StartInsightsArticlesHow a property developer uses data for success

How a property developer uses data for success

What data are they interested in?

Examples of data they are looking at are:

  • Statistics regarding interest in previous projects

What has the interest looked like in the past for similar projects? Among other things, they look at registrations of interest (linked to either entire projects or to specific objects), link clicks in newsletters and campaign site visits.

  • Past customers and prospects

By saving their data, they have a valuable bank of potential buyers that they can address directly when planning new projects. With sufficient structure, they can easily segment by e.g. previous expressions of interest, the type of property they were interested in, age and previous residence.

  • Statistics on past sales

D.E. can forecast sales by looking at the average time it has taken in the past to sell properties of a similar type. How many viewings have been required? Which properties have been the easiest and hardest to sell?

How will they use their data?

Now that the groundwork is done and all the data is collected and structured, Dreambuilders Estate can easily see the following:

  • What kind of projects and areas are the most and least popular?

By comparing and analysing their data, they can easily find out which projects generate the most and least interest early on in the development process. With that knowledge, they can make informed decisions about how to proceed.

In a high demand project, there may be steps to take to maximise sales.

In less popular projects, quick actions are needed to change the trend. In this project, D.E has planned to build mainly 3-bedroom units, but they are only receiving expressions of interest for the 2-bedroom units. Thanks to their accessible data, they see this pattern immediately. The way forward for D.E. may mean correcting their blueprints, or changing their marketing strategy.

  • Who is the primary target audience for this project?

By analysing previous data, they see that this type of project has previously attracted mainly the 40-50 age group, and families with children rather than single households.

In their upcoming communication about the project, they therefore choose to make extra mailings to that particular target group.

After each project, D.E. analyses the end result, which either validates that their theory about the target group is correct, or gives them the insight that the market has changed. Important knowledge to take with them in future projects.

  • Data-based communication strategies

As D.E’s projects are long term, it’s important to stay relevant over time and remain top of mind with personalised and engaging content. D.E achieves this with minimal effort thanks to marketing automation tools. Using these tools, they create a number of different communication flows, which contain mailings in the form of emails or text messages. The messages in these are adapted to different target groups.

It is easy for D.E. to set it up so that those who click on a newsletter continue to receive the emails frequently, but those who do not click anywhere (and thus are assumed to have a cooler interest) receive newsletters more rarely or with a different content that may be more relevant. By organising its data, D.E. can easily create different audiences and reach out with the right information, to the right audience, at the right time.

With a communication strategy that focuses on personalisation and automation, they can get a lot of information out and stay top of mind – with minimal effort.

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