Problem Statement

User Challenges

• Inconsistent search experience across different query types

• Important content like recipe videos receiving low visibility and engagement

• Difficulty finding complementary products during shopping journey

• Varied user needs not being met by one-size-fits-all search results layout

Business Impact

• Missed revenue opportunities from underutilized upselling/cross-selling

• Low engagement with expensive-to-produce video content

• Suboptimal conversion rates across different search types

• High cart abandonment rates

Research & Discovery

Data Collection

• 30 participants across moderated and unmoderated testing

• Semantic Differential scale evaluation

• Platform analytics analysis

• Search query pattern analysis

Search Specificity Levels & Hypotheses

General Searches

Example queries: "snacks," "breakfast," "drinks"

• Primary Hypothesis (H1): For general searches, a category-first template with visual browsing capabilities (grid layout with category thumbnails) will lead to faster selection times and higher user satisfaction compared to a list-based product layout.

• Secondary Hypothesis (H1a): Users will engage more with filtering options (particularly category refinement) during general searches compared to specific searches.

Medium-Specificity Searches

Example queries: "organic cereal," "gluten-free bread," "fresh fruit"

• Primary Hypothesis (H2): A hybrid template showing both relevant subcategories and top-matching products will result in higher task completion rates compared to either a category-only or product-only layout.

• Secondary Hypothesis (H2a): Users will spend more time comparing products (measured by product detail views) in medium-specificity searches compared to general or specific searches.

Specific Searches

Example queries: "Cheerios 12oz," "Chobani vanilla yogurt," "Red delicious apples"

• Primary Hypothesis (H3): A product-focused template with prominent variant selection (size, flavor, etc.) will result in faster add-to-cart actions compared to templates optimized for browsing.

• Secondary Hypothesis (H3a): Users will require fewer query refinements when presented with a product-focused template for specific searches.

Research Findings

General Search Results

Category-First Template Hypothesis (Supported)

• 73% of users completed tasks faster with category-first layout

• 42% decrease in time to first selection (18s → 10.5s)

• 28% increase in user satisfaction scores

Filter Engagement Hypothesis (Partially Supported)

• 3.2x higher filter usage in general vs specific searches

• Price range filters outperformed category refinement

• Led to enhanced price filter prominence recommendation

Medium-Specificity Results

Hybrid Template Hypothesis (Supported)

• 34% improvement in task completion rates

• 81% success rate without query refinement

• Users leveraged subcategories as natural search refinement tools

Product Comparison Hypothesis (Rejected)

• Lower than expected comparison time for low-cost items

• Average product detail view: 12s vs 22s for specific searches

• Findings influenced final template design priorities

Specific Search Results

Product-Focused Template Hypothesis (Strongly Supported)

• 56% faster add-to-cart actions with variant-forward design

• 92% first-attempt selection success rate

• 4.7/5 average user confidence ratings

Platform-Specific Insights

Mobile vs Web Behavior Analysis

Filter Usage Patterns

• Mobile: Higher reliance on visual filters and quick sort options

• Web: 1.8x higher use of advanced filters

• Platform-specific optimization opportunities identified

Session Characteristics

• Mobile: 40% shorter average session time

• Web: 2.1x more product comparison activity

• Different template optimizations required per platform

Navigation Behaviors

• Mobile: Preferred scroll-through category exploration

• Web: Favored multi-tab comparison approach

• Platform-specific navigation patterns emerged

Design Challenges & Solutions

Mobile Information Architecture

Challenge:

• Complex filtering requirements

• Limited screen real estate

• Need to maintain smooth scrolling experience

Solution:

• Implemented collapsible filter cards

• Developed smart filter presets

• Optimized touch targets and spacing

Video Content Integration

Challenge:

• Initial loading time impacts

• Mobile scroll friction

• Optimal placement determination

Solution:

• Implemented lazy loading

• Optimized thumbnail previews

• Strategic placement based on user testing

Impact Analysis

Video Component Performance

Engagement Improvements

• 47% increase in watch time

• 31% higher click-through rate

• 24% increase in page retention

Additional Benefits

• 28% increase in related product exploration

• Enhanced product detail recall in user interviews

• Improved cross-selling effectiveness

Overall Impact Metrics

Search Efficiency

• 42% reduction in time-to-purchase

• 67% decrease in search refinements

• 89% first-attempt success rate

• 27% reduction in cart abandonment

Key Recommendations

1. Template Adaptivity

• Dynamic template switching based on search specificity

• Specific triggers for template changes

• 31% improvement in conversion rate

2. Mobile-Specific Optimizations

• Simplified filter interface

• Enhanced touch targets

• Platform-specific navigation patterns

3. Video Content Integration

• Lazy loading implementation

• Thumbnail preview optimization

• 47% performance improvement

4. Filter Enhancement Strategy

• Smart filter suggestions

• Personalized filter presets

• Priority ranking based on user behavior

Key Learnings

• Search specificity significantly impacts user behavior and needs

• Platform-specific design considerations are crucial

• Video content placement dramatically affects engagement

• Data-driven template selection outperforms one-size-fits-all approaches

• User research timing is critical for maximum impact