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The OLX Group is one of the world’s fastest-growing network of trading platforms for 300 million+ people around the world. After launching the OLX Marketplace in India, the platform became one of the largest classifieds to buy, sell and exchange a variety of products in the country. As the product gained more users, it witnessed a high recall rate across all categories, including electronics, household appliances, fashion and transportation.
However, based on the data from their longstanding interactions, OLX realised that buyer needs were quickly changing and there was a need to pivot from the classifieds way of doing things.
To harness their true potential and build a product that could stand the test of time, the team needed to evolve OLX’s already successful platform into something that could stay relevant for years to come.
Predict 01Harnessing big data insights to predict consumer behaviour and pivot to a hyperlocal-first marketplace
Explore 02Turning passive consumption into active purchases by exploring new ideas and refining the browse experience
Modify 03Modifying the ad creation journey to elevate both the buyer and seller experience thereby increasing deal conversions
Harnessing big data insights to predict consumer behaviour and pivot to a hyperlocal-first marketplace
OLX was already one of the frontrunners in the classifieds space in India. But to continuously deliver solutions that evolved with user needs, the team needed to study market trends and equip themselves for any foreseeable changes.
While synthesizing big data, it was discovered that since hyperlocal services such as Dunzo were not mainstream at the time, buyers preferred purchasing from sellers near them to avoid the hassle of transportation.
Based on this insight and the rise of hyperlocal delivery, the team predicted that buyer expectations from their platform would gradually change to hyperlocal-first. To tackle this, a new filter was introduced to surface results based on distance. By prioritising buyer preferences to shop within a certain geographical radius, the team brought the ease of shopping from a neighbourhood store onto the platform.
Turning passive consumption into active purchases by exploring new ideas and refining the browse experience
After the platform was redesigned to be hyperlocal-first, it was also observed that buyers did not necessarily come in looking for a specific product. Instead, they responded better to bargain deals irrespective of what category they had initially searched for on the app.
Borrowing from the idea of window shopping where people look for a wide range of products in actual markets, the team pivoted the core experience from a “search for what you need” listings platform to a “browse through what you might like” marketplace. To keep the app experience relatable, the team ran a series of experiments to test different ideas and refine the new experience. Based on past user search patterns and ongoing deals, the browse-first C2C marketplace now showcased results that allowed buyers to browse through deals across categories and pick what best suited their desires.
Modifying the ad creation journey to elevate the buyer and seller experience and increase deal conversions
Having established the need to move towards a browse-first experience, a major intervention was made to ensure that seller ads were rich with information so that the buyers could be shown the most relevant products when browsing.
To do so, the team modified the ad creation experience while ensuring that the sellers did not find the process lengthy or cumbersome. Instead of a process where sellers first add all product details and then upload pictures, the journey was switched to uploading the pictures first.
The platform then employed an image recognition AI library to fetch a product description. This meant that sellers had to add very little information manually.
By building an extremely intuitive ad creation process, the team reduced the time it took to list new ads. This led to a reduction in drop-offs during ad creation and consequently, an increase in the number of products being listed. This two-in-one result increased deal conversion rates while providing buyers with ample information to guide their purchases.