AI Ecommerce Dashboard Dashboard from CSV

Shopify's built-in analytics are perfectly fine for the question 'how much did we sell yesterday?'. They are less useful for the question 'which SKU is dragging down our margin because of a 14% return rate?'. That second question requires joining the orders table to the refunds table, grouping by SKU, and ranking by the refund-to-order ratio. With a CSV upload, Sreniq does that join automatically and surfaces the worst offenders alongside the standard top-revenue table — so the same dashboard answers both questions.

Repeat-customer analysis is the other gap most stores have. Out of the box, you know order count and revenue; you do not know what fraction of revenue came from buyers who had already bought before. Sreniq computes that ratio by customer ID, plots it over time, and lets you ask follow-ups like 'show AOV for first-time vs repeat' or 'list customers who bought 3+ times in the last 90 days'. For a store running paid acquisition, this is the cohort metric that ultimately decides whether the LTV math works.

Discount and promo analysis is a third easy win. If your CSV captures a discount code or amount per order, Sreniq can break out discount-driven revenue, average discount per order, and AOV with vs without a promo applied. That tells you whether your most-used code is pulling in incremental customers or just giving regulars a price cut they would have paid full price for.

The cadence we see working best is a weekly review using the standard dashboard, plus an as-needed deep-dive when a number moves. Because the dashboard is rebuilt from the latest export each Monday, drift is impossible — every chart reflects the order table at upload time. Public links make it easy to send the weekly view to a brand partner or marketplace ops contact without granting them admin access.