Use Data Classification to Find the Perfect Home for Your Customer

Sequence
Sequence
Aug 29, 2018 · 3 min read

Learn how Right Home uses Sequence to optimise data classification for their matching algorithm.

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Sequence helped us where no other solutions were available. They handled a completely unstructured dataset, and managed to convert the data into tasks and classify the data as per our requirements. They are a resourceful partner for any machine learning project.”
- Armelle M., CEO, Right Home.

Right Home is a real estate agency based in Paris that specialises in house hunting. It’s the perfect solution for those looking to buy an apartment or house in the city. Their customers often already have the requirements in mind but don’t have the time or market knowledge to proceed by themselves. Right Home provides a professional and personal service from the first to the last step of the buying process.

Problem Statement

Manually searching for homes in a market made of millions of properties is no mean feat. On top of which many of the website are not optimised and have poor search functionality. This all adds up to inefficient work that is extremely time-intensive.

To overcome this, Right Home uses machine learning to match properties to their client’s requirements. The challenge that then arose was to prepare a large enough data-set for the model. The goal was to categorise the information from tens of thousands of real estate ads into different classes.

Right Home contacted us to figure out how we could help them to prepare their unstructured data-set. As all machine learning models do, they needed a high accuracy outcome to ensure the best quality.

Solution

To provide this quality, we began by on-boarding contributors that had an accuracy of at least 95%. Also, as Right Home is a French company, we selected French speaking contributors for the task. We then ran assessments to give them a clear understanding of the real estate industry’s terms and vocabulary before contributors were able to work on tasks.

To process the unstructured dataset and redistribute the data points as tasks, we build templates that are custom to each project. Our team was able to deliver an intuitive and user friendly interface for our contributors. Allowing them to work with more clarity and less of the clutter from all the unoptimised real estate websites. These templates are a simple way that allows us to save time and money for our clients.

Close collaboration with Right Home was key to the success of this project. Our Account managers are the point of contact that helped us to guarantee a smooth experience for both the contributors and the client. Navigating questions and hurdles together allowed us to improve the project outcome as it went along. Through this partnership, we categorised 20,000 ads, a total of 200,000 data points.

Sequence is an outsourcing service for data science teams. Our products include data annotation, tagging, and classification for all project sizes. We offer a free trial to new customers — learn more at our website: sequence.work.

Sequence Blog

Sequence is a straight-forward outsourcing service for all…

Sequence

Written by

Sequence

Image annotation, tagging, and classification outsourcing. Made for data science teams.

Sequence Blog

Sequence is a straight-forward outsourcing service for all your data labelling needs. Gain more accuracy, completeness, and uniformity across all your datasets.

Sequence

Written by

Sequence

Image annotation, tagging, and classification outsourcing. Made for data science teams.

Sequence Blog

Sequence is a straight-forward outsourcing service for all your data labelling needs. Gain more accuracy, completeness, and uniformity across all your datasets.

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