How is iDBQuery used by D2C brands?
Direct-to-consumer brands use iDBQuery to ask plain-language questions across store, ad-platform, subscription and fulfilment data, getting cited answers in seconds without SQL. It builds one live model across your Shopify database, ad APIs and spreadsheets so teams track CAC, LTV and margin without pipelines.
D2C brands live across an e-commerce store, ad platforms, email/SMS tools, a subscription system and a 3PL. iDBQuery unifies these into one live model so founders and growth teams ask plain-language questions and get a cited answer, no analyst and no pipeline.
Examples:
- What is blended CAC and contribution margin by channel this month?
- Show LTV and repeat-purchase rate by acquisition cohort.
- Which SKUs are most profitable after COGS, shipping and returns?
- What is our return rate by product and reason?
- How does subscription churn trend by cohort?
iDBQuery connects your store database, ad-platform and analytics APIs, and fulfilment CSVs together with no ETL, joins them, and cites each figure to the source row, so growth and finance decisions rest on trustworthy numbers. The Analyst agent can investigate a CAC spike or margin drop autonomously and produce a shareable report.
Deployment is flexible: cloud, your own VPC, or the Desktop app with query-in-place. The differentiator over stitching together dashboards or exporting to spreadsheets is that a lean team gets instant, cross-channel answers, from ad spend to fulfilment cost, in one place, each number auditable back to source.
Updated 2026-06-22