Ensemble
SEO Specialist · Oct 2024 – Jul 2026 · Luxury multi-designer fashion e-commerce
The challenge
Improve organic visibility and e-commerce performance, while actually understanding which categories, markets and customer segments were driving the growth — rather than assuming.
My approach
Analysed GA4 total users across designer, category and occasion pages from 2024 to 2026 to find which content types and search terms were actually driving growth, then concentrated expansion there instead of spreading effort evenly.
What I did
- Standardised meta titles and descriptions across category, designer and product pages
- Resolved product-feed and Merchant Center errors limiting product visibility
- Led content expansion across designer, category and occasion pages
- Built AI-assisted content workflows with editorial review on top
Designer pages — GA4 users
Top four pages by 2026 traffic. The designer listing page nearly doubled again in 2026, while long-tail designer pages like asal-by-abu-sandeep grew more than tenfold from a standing start.
| Designer page | 2024 | 2025 | 2026 | 2025 change | 2026 change |
|---|---|---|---|---|---|
| designers.html | 1,403 | 2,658 | 5,105 | +89.5% | +92.1% |
| reik | 512 | 909 | 1,152 | +77.5% | +26.7% |
| asal-by-abu-sandeep | 104 | 536 | 1,113 | +415.4% | +107.6% |
| yam | 586 | 794 | 940 | +35.5% | +18.4% |
Occasion pages — GA4 users
Top four pages by 2026 traffic. Wedding-related occasions saw the sharpest growth of any category — cocktail, sangeet and haldi grew several times over, tracking rising search demand around wedding functions.
| Occasion page | 2024 | 2025 | 2026 | 2025 change | 2026 change |
|---|---|---|---|---|---|
| cocktail | 63 | 680 | 2,111 | +979.4% | +210.4% |
| resort-wear | 940 | 1,829 | 1,975 | +94.6% | +8.0% |
| sangeet | 40 | 308 | 1,745 | +670.0% | +466.6% |
| haldi | 49 | 218 | 1,447 | +344.9% | +563.8% |
Women's clothing pages — GA4 users
Top four pages by 2026 traffic. Every subcategory grew across 2024–2026 — dresses stayed the largest and steadiest driver, while the clothing listing page posted the sharpest relative gain.
| Clothing page | 2024 | 2025 | 2026 | 2025 change | 2026 change |
|---|---|---|---|---|---|
| dresses | 3,719 | 4,627 | 5,960 | +24.4% | +28.8% |
| women/clothing.html | 305 | 1,493 | 3,100 | +389.5% | +107.6% |
| coordinate-sets | 1,504 | 1,932 | 2,292 | +28.5% | +18.6% |
| tops | 745 | 966 | 1,830 | +29.7% | +89.4% |
Also shipped at Ensemble
First 90 days — Merchant Center
Product names were being incorrectly appended with "Ensemble" in Google Merchant Center. Traced it to source and fixed it, a feed-level issue that could have quietly affected product visibility and shopping ad performance.
The content framework
A single system for how every category, occasion and designer page gets written — H1/H2 structure, fabric mapped to occasion and mood, designer storytelling, and which product suits which occasion. This framework underpins the traffic growth in the tables above.
Market intelligence from sales data
Dissected MOSS sales data by city, country, designer, category, price and quantity at once rather than looking at revenue in isolation. Findings informed where to focus content, marketing and inventory attention.
The product naming experiment that failed
Tested adding descriptive keywords — "lehenga", "bridal", price ranges — in front of ~100 product names. It largely flopped against its SEO goal, but unexpectedly improved Ads performance and lead quality. A reminder to track downstream impact, not just the metric you set out to move.
Email & WhatsApp ownership
The person running MoEngage left with no handover. Self-taught the platform in about a month, then redefined the role beyond scheduling — becoming the bridge between campaign data and the creative team, surfacing performance by country, open and click rates, and designer-level results. Ran it 6–7 months.
Database consolidation
Customer data lived across three or four inconsistent databases. Consolidated everything into one standard format, including the unglamorous work of cleaning and sorting phone numbers by country — giving targeting a reliable foundation.