Derma Belle — E-commerce Analytics Case Study

• What explains the change in net sales from May to June 2026?
• How much of the May-to-June sales decline came from receiving fewer successfully paid orders?
• Why did average order value change from June 15–21 to June 22–28, 2026?
• How much of the May-to-June change in paid merchandise sales came from items per order, product mix, prices, and allocated discounts?
• Based on results through June 30 and relevant earlier patterns, what are the projected paid orders, paid merchandise sales, and average order value for July 2026?

• Which successfully paid Shopify orders from June 22–28, 2026, are missing from GA4?
• Which GA4 purchase records from June 22–28 were recorded more than once?
• Which GA4 purchase records from June 22–28 cannot be matched to an eligible paid Shopify order?
• Which GA4 purchases from June 22–28 recorded a different merchandise amount from the matching Shopify order?
• How many orders and how much merchandise revenue from June 22–28 are affected by missing, repeated, unmatched, or incorrectly valued GA4 purchase records?

• How did Meta’s reported purchases compare with successfully paid Shopify orders from June 15–21 and June 22–28, 2026?
• Which Meta campaigns spent the most money without producing enough GA4-linked, successfully paid Shopify orders from June 22–28?
• Which Meta campaigns appeared to improve from June 15–21 to June 22–28 but produced weaker Shopify-confirmed sales or estimated profit?
• Which Meta campaigns produced the most GA4-linked Shopify sales and estimated profit from June 15–21 and June 22–28?
• What percentage of Meta-reported purchase activity from June 22–28 can be connected through GA4 to successfully paid Shopify orders before Derma Belle reviews campaign budgets?

Buy

• How many observed GA4 sessions from June 22–28 progressed from a landing page to product viewing, cart, checkout, and purchase?
• Which landing pages and advertising sources produced the highest and lowest Shopify-confirmed purchase rates from June 15–21 and June 22–28?
• How much GA4 checkout activity from June 22–28 can be connected to successfully paid Shopify orders?

Leave

• At which shopping step did the largest decline occur between June 15–21 and June 22–28?
• How much of that decline is associated with different visitors, weaker website progression, or missing and inaccurate purchase records?

Return

• What percentage of customers whose first observed paid order occurred in May 2026 purchased again within 30 days?
• Did customers whose first observed paid order occurred May 16–31 return within 30 days less often than customers from May 1–15?
• Which May 2026 customer groups produced the most repeat sales and estimated profit during the 30 days after their first observed paid order?
• Which initial products and supported marketing sources were associated with May customers who purchased again within 30 days?

• How much estimated profit did each product sold in June 2026 leave after discounts, refunds recorded through June 30, and recorded order costs?
• How much did product costs, fulfillment costs, payment fees, dispute fees, and net customer-paid shipping affect estimated June profit?
• Which products generated strong June sales but left little or negative estimated profit?
• Which orders paid during June lost money after discounts, refunds recorded through June 30, and recorded costs?
• Which revenue and cost changes explain the difference in estimated profit margin between May and June 2026?

• Do the balance transactions assigned to payouts issued from June 1–30, 2026, add up to the recorded payout amounts?
• Which payment, refund, fee, or dispute balance transactions dated June 1–30 cannot be matched to the expected order, refund, dispute, or payout?
• Which payment and payout differences from June 22–30 are explained by normal processing time at the June 30 reporting cutoff?
• Which June differences are documented adjustments, and which remain unexplained as of June 30?
• What is the total value of June payment and payout records that still require investigation as of June 30?

• How much sales and estimated profit did each discount code, automatic promotion, and bundle produce in June 2026?
• Which June promotions were attached to orders with negative estimated profit after refunds recorded through June 30 and recorded costs?
• Did promotions and bundles that increased average order value from May to June also increase estimated profit?
• How did June sales and estimated profit from each bundle compare with the related products sold separately during the same month?
• Did bundle sales increase from May to June while sales of the related standalone products declined?