Information architecture (IA) is the skeleton of every website. Get it right, and users find what they need effortlessly. Get it wrong, and even the best content stays hidden.
For Arabic websites, IA is especially challenging. Right-to-left (RTL) layouts, bilingual navigation, and cultural categorization differences all create complexity that card sorting can resolve.
Card sorting is a UX research method where users organize content items into groups that make sense to them. It reveals how your target audience thinks about and categorizes information — directly informing your site's navigation, menus, and content structure.
This guide covers everything you need to know about running card sorting studies for Arabic websites.
Most Arabic websites also serve English-speaking users. This creates a fundamental IA challenge: Arabic and English speakers may categorize the same content differently.
For example:
- A Saudi user might group "payment methods" under "حسابي" (My Account), while an expat user expects it under "Settings"
- "أسئلة شائعة" (FAQ) might be expected under "مساعدة" (Help) by Arabic speakers but under "Resources" by English speakers
- Financial terms, legal content, and product categories often have no direct translation equivalent
Card sorting with users from both language groups reveals these differences before you commit to a navigation structure.
Arabic is a right-to-left language, which affects how users scan and process visual information:
- Reading patterns: Arabic readers scan from right to left, affecting navigation placement
- Visual hierarchy: Primary actions should be on the right side in Arabic interfaces
- Breadcrumbs: Flow right-to-left in Arabic
- Menu order: May need to be reversed or restructured for Arabic layouts
Card sorting results often reveal that Arabic users expect different menu ordering than English users — even when the same categories are used.
Cultural context influences how people organize information:
- Privacy sensitivity: Saudi users may expect privacy-related items to be more prominent
- Social proof: Content like testimonials and reviews may be categorized differently
- Trust signals: Certifications and security badges may need different placement
- Religious and cultural content: May require dedicated categories that do not exist in Western IA patterns
Participants sort items into groups and create their own category labels.
When to use:
- Early in the design process
- When you have no existing IA structure
- When exploring a new content domain
- When building Arabic navigation from scratch
What you learn:
- How users naturally group your content
- What labels users would use for each group
- How many categories users expect
- Whether Arabic and English users group differently
Participants sort items into predefined categories that you provide.
When to use:
- Validating an existing IA structure
- Testing whether your category labels make sense
- Comparing two alternative navigation structures
- After an open sort to validate findings
What you learn:
- How well your categories match user expectations
- Which items are hard to categorize (ambiguous content)
- Whether your labels are clear and intuitive
- Confidence level in your current IA decisions
A combination: some categories are fixed, and participants can create additional ones.
When to use:
- When you have some confident categories but want to explore others
- When validating core navigation while discovering new sections
- For large sites with established and emerging content areas
List 30-50 items that represent your website's content or features. For Arabic websites:
- Write items in both Arabic and English — you will run separate sorts for each language
- Use real content labels — not abstract descriptions
- Include edge cases — items that are hard to categorize reveal IA problems
- Keep items at one level — do not mix page titles with section headers
Example items for a Saudi e-commerce site:
| Arabic |
English |
| طرق الدفع |
Payment Methods |
| سياسة الإرجاع |
Return Policy |
| الأسئلة الشائعة |
FAQ |
| تتبع الطلب |
Order Tracking |
| المحفظة الإلكترونية |
Digital Wallet |
| عروض اليوم |
Today's Deals |
| خدمة العملاء |
Customer Service |
| أحجام الملابس |
Clothing Sizes |
For meaningful results, recruit separately for each language:
- Arabic sort: 15-20 native Arabic speakers (preferably Saudi/Gulf Arabic speakers)
- English sort: 15-20 English speakers (consider both native and ESL users)
- Bilingual sort (optional): 10-15 bilingual users who use both versions of your site
| Your Situation |
Recommended Type |
| Building a new Arabic website |
Open sort |
| Redesigning existing navigation |
Closed sort |
| Launching an Arabic version of an English site |
Open sort for Arabic, closed sort for English |
| Validating a proposed IA structure |
Closed sort |
| Not sure how Arabic users think about your content |
Open sort |
Use a platform like Afkar's card sorting tool that supports Arabic content and RTL interfaces. This ensures:
- Arabic cards display correctly in RTL layout
- Participants can create Arabic category labels
- Results can be analyzed per language group
- The study interface itself is available in Arabic
Card sort analysis typically uses two approaches:
Similarity Matrix: Shows how often pairs of items were grouped together. Look for:
- Clusters of items that are always grouped together → strong categories
- Items that split across groups → ambiguous content that needs reconsideration
Dendrograms: Tree diagrams that show hierarchical relationships between items. Look for:
- Natural groupings that emerge at different levels
- Items that appear at the fringes → these do not fit well anywhere
Some content categories do not translate cleanly between Arabic and English. For example:
- "How-to guides" has no single-word Arabic equivalent — "أدلة إرشادية" or "كيف تسوي" both work
- "Blog" is often kept as "بلوق" (transliteration) rather than "مدونة" in Saudi Arabic
- "Dashboard" is commonly used in English even by Arabic speakers, alongside "لوحة التحكم"
Solution: Run open sorts in both languages independently. Do not assume the English IA translates to Arabic.
In English, the most important menu items are typically on the left—where readers start. In Arabic, they should be on the right. But how far does this principle extend?
- Primary navigation: Reverse order for RTL
- Dropdown menus: Items should flow from right to left
- Breadcrumbs: Must flow right-to-left
- Footer navigation: Follow the same right-to-left principle
Card sorting will not directly tell you about left-right ordering, but it reveals which categories are most important to users, helping you prioritize placement.
Many MENA websites use bilingual labels in their navigation. Card sorting helps you:
- Determine if both languages need separate IA structures
- Find cases where a single structure works for both
- Identify where language-specific categories are needed
Arabic interfaces sometimes need different category depths than English:
- Arabic text is often more compact, allowing more items in dropdown menus
- But readability of Arabic navigation labels decreases faster at deep nesting levels
- Two-level navigation is often ideal for Arabic sites
Run the analysis for Arabic and English results independently:
- Generate a similarity matrix for each language
- Create dendrograms for each language
- List the top categories from each
Map Arabic categories to English categories:
| Arabic Category |
English Category |
Match Level |
| المنتجات |
Products |
Direct |
| حسابي |
My Account |
Direct |
| المساعدة والدعم |
Help & Support |
Direct |
| العروض والخصومات |
Deals & Offers |
Partial |
| الإعدادات والأمان |
Settings |
Partial |
| المجتمع |
Community |
Arabic-only |
Based on your comparison:
- Direct matches → Use the same structure with translated labels
- Partial matches → Use the same top-level category but different sub-categories
- Language-specific → Consider adding categories that only appear in one language, or restructuring
Afkar's card sorting is built for Arabic-first research:
- Full RTL support for card display and category creation
- Arabic and English studies in one platform
- Pre-screened Saudi and Gulf Arabic participants
- Automated similarity matrix and dendrogram analysis
- Export results for further analysis
- Test the study yourself first in both Arabic and English to catch display issues
- Use real navigation labels — not generic descriptions
- Keep card count between 30-50 — fewer gives insufficient data, more fatigues participants
- Allow 15-20 minutes per session
- Top-level categories → Main navigation items
- Sub-groups within categories → Dropdown or sidebar navigation
- Frequently co-grouped items → Consider cross-linking or combined pages
- Ambiguous items → Test with a tree test to validate placement
After redesigning your IA based on card sort results, validate with a tree test:
- Create your proposed navigation hierarchy
- Give participants tasks: "Where would you find shipping information?"
- Measure success rate and directness (how many clicks to find the answer)
- For Arabic sites, run tree tests in both languages
Tree testing is the natural follow-up to card sorting — it validates whether your new IA actually works. Afkar supports tree testing studies alongside card sorts for a complete IA research workflow.
- Card sorting is essential for Arabic websites because Arabic and English speakers categorize differently
- Run separate sorts for each language — do not assume English IA translates directly
- Use open sorts for discovery, closed sorts for validation
- Pay attention to RTL-specific navigation patterns
- Follow up with tree testing to validate your new information architecture
- Target 15-20 participants per language group for reliable results
Information architecture is invisible when it works and infuriating when it does not. Card sorting takes the guesswork out of it.
