Set a timer for sixty minutes and open a blank spreadsheet. When the timer rings, you will have a tracker that records the sale prices of one building and shows how they move. You need no special skills, only patience with a few formulas.
Choose one building and one source
Pick a single tower, ideally one you might buy in or already own in. A building with many recent sales gives you data faster than a quiet one, and one building keeps the figures comparable. Then decide where the sale prices come from, and write that source in the sheet. Some people use broker reports. Others use dataHabibi, a Dubai platform that turns sales recorded by the Dubai Land Department into a price history for every building. Whichever you choose, use it for every row, so the numbers stay consistent. Give this step ten minutes.
Set up six columns
Label the first row and keep one sale per row. Do not merge cells:
· Date: the month of the sale.
· Price: in AED, as a plain number with no symbols.
· Size: in square feet.
· Floor: the floor number, because floors change prices.
· Price per square foot: calculated, never typed.
· Source: where you found the figure, so you can check it later.
Here is a made-up row: March, 1200000, 800, 14, 1500, broker report. Keep sale prices and asking prices apart. If you track asking prices at all, give them a separate sheet, because mixing the two spoils the comparison. Spend ten minutes on the columns and twenty-five on entering ten to twenty past sales. Older entries give the tracker a history from the first day.
Add three formulas
Assume Date sits in column A, Price in B, Size in C, Floor in D, Price per square foot in E and Source in F. This step takes fifteen minutes.
1. Price per square foot. In E2 type =B2/C2, then copy the formula down the column. Show it as a whole number with no decimals.
2. Typical price per square foot. In a cell beside the table type =MEDIAN(E2:E50). The median is the middle value, so one odd deal moves it far less than it moves an average.
3. Monthly change. Make a small second table with the month in column H and, in column I, the median of that month’s rows. Then =(I3-I2)/I2 gives the change from the month in row 2 to the month in row 3.
If a formula returns an error, look for text in a number cell, such as the letters AED typed into a price.
Update weekly, then read the result
Add new sales once a week, on a fixed day. Ten minutes is enough. After a month, sort the table by floor and let the sheet answer three questions:
· Which floors cost more per square foot, and by how much?
· Is the typical price rising, falling or flat?
· Is the building busy or quiet this month?
Read every answer with the count of sales in mind. In a sample month, the median rises from AED 1,500 to AED 1,560 per square foot on twelve sales, a rise of 4 percent on steady volume. The same rise on three sales proves much less. Treat the first month as a first look. By the third month the median starts to mean something.
Where a platform saves the typing
The weak point of this project is the manual work. Each row means finding a record, checking the size and floor, and copying numbers by hand. A platform that already holds the building’s history does that collecting for you, so you spend the hour reading instead of typing. It also covers thousands of buildings at once, while your sheet covers one. Keep the sheet for the questions only you ask, such as how your own flat compares with the median.
Build the sheet once and you will read every market report with more care. When the weekly typing becomes a chore, take the history from datahabibi.ae and keep the questions for yourself.
