one-off item and a new subscription, so if you add up all the _count values, you may get a number higher than the number of transactions you actually had.
• subscriptions_new_count: The number of transactions with new subscriptions.
• subscriptions_renewed_count: The number of transactions with subscriptions that renewed successfully. (If there was a payment error, that doesn't count as a transaction.)
• subscriptions_cancelled_count: The number of subscriptions that cancelled. Note, as above, that setting a subscription to inactive without an enddate will result in the subscription not being counted here.

The LTV summary report is intended to help you understand how much an average customer is worth, which can be helpful in determining marketing budgets and ad spend. It includes the following columns:

1. customer_count: The number of unique customers in the grouping.
2. avg_transaction_count: The number of transactions per customer. Note that this is a count of transactions, not a timeframe. For instance, if you offer subscriptions with different frequencies (monthly and annually, for instance), this value may be difficult to parse. If you'd like additional categorization (such as by subscription frequency), please let us know.
3. avg_order_value: The average of the total_order value (which includes items, shipping, taxes, and discounts).
4. avg_ltv: The average value per customer (ie. the LTV, “lifetime value”).

And the following rows:

1. subscribers: This includes any customers who have ever had a subscription. In other words, if a customer placed 2 non-subscription orders, then subscribed, then cancelled, they would count as a subscriber.
2. oto: “One-time order” customers have never had a subscription.
3. all: This is all customers (inclusive of the previous two rows).