Over the last several weeks Jenna and I have been shopping for a house in California. We've been living in London for the last three years, and are now preparing to move home to the San Francisco Bay.
By all accounts, this is a great time to buy a house. When we contacted our old friend and real estate agent, Roger Knapp, we were surprised that he sent us so many properties that met our requirements.
Roger sent us 140 possible properties for us to look at. Of those we choose 19 to visit on this trip, and we're hoping to buy one of those 19 this week.
The last time we bought a house, we approached the task in a very loose way. We visited the properties, took some pictures, and discussed them afterward, but we mostly relied on our feelings to tell us which house to buy. We don't have that luxury on this trip, so we've been more rigorous about collecting and collating data on each property we want to consider.
Google Spreadsheets has been a huge help in this. First we created a spreadsheet with MLS number, address, and price. Then we added a gadget to the spreadsheet to create a map with all the properties on it. This spreadsheet had the added advantage that we could share it with Roger, and our families to get their opinions on the properties we are looking at.
We realized pretty quickly that there were many more properties than we could possibly look at, so we introduced a simple subjective rating system. For each property on the list, Jenna and I looked at the MLS page for it, and gave it a rating of 1-5. We decided that we would only look at houses with a 4 or 5 rating.
Next we decided that we should derive some metrics from the data we had in the spreadsheet. So we created a sheet to calculate the monthly mortgage payment for each property with a fixed down payment, and added a price per square foot column to help us understand the underlying cost of each property.
After that we added some formulas to color the cells for our metrics. In each case we sorted the sheet by the metric in question, and divided the different between the lowest number and the highest number by 3. We assigned green, yellow, and red to the cells based on which third of the spread their contents fell in. This allowed us to get a really great overview of the properties, and showed us how some of our favorites were great values and some weren't.
Finally we created a form in the spreadsheet, that we could access from our iPhones while we are visiting the properties. It's got about 20 questions on it, where we ask ourselves to enter a rating of 1-5, and it is keyed off of MLS number. This means that as we are touring a property, Jenna and I can each answer the questions individually, and then send the data back to our spreadsheet.
We'll combine the survey data for each property and the metrics we calculated before to develop a ranking for our potential houses. That data should help us to understand which house is really our favorite across several considerations.
Once this is all done, I'll post the spreadsheet for others to see, but until then, wish us luck.