Using GIS to Map Change
Using GIS to show that a real estate agent's expansion led to them losing dominance of their most lucrative market.
Well, here’s another in my subscriber-only series of posts. Please feel free to share it with your Twitter or Facebook friends. They’ll get the most benefit from it if they download the FREE eBook though. Unless they do that they wont find out about other new posts in this series.
In the last post I introduced the three basic GIS data structures – Points, Lines and Polygons. I needed to do this so that you would have a chance of understanding this post.
Now, onto the GIS story for today. Its about a Melbourne real estate agent that grew rapidly in the 1990s. I use GIS to show that at the beginning of the 1990s this agent dominated the market on its VERY valuable home ground. However, during the 1990s it underwent a period of expansion, as so many businesses did at that time. But during its very successful expansion the agency took its eyes off its home-turf and lost market share.
This sort of GIS analysis is timeless and applies to so many businesses. This agent would have to ask itself whether losing market share in a very expensive area was worth gaining market share in less expensive areas.
From the eBook…
Real estate agents like to understand how their business is performing in each of their sales areas. Are they selling more homes in some areas than others and what is the value of all homes they’ve sold in an area? How are they performing compared to their competitors – are they selling every home in an area? Every second home? Every fifth home? And are any of these figures changing over time? Let’s look at a GIS project that addresses these questions.
Still in the 1990s, I teamed up with a housing researcher and developed some GIS software to analyse housing markets. The software was simple. It automated the large number of mouse clicks required to produce the GIS maps manually. It turned a list of house sales into dots on a GIS map and then annotated each dot with the sale date, value and agent details. The next step was to relate each dot to a grid square from a GIS street directory. For each real-estate agent we shaded the grid-squares according to the total value of house sales, the number of sales, the market share of each agent, and change in the themes over time.
For me, market share was one of the most interesting series of maps. Market share is the ratio of all the sales in an area compared to the sales made by an individual agent – so if 10 homes were to be sold and one agent sold 5 of them, then that agent would have a 50% market share.
The Hocking Stuart series of maps are typical of the sort of maps we produced. The first map shows that in 1991 they dominated all other agents in Albert Park. The second map shows that they no longer dominated that area in 1996. We met with the agent’s marketing manager and he explained that they had expanded into new geographical areas between these years. The final GIS map shows that during their expansion phase, while increasing the overall value and number of sales, Hocking Stuart lost their home-turf dominance that they had in 1991. Perhaps they were distracted with their expansion?
PLEASE GIVE ME FEEDBACK: This is a young site and I’d like to make it relevant to people wanting to learn GIS. My thoughts are that I’ll start with a few examples of GIS applications, mostly from the eBook before going into detail about GIS theory. I’d really like your feedback about what you want. For example is this video too long for you & would you prefer it to be split up? Or do you just want to know about the GIS techo stuff? Please write you comments below. I make use of the Facebook commenting system – it is a way to ensure less spam on the site.