AeroJet – Digital Marketing – Cyprus
Deventor is a retail ecommerce brand operating in Cyprus on Shopify. The business was underperforming relative to its existing traffic — navigation friction, weak collection architecture, and a thin product page were depressing conversion efficiency. The store was rebuilt using an analytics-led methodology covering sitemap restructure, collection expansion, filter and sort systems, and an above-the-fold product page redesign, with the measurable outcome of converting existing demand more efficiently before scaling spend.
Objective
Deventor's Shopify store was underperforming relative to existing traffic demand — a conversion problem, not a traffic problem. The contributing UX issues were navigation friction, a collection structure built around internal taxonomy rather than user intent, and a product page that pushed trust signals below the fold. The objective was to apply an analytics-led restructure across sitemap, collections, filtering, and product page architecture, with the measurable outcome of converting existing visitors more efficiently before adding paid spend.
The Outcome
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Advertising Platforms Used
Google Search
Meta Ads
TikTok Ads
Youtube Ads
Tracking & Measurement Platforms Used
GA4
Google Tag Manager
META Pixel
Conversion API
Assets Used
Static Image Ads
Product Catalogue Ads
Video Ads
Carousel Ads
Collection Ads
Display Banners
Landing Pages
Service Pages
Product Pages
Lead Forms
Ecommerce Checkout
Product Feed
CRM Integration
Email Automation
Conversion Tracking
Strategic Approach
Analytics-Led UX Strategy.
The existing store was built around internal taxonomy rather than user behavior, and historical data showed where this was costing conversions — drop-off points, under-served demand, and category pages misaligned with paid traffic intent. The audit defined the structural brief: which collections needed to exist, where filtering had to be introduced, and which product page elements needed to load first. The expected commercial impact: converting existing demand more efficiently before scaling spend.
Collection Architecture Strategy.
The original collection structure was too narrow to support paid media. Meta campaigns were landing on generic category pages, weakening ad-to-page relevance. Collections were expanded and segmented so each paid campaign could land on a page built around its specific intent. This tightens landing-page alignment and improves the conversion work the destination page does.
Product Page Strategy.
The product page wasn't making the conversion case before users scrolled. Trust signals, shipping information, and key purchase context sat below the fold, leaving mobile users especially exposed to drop-off. The page was rebuilt around an above-the-fold trust hierarchy so the buying decision is supported in the first viewport — the highest-leverage change for mobile conversion.
Navigation & Filtering Strategy.
The store had no filter and sort system, which on a retail catalogue forces users to scroll through irrelevant inventory. A filter and sort layer was added across collections, aligned with the attributes the data showed users were trying to narrow by. This reduces category-level friction and directly improves browsing depth and product discoverability.
Key Implementation Highlights
Analytics audit of historical store data to inform structural priorities
Shopify sitemap restructure based on user-flow analysis
Collection expansion aligned with paid media intent and search demand
Filter and sorting system implementation across collection pages
Above-the-fold trust hierarchy redesign on the product page
Mobile-first product page restructuring
Expanded landing-page architecture for Meta Ads
Product photography production for category-level visual consistency
Internal linking optimization across collections
Metric
Performance
CPC
2.4%
ROAS
68%
CTR
0:52
Cost Per Lead
Euro: 1.4
Cost Per Purchase
Euro :0.4
Engagement Rate
+20%
Store Visits
+200/m
The store now converts existing demand more efficiently. Sitemap restructure improved product discoverability and reduced category-level friction, with users reaching relevant inventory in fewer steps.
Collection expansion strengthened paid traffic alignment. Meta Ads now land on pages built around campaign intent rather than generic category pages, increasing landing-page relevance and giving the ad-to-page handoff a clearer conversion path.
The product page rework improved mobile usability where it matters most — the first viewport. Pulling trust signals above the fold gives mobile users the purchase context they need without scrolling, addressing the highest-friction point in the funnel.
The filter and sorting system improved browsing depth and engagement with collection pages, particularly on mobile, where their absence had been driving early abandonment.
Audience Search Intent
GMI’s audience strategy focused on users actively searching for medical services, clinic information, and direct contact options. The structure had to support local patients in Cyprus, while also helping international and English-speaking visitors understand available services before making an inquiry.
Core Audience Profile
The core audience was primarily mobile-first, aged 30–54, and driven mainly by organic search. Cyprus remained the strongest market, with balanced gender intent and moderate returning visitor behavior from users comparing services, doctors, appointment options, and clinic access details.
High-Intent Page Strategy
High-intent pages were prioritised because they directly support patient decision-making. Service pages, doctor pages, appointment areas, contact routes, and location information were structured to reduce browsing friction and help users move from research to inquiry with fewer unnecessary steps.
GEO Visibility Logic
From a GEO perspective, the website needed clearer service naming, location relevance, and structured information hierarchy. This helped search engines and AI systems understand who GMI serves, which medical services are offered, and which pages best match patient inquiry intent.
Channel
Primary Role
CTR
CPC
ROAS
TikTok Spark Ads
Top-of-funnel awareness
1.8%
$0.35
1.9x
Meta (Instagram/Facebook)
Retargeting and conversion
1.2%
$0.85
3.4x
Google Search
High-intent capture
3.5%
$1.20
4.1x
Organic social
Brand building, low cost
2.1%
—
—
Email marketing
Retention, repeat purchase
4.0%
—
8.5x
Key Takeaway
Most ecommerce conversion problems are navigational, not aesthetic — historical store data tells you which structural fixes will move the number before any pixel is redesigned.
FAQs
Why is collection architecture important in ecommerce?
Collection pages are where most paid and organic traffic lands, so their structure directly shapes ad efficiency and conversion rate. Collections built around commercial intent — rather than internal taxonomy — match user demand more accurately, increase landing-page relevance, and reduce wasted ad spend. A well-segmented collection architecture also strengthens internal linking and improves discoverability across the catalogue.
How does ecommerce UX affect paid advertising efficiency?
Paid media efficiency is partly determined by what happens after the click. If landing pages are misaligned with ad intent, navigation is friction-heavy, or product pages fail to convert, ROAS suffers regardless of ad quality. Improving ecommerce UX — particularly collection structure and product page trust signals — lifts the conversion rate of existing traffic and reduces the cost of every campaign.
Why do Shopify product pages need above-the-fold trust signals?
Mobile users make purchase decisions in the first viewport. If trust signals — shipping terms, returns, reviews, guarantees — sit below the fold, users drop off before they encounter the information that would have converted them. Pulling trust hierarchy above the fold addresses the highest-friction point in the mobile funnel.
What causes navigation friction in ecommerce stores?
Navigation friction usually comes from sitemaps built around how the business thinks about its catalogue rather than how users actually browse. Missing filters, oversized categories, unclear collection naming, and weak internal linking all force users to scroll through irrelevant inventory. The fix is to rebuild navigation around user-flow data rather than internal taxonomy.
Why are filters important for ecommerce CRO?
Filters let users narrow inventory by the attributes they actually care about. Without filters, users on large catalogues abandon when they can't quickly find relevant products. Adding a filter and sort system reduces category-level friction, improves browsing depth, and increases the rate at which users reach product pages.