Analytics

% of customers who place a 2nd+ order. Canonical retention metric.

Conversion rate trend: % of sessions that purchase. Canonical storefront health metric.

Revenue per acquisition source: organic, paid, email, social, direct, referral.

Groups customers by signup month + tracks retention over time. Reveals if newer cohorts retain better.

Per-product performance: views, add-to-cart, conversion, revenue, units.

Total sessions plotted over time: the canonical traffic trend.

Conversion through checkout: % of cart-builders who complete payment. The bottom-of-funnel KPI.

Decomposes conversion into funnel stages: session → product view → add-to-cart → checkout → completed. Pinpoints drop-off.

What's happening on your storefront right now: active visitors, orders being placed, geographic spread.

Revenue attributed to channels: first-touch, last-touch, multi-touch models. Resolves which channels drive orders.

Every analytics metric defined: formula + interpretation + caveats.

Per-PSP / payment-method breakdown: count, revenue, fail rate, processing time. Surfaces underperforming PSPs.

Browse every report category: sales, customers, conversion, behavior, attribution, search.

Revenue per product. Granular view for merchandising.

Top-line sales summary: revenue, orders, AOV, refunds, taxes for the period.

Aggregate customer-behavior reports: at-risk, cohort, segmentation. Lives under Customers category.

Summary of purchasing behavior + demographics. Foundation for segments + tailored merchandising.

Revenue per sales channel: online store, POS, mobile app, marketplaces, Shop.

Session count + conversion broken down by country / region. Identifies geographic concentration + growth markets.

Products ranked by revenue, units sold, or AOV contribution. The merchandising "what's selling" view.

Reference for column categories: sales, conversion, traffic, customer, product. Each groups related metrics.

Tanqory ships 210+ canned reports across categories: Sales, Customers, Marketing, Behavior, Finance, Inventory. Use the catalog to find what you need.

Revenue attributed to UTM campaigns: measures campaign ROAS.

Index of every sales-related report: discover the right one for your question.

Sessions per referring website: discovers partnerships + surprise traffic drivers.

Single number: active visitors this moment. Useful during launches.

Key store metrics on one screen: sales, orders, conversion, traffic, AOV. The starting point.

Every metric + chart label in plain language. Reference companion to reports.

Per-discount performance: redemptions, revenue impact, AOV lift, margin given up.

Export any report to CSV: for offline analysis, sharing without admin access, or BI integration.

Splits revenue by first-time vs repeat customers. Measures acquisition vs retention balance.

World map of current visitor locations: situational awareness during launches.

Visitor-level split between first-session + repeat-session. Session-side companion to First-Time vs Returning Sales.

Tax collected per jurisdiction. Used for filing + accounting reconciliation.

Distinct-visitor count over time. Deduplicated complement to Sessions Over Time.

Pick which columns / metrics appear in each report. Customize the view to what matters.

Pick date range: today, yesterday, 7d, 30d, custom. Compare to previous period.

Single-page-session rate: leaves without engaging. High bounce = landing page mismatch.

Multi-store conversion comparison: identifies outliers.

Recommendation widgets with low CTR: placement not earning its space.

Ad-hoc analytics workspace: pivot, slice, and chart any metric across any dimension. For questions canned reports do not cover. Launched from Analytics > Explore.

How often product-recommendation widgets (related, you may also like) lead to add-to-cart + purchase.

Sessions broken down by social platform: Instagram, TikTok, Facebook, X, etc.

Install a tracking pixel: Meta, TikTok, Pinterest, GA4. Powers ad attribution + audiences.

AOV over time: cart-size health. Rising AOV = upsell + cross-sell working.

Read customer-behavior signals from the Analytics dashboard: Returning customer rate, device + channel splits, drill into Customer Insights and Cohort Analysis.

Orders-specific dashboard: pending, fulfilled, refunded, average processing time.

Conversion by storefront search query. High-intent + low-conversion = top-priority merchandising fix.