March

Building a recommendation engine for March Real Estate

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In commercial real estate, finding the right match is often slow and reactive. March set out to change that using AI to transform lead generation into a proactive engine for growth.

 

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March_Poland, Warzawa, two businessmen under discussion By westend61_envato

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March, a Belgian proptech startup, partnered with ML6 and Bothrs to develop the March Matching Engine, an internal tool that uses machine learning and over 50 property features to identify high-potential prospects. This proactive recommendation system shifted March from reactive outreach to data-driven targeting, leading to a 7x increase in new contacts per day, with 45% of leads now generated by the engine. Within four weeks, 70% of companies responded, and 10% confirmed an active search for a new location, positioning March well ahead of competitors in efficiency and innovation.

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About this client

The Belgian startup March is a fast-growing commercial property company specialised in matching companies looking to rent or buy commercial real estate with developers and owners. In the generally conservative real estate industry, March differentiates itself as an innovative proptech player which has the human element at heart. At its core, the company uses data intelligence to generate high-impact leads, thereby freeing the time of its real estate agents to focus on the customer.

Impact

Since integrating the proactive recommendation tool, the number of leads from the matching engine skyrocketed to almost 7x the number of new contacts per day. 45% of March leads are now realized using the March Matching Engine.

By using a data-driven approach, March also gets a high response rate from companies. Four weeks after the initial contact 70 percent responded, and 10 percent of the companies contacted indicated that they are actually looking for a new location at that moment.

7X

Increase in the number of new contacts per day from the matching engine. 

45%

Of March leads are now realized using the March Matching Engine. 

70%

Response rate within four weeks, with 10% actively looking for a new location.

Challenge

A lot of factors influence the location decision of business space for different companies in various industries. March’s vision was to use all these variables in a fast and efficient way for targeted prospecting in order to find the optimal match between companies and business space owners. That is why they got in touch with ML6. 

45% of our leads are now coming from the March Matching Engine. That is very much in line with our ambition to be twice as efficient in our industry than our competitors. We are on the right track and can continue to work on making our algorithm even more accurate by adding more features and further fine-tuning the model.
philippe meire - march
Philippe MeireCo-founder & CEO

Solution

March, together with ML6 and experience design studio Bothrs, developed an internal online tool that makes it easy to determine high-potential prospects for a particular property, based on their suitability for that location as determined by machine learning algorithms. The March Companions can leverage personalised information to approach these leads, allowing March to pivot from a reactive to a proactive approach.

  • Data and Features

    The March Matching Engine starts from a large collection of private and public data. More than 50 features analyse the location, the building and the parcel of each property in Belgium.

  • Reports and Offers

    This allows employees to generate reports for potential clients, show them related property scores and bring all valuable factors together in a single, convenient overview. In addition, the tool has a few other features, such as personal and auto-generated offers.

Results

Since integrating the proactive recommendation tool, the number of leads from the matching engine skyrocketed to almost 7x the number of new contacts per day. 45% of March leads are now realized using the March Matching Engine. By using a data-driven approach, March also gets a high response rate from companies. Four weeks after the initial contact 70 percent responded, and 10 percent of the companies contacted indicated that they are actually looking for a new location at that moment.

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Nicolas Deruytter 39
Nicolas DeruyterFounder & CEO ML6

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Nicolas Deruytter 39
Nicolas DeruyterFounder & CEO ML6
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