dubizzle

Designing a smarter category tree for the most diverse country in the world

 

The Challenge

In the UAE, dubizzle is the go-to marketplace. But its Classifieds vertical (used for buying and selling secondhand goods) — unlike Real Estate and Motors — wasn’t making money. Still, it played a critical role: it was the gateway for new users, many of whom later moved into revenue-generating verticals. In short, Classifieds had network effects, and needed to be optimized as a growth engine.

Goals

1. Make Sellers Happy

The supply side is harder to scale. Repeat sellers drive marketplace health. So we optimized for seller-side UX and seller-side visibility.

2. Target Untapped Markets

Some high-potential categories (like strollers or car seats) were underperforming because users didn’t realize they existed or couldn’t find them.

3. Improve Search and Discoverability 

The category tree was confusing. Users were getting lost — even when the product they wanted was actually listed.

User Research

I conducted open-ended interviews with users to understand how they think about items, categories, and navigation.
I also leaned heavily on stakeholder input — much of the data I needed was already available internally:

  • 80% of users were male

  • 90% were expats — cultural context really mattered

  • OLX partner companies helped us understand when navigation outperforms search, and vice versa

 

Data Analysis

I dove deep into:

  • Top search terms by volume and conversion

  • Supply/demand mismatches — including categories where one side drastically outpaced the other

  • Seller profiles — discovering that small vendors made up a surprisingly large portion of supply, influencing how categories should be tailored

 

Card Sorting & Tree Testing

  • I ran card sorting sessions both before and after the redesign, using Workflowy for digital sorting and in-person tests with friends and coworkers

  • In one early session, I learned the hard way not to print paper cards too small — one gust of air and the whole UX test went flying 

  • User testing revealed where users got stuck, and even more importantly, why they confused certain categories for others

Guerrilla User Testing

I bribed friends, harassed coworkers in the office kitchen, and used Lookback to record sessions. Testing revealed patterns like:

  • Users confusing categories (e.g., putting fridges under Furniture instead of Appliances)

  • People blending adjacent product types in their minds (e.g., desks and office furniture were often seen as the same category)

     

6-Part Decision-Making Framework

I created a 6-part lens for evaluating and prioritizing changes:

1. Liquidity & Volume

Prioritized high-volume + high-supply categories to keep sellers engaged

🛋️ Example: Furniture had a high number of listings but slower buyer interest. We made it a prominent top-level category to support sellers, even though electronics (which had more demand) stayed one level down due to lower supply and seller churn.

 

2. Network Effect

Some categories act as gateways to high-value verticals — users who browse these categories often go on to generate revenue elsewhere.

⌚️ Example: High-end watches aren’t a major revenue stream themselves, but buyers who browse them often also browse luxury cars — a huge moneymaker for dubizzle. So, we gave luxury watches more visibility in the tree to pull those users into the ecosystem.

    3. Emerging Market Demand

    Stay responsive to external shifts in culture, law, or trends that quietly spike category interest.

    🍼 Example: After the UAE made child car seats mandatory in 2017, demand for them on dubizzle spiked — but the category was buried. We elevated car seats within the baby products section to match growing user interest and make listings easier to discover.

    4. Top to Bottom Reading

    Users tend to click the first category that looks “close enough” — so we needed to order categories in a way that avoided predictable mistakes.

    Example: Many users looking for phones clicked “Electronics” and then gave up, unaware that “Phones & Tablets” was a separate category buried below. We moved it higher to reduce misclicks and bounce rates.

      5. Serendipity

      Sometimes users don’t know exactly what they’re looking for — and that’s a good thing. In those cases, merging related categories encourages browsing and discovery, increasing the chance of a sale. Other times, too much ambiguity or missing filters creates frustration and drop-off — those need to be split or deprioritized.

       

      ✏️Example (merge): A user looking for a black desk might stumble onto a sleek dining table and think, “that could work too.” Instead of segmenting every type of table, we grouped them together under “Tables & Desks” to promote this kind of cross-pollination and boost conversions.

        6. Use of Icons

        With such a culturally diverse user base, icons were more effective than text in helping users quickly understand categories.

        • 🛋️ Example: Instead of labeling “Furniture” with a generic chair emoji, we used a couch icon, since couches were the most commonly listed and most visually distinct item. This helped users recognize the category instantly — even if they didn’t speak English or Arabic.

        Implementation, Rollout, and Outcomes

        • Changes were A/B tested in stages to avoid disrupting millions of existing users

        • Some hypotheses worked immediately; others needed refinement

        • The project sparked deeper internal conversations about taxonomy across other OLX markets

        • Improved seller experience in high-liquidity categories

        • Increased buyer success rate from more intuitive navigation

        • Boosted engagement across verticals by increasing product visibility

        • Created a replicable model for marketplace taxonomy strategy across the region

        Redesigning a category tree might sound tactical — but in marketplaces, it’s often the quiet lever that shapes behavior, engagement, and revenue.
        This project helped me combine UX thinking, data analysis, and business strategy to drive meaningful impact on the product.