Imagine knowing for sure what buyers are looking for… By using insights along the entire value-added chain – from the initial design to the sale of a new build – and cleverly combining data, allmyhomes can make accurate predictions. 

 

There are no end of complex steps involved in the transaction process, including the branding concept and architecture for a new build, the definition of suitable target groups, the generation and qualification of buyer leads, and finally the sale to the end customer through a realtor. Allmyhomes covers all of this with a digital end-to-end platform that provides a complete solution from a single source.

 

One of the main factors involved when recording real estate transactions is time since property sales go through slowly over long periods. This is the complete opposite of, say, standard online shopping. In this case, shoppers spot something they want to buy, make a decision, and pay in one smooth process lasting a matter of minutes. Managing the whole process in the real estate sector now requires careful data archiving and constant monitoring of price changes and all kinds of development within the entire ecosystem and throughout the timeline of the transaction, for example. 

 

From a financial point of view, serious resources (both time and money) are also essential in order to account for the long sales cycles involved with new-build projects. As you can imagine, accurate plans and smart forecasts are a must from the outset. Agility is also an advantage here, with optimizations needing to be continually made throughout the project life cycle and changes requiring quick responses. This approach could be applied to pricing structures, tailored lead follow-ups, and constructive realtor coaching.
The end-to-end platform creates a
feedback loop from transaction to transaction and project to project, which makes it possible to continually learn and in turn make processes all the more efficient.

 

Ultimately, allmyhomes can use data collected all the way along the value-added chain and based on external trends, for instance, to come up with prediction models that deliver crucial findings:

 

  • The top strategic locations for new project developments
  • Target group insights on brand preferences and behaviors
  • The optimum floor plan and fittings in a new residential property
  • The ideal price point to be set to account for the margin and a speedy sale
  • The most effective marketing channels and promotional materials for a project
  • The most suitable realtor for a specific residential property
  • Which residential units will sell when

 

Looking into these aspects by analyzing data generated at all stages of the value-added chain and integrating these into a platform allows for prediction models to be perfected, ultimately providing a better understanding of the market and real estate projects.