← all casesFashion & Accessories · Stainless steel demi-fine jewelry
Bia Aloi
Before 02/05–01/06 (31d) · After 12/06–15/07 (34d) · 81 optimized products
+24,3%
revenue on optimized products
In a period when catalog traffic plunged, the optimized products grew +24,3% in revenue and +13,6% in purchases — versus just +9,8% and +2,7% for the control group.
Revenue · optimized products
Conversion rate
8,33%
before 7,63%
▲ +9,2%
Purchases (items)
1.714
before 1.509
▲ +13,6%
Revenue
R$ 62.579
before R$ 50.350
▲ +24,3%
Views
20.587
before 19.789
▲ +4,0%
§ the challenge
A demi-fine jewelry catalog with dozens of similar earrings, short names and descriptions repeated across products. Hard for the customer to tell pieces apart and for the search engine to understand each one — all during a period of steep traffic decline in the catalog.
§ what we did
01
Attribute standardization
We structured the material, plating, size and occasion of use for each piece — what sets one earring apart from another.
02
Unique titles and descriptions
81 products rewritten with descriptive titles and their own copy, ending the repetition across similar pieces.
03
Care, FAQ and schema
Stainless steel care instructions, frequently asked questions and structured data per product.
04
Control group
We compared the optimized items with 419 non-optimized products in the same store and period — to isolate the effect of the work.
§ how we measured
a transparent, replicable, no-black-box method
The result only counts if you understand exactly how it was measured.
01
Comparable windows
Two periods of the same length, one before and one after the work.
Before · 02/05 – 01/0631 days
After · 12/06 – 15/0734 days
02
Control group
We compared the 72 optimized products with 419 non-optimized products — same store, same period. This isolates the effect of the work from any seasonality or paid media affecting the whole store.
72 optimized
vs
419 control
03
How we calculate
Conversion is always result divided by opportunity — no inflated metric.
items purchased
items viewed
= conversion per product
We excluded the publication period (02–11/06) so as not to mix the transition into the measurement.
Before vs after, side by side
The proof is in the control group
Conversion rose across the whole store in the period — which is why the most robust proof isn't the isolated conversion Δ, but the differential vs the 419 non-optimized products. Among the products with meaningful volume, 68% increased conversion.
Optimized vs the rest of the catalog
Optimized (72)
Conversion7,63% → 8,33% (+0,70 p.p.)
Views/day638 → 606 (−5,1%)
Purchases+13,6%
Revenue+24,3%
Control (419 products)
Conversion6,09% → 7,18% (+1,09 p.p.)
Views/day1.535 → 1.219 (−20,6%)
Purchases+2,7%
Revenue+9,8%
Biggest conversion gains
Product
Views (before → after)
Conversion
Δ
Revenue after
Brinco Gota Alongada Prateado
113 → 125
4,42% → 15,2%
▲ +10,78 p.p.
R$ 488
Brinco Argola Lua Bold Dourada
202 → 381
5,45% → 14,17%
▲ +8,72 p.p.
R$ 746
Brinco Flor Prateado
156 → 323
5,77% → 13,31%
▲ +7,54 p.p.
R$ 625
Brinco Sol Prateado
152 → 313
9,21% → 16,29%
▲ +7,08 p.p.
R$ 780
Brinco Ninho Torcido Dourado
474 → 805
9,7% → 13,79%
▲ +4,09 p.p.
R$ 3.192
Executive summary
In a period of steep traffic decline (−20,6%/day across the rest of the catalog), the optimized products held on to their visits (−5,1%), converted better (8,33% vs 7,18%) and grew +13,6% in purchases and +24,3% in revenue — while the control advanced only +2,7% and +9,8%.
Methodological transparency
Organic Lab's proof here is the differential vs the control group, not the isolated conversion Δ. Among the 34 optimized products with meaningful volume (≥100 views in both periods), 23 (68%) increased conversion.
Full methodological note · Before 02/05–01/06 (31d) · After 12/06–15/07 (34d), excluding the publication period (02–11/06). Optimized = 72 of the 81 products with sales data. Control = 419 non-optimized products, same store and period. Conversion = items purchased ÷ items viewed.
