What is naver
Naver is South Korea’s largest internet platform, and its mobile app serves
as the country’s most widely used gateway for search and content.
Within a single app, customers can access news, blogs, communities, shopping, and payments.
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The Unique Characteristics of Naver Shopping
Naver Shopping can only be accessed through the Naver app, as it does not have a dedicated standalone app.
When opening the Shopping tab, the Shopping Feed is displayed first, with the Shopping Home nested one level deeper as a secondary screen.
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The Need for a Shopping Home Redesign
The Naver app's tab bar redesign brought Shopping Home to the forefront for the very first time. After 10 years buried at the 2nd depth, it was finally time to redesign everything from scratch.
PROBLEM 01. HEADER AREA
Low click-through rate on content
84.2% of all clicks occurred within the GNB, with hamburger menu exits accounting for the highest share at 42.8%. Users weren't engaging with home content — they were looking for their own shopping information.
Wasted space above the fold
Digging deeper into the hamburger menu exit data, 70.4% of users who exited went on to check their order and delivery status. The information users needed most was buried deep in the app hierarchy — nowhere near the top.
Hamburger menu drove ~43% of top clicks
70.4% checked order status
Ads that weren't pulling their weight
The top banner ad click-through rate was just 2.4%. The content users actually wanted was hidden away, while prime real estate at the top of the screen was occupied by ads that barely drove any clicks.
PROBLEM 02. MODULE CONTENTS
Unappealing Shopping Home Content
The content provided on the Shopping Home failed to capture users' interest.
Most of the products and brands displayed were presented uniformly, without reflecting individual preferences or personal interests.
The one thing users did care about: recommendation modules
While the average click-through rate across recommendation modules was a low 0.7%,
modules powered by personal shopping data showed CTRs up to 13x higher than average.
Users were only responding to content that felt personally relevant — not one-size-fits-all recommendations.
Recommendations
based on age and gender
0.3%
4%
Modules powered by personal shopping data
3.3%
2.5%
PROBLEM 03. VERTICAL SERVICE
Low traffic to vertical pages
With most users exiting via the GNB and the hero banner dominating the top of the screen, the LNB vertical tab click-through rate stood at just 2.4%.
2.4% of total clicks
Vertical landing buttons that failed to showcase what was inside
There were over 20 verticals, each with its own distinct look and experience — but simple icon buttons offered no way to convey that richness to users.
Goal
Shopping Home Redesign Goal and Strategy
Goal
SOLUTION 02. UTILITY
A MY module at the top, surfacing only what users actually need
With 70.4% of hamburger menu exits leading to order and delivery checks, it was clear users needed MY information far more than home content. I curated the highest-traffic menu items into a MY module at the top, and designed the structure to re-engage purchase intent by surfacing cart and wishlist items.
Ads absorbed into modules, not dominating the top
I removed the top banner ad and redistributed ad exposure across recommendation modules lower on the page. Despite reducing the overall ad footprint, this structure generated higher ad revenue than before.
Ad placements interspersed
within standard modules
SOLUTION 01. PERSONALIZATION
Recommendations tailored to each user's shopping context
Personal data-driven modules outperformed average CTR by 13x, leading me to design a recommendation architecture structured as real-time → personalized → ranking, rooted in each user's shopping history.
Personalization
Real-time
Ranking-based
New products surfaced via real-time click data
Driven by search history
Keyword extraction
A 3×2 grid for product listings
Data from the Grocery vertical showed that an expanded grid layout outperformed a swipeable carousel in CTR.
I applied the same 3×2 expanded structure and set up separate post-launch monitoring to account for contextual differences.
Type
UV
In-page click ratio
Carousel
74
3.3%
2X2 Grid
1,729
4.8%
1.5%
SOLUTION 03. EXPLORATION
Improving vertical page entry points
With the LNB CTR at just 2.4% and most verticals hidden behind a "more" button, discoverability was a clear problem.
I redesigned the entry point structure to surface both official brand stores and SmartStores simultaneously through a shortcut layout.
Vertical modules that showcase what makes each vertical unique
I collaborated closely with each vertical business unit to design modules that highlight the distinct strengths of every vertical. Since the structure served the same content to all users without personalization, I set up separate post-launch monitoring to track performance.
UI IMPROVEMENT
Unified experience across mobile and PC with responsive design
I applied responsive design across mobile, tablet, and PC environments to deliver a consistent shopping experience regardless of device.
validation
Evaluating the Success of Renewal Strategy
Validated
Daily average clicks on Shopping Home grew from 2.37M to 4.19M — a 77% increase.
Recommendation modules stayed active all the way to the bottom of the page, with the lowest widgets still generating 50K daily clicks, showing that users were actively exploring well past the fold.
4.5M
4.0M
3.5M
3.0M
2.5M
2.0M
1.5M
Daily Average Clicks
4.19M
2.37M
Released
5.0M
Validated
The MY module drove 1.08M daily average clicks. By bringing the information users needed directly to the home screen, we removed the structural reason to navigate away.
1.08M
Daily Average Clicks
Partially validated
The shortcut area showed no meaningful CTR improvement over the previous LNB, and vertical modules averaged around 100 daily clicks. Providing entry points alone was not enough to drive engagement.
60K
70K
50K
40K
30K
20K
10K
3.7K
50K
60K
Released
Shortcut Click Trends
result
UV up 40%. Daily average GMV grew from ₩80M to ₩300M — roughly 4x growth.
A combined result of improved accessibility and the home redesign, this proved that a structural overhaul can translate directly into real business impact.
770K
550K
670K
5 Days Before Launch
Release
5 Days After Launch
+40%
900K
700K
500K
300K
100K
350M
300M
250M
200M
150M
100M
50M
0 (KRW)
Pre-launch
Post-launch
80M
300M
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