Datajar
Case Study

38% of orders were discounted. It cost almost nothing — and bought almost nothing.

An electronics & PC-hardware retailer on Shopify — $2M+ in online revenue across ~4,700 orders in the 4.5 months analyzed — asked one question: “How do we grow revenue 15–25% in the next 3–6 months without burning margin?”

Client anonymized by agreement. Numbers are real, lightly rounded.

38%
of orders carried a discount
0.3%
of revenue — total discount cost
27%
smaller baskets on discounted orders
54%
of revenue from one-time buyers

The Findings

What the data actually said

  1. 1

    The discount illusion

    ~1,800 of ~4,700 orders (38%) carried a discount. Total discount spend: just 0.3% of revenue — so nobody was worried about it. But orders with a discount averaged 27% less than full-price orders, and on promo-heavy days order volume jumped +30% while average order value stayed completely flat. Discounts were buying volume, not basket size. The fix wasn't “discount less” — it was “discount differently”: bundle and threshold mechanics instead of flat cuts.

  2. 2

    More than half the revenue came from customers who never came back

    53.9% of all revenue came from one-time buyers; the repeat rate was 10.4%. Doubling that rate — at current spend levels — is worth roughly +27% more revenue over 18 months with zero new customer acquisition. The data even said where to start: two warm segments covering ~3,200 reachable customers, one of them spending 44% above store average.

  3. 3

    Bestsellers that never sold

    The store's single most-wanted product had ~2,300 views and ~340 add-to-carts in the period — and zero purchases. It wasn't alone: five high-intent products were silently leaking conversions to stock, pricing, or checkout friction that no dashboard was surfacing.

  4. 4

    The bundle attach gap

    Customers who bought PC bundles spent 44% more than the store average — yet 78.6% of bundle orders left with no add-on. The co-purchase data named the exact product pairs to offer, some bought together in 100% of observed cases.

The Output

What they walked away with

  • ✓
    A prioritized 10-action plan, scored by impact and effort, sequenced week by week
  • ✓
    A customer-segment CRM playbook built from real purchase behavior
  • ✓
    The exact products to fix first, ranked by lost-conversion value
  • ✓
    A 90-day SEO roadmap — including the fastest-growing competitor to defend against

All of it came from data the store already had. GA4 and Shopify exports. No data team, no analyst hire, no new tracking setup.

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