Case Study

Unlocking 3x More Conversions: How Zoopla Transformed Property Search with TravelTime

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Zoopla, one of the biggest names in the world of property websites, embarked on a transformative journey to enhance the property search experience for its users.

Central to their success was the integration of TravelTime, a groundbreaking API that redefined property search parameters to focus on personalisation through time-based location insights.

Creating a high-converting property website or app is a complex task.

The key lies in connecting potential buyers or renters with property listings that match their unique criteria. However, this challenge becomes complex when considering the diverse factors that influence a property choice.

Zoopla, one of the UK’s leading property websites, recognised that one critical factor for homeowners and renters is commute time data.

Property seekers were not only looking for homes - they were looking for residences that provided an optimal commute to their frequently visited and most important locations, such as offices, schools, green spaces, or family homes.

Traditionally, property search platforms rely on distance-based search parameters. But Zoopla chose to revolutionise this approach, with TravelTime.

Zoopla introduced TravelTime, a groundbreaking API that empowered Zoopla to go beyond the conventional property search.

There are three key ways that TravelTime is being used by Zoopla:

1. Zoopla is embedding journey time data into every search

Instead of just asking users to select a specific location to live, Zoopla prompts them to identify their frequent travel destinations or desirable location features. Property seekers can also specify transport mode preferences and their maximum acceptable travel time to reach these destinations.

TravelTime API then harnesses this data to create a customised search area and personalises the search results ranking more effectively, answering queries like, "Find me a home within a 15-minute drive from my office."

zoopla embedded journey time data into every search

2. Zoopla is personalising every journey using Travel Time

The Single Consumer Profile unifies the data that Zoopla holds about a consumer and generates insights, providing a snapshot of their current needs and journey. Alongside factors including current location, number of bedrooms, budget, and recent activity, TravelTime is an essential building block to this profile.

zoopla’s generated insight on single user, including location

3. Zoopla is performing more intelligent property matching

Using TravelTime data, Zoopla is increasingly able to harness data science to find their property seekers the right property. Higher quality leads to agents, which enables agents to get more value from Zoopla meaning they are less likely to churn, and the end-users remember Zoopla for a great homefinding experience. Further down the road, this means that the users want to use Zoopla in future to sell their home.

zoopla performing intelligent property matching

This dynamic approach frees users from the confines of predefined neighbourhoods and knowing exactly where they want to live, offering a more personalised and flexible property search experience.

“More than 20% of property seekers don’t know where they want to live. For a very long time, we just had to hope that these users would do their own research and come back to Zoopla to perform this final search. Now, with TravelTime, we can help these users much earlier on in their property search journey, providing a more personalised discovery process based on what they need to be near, how long they want to travel, and by what transport mode.”

- Ben Amos, Senior Product Manager, Zoopla

Driving a 300% increase in conversions

The impact of TravelTime was nothing short of remarkable. Within just 10 months of its launch, Zoopla had “achieved an impressive 300% increase in conversions”.

These conversions represented users who had not only expressed interest but had taken the next step by booking viewing appointments, and is 3x higher than when using just distance.

By delivering highly relevant search results based on commute time preferences, Zoopla empowered its customers to make well-informed decisions. This newfound confidence in their property choices translated into higher conversion rates.

"We’re pleased to announce that our travel time tool has achieved an impressive 300% increase in conversions. We believe that because the results are more relevant to the quality of leads we pass to our members is higher. We’re delighted that the tools and services we provide our consumers can deliver such commercial benefits to our members."

- Matt Cohan, Chief Product Officer, Zoopla

How TravelTime works

TravelTime’s success can be attributed to its ability to filter out misleading results and present only the most relevant options to users.

For instance, the API can demonstrate that a mile’s distance in the suburbs might take only 5 minutes by car, but in a bustling city, it could be an hour-long commute—something that distance-based search methods often overlook.

Furthermore, TravelTime factors in locations with efficient transport links, even if they are physically further away. This prevents the exclusion of potentially attractive areas for prospective buyers. Chris Hutchinson, Chief Customer Officer at TravelTime, demonstrates this value: “TravelTime is uniquely positioned to deliver public transport insights, as well as driving, walking, and cycling - or a combination. This makes it more effective for the end-user, particularly when it comes to searching in a city.”

Elevate your property search with TravelTime

If you want to replicate Zoopla’s success and provide your users with more relevant, personalised search results, integrate the TravelTime API into your platform.

Unlock the potential for higher conversions and happier customers by adopting this innovative approach to property search.

Get started for free by signing up for an API key or request a demo from one of our team.

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Display more relevant, personalised search results with the TravelTime API

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