By the Numbers: Using Google Trends to Analyze Real Estate Demand

David Diwik
4 min read

It is well-known that real estate has been slow to catch up with the burgeoning use of data science in financial analysis. However, things are starting to change:

Essentially, the research involves getting region-by-region search volume data for terms such as “commercial property”, “commercial real estate”, and “jones lang lasalle.” This has shown to be highly predictive of medium-term real estate price movements. In fact, See the below image for U.S. market results (Dietzel et al. 2014).




How can this apply to emerging markets?

When this research is applied to emerging markets things get even more interesting. Emerging markets notoriously have a data availability problem, which makes Google search volume all the more useful since it is one of the few accessible data feeds that is both highly precise and available virtually in real time. So what are the results?

Venkataraman et al. (2017) conducted an analysis for four large cities in India and found that Google search volume data was eight times as predictive as it was in the U.S.[1]. For example, a 1% increase in the search intensity for the word “sale” within Google’s real estate category lead to a 0.132% abnormal quarterly increase in housing prices. This is while controlling for factors such as population and construction costs[2]. Because of the delays associated with getting Indian real estate data, this means that Google trends data could be particularly relevant in evaluating Indian real estate markets.


Still Reasons to Be Cautious

The success of Google trends data is a promising development that is broadly indicative of the power of alternative data in a world in which traditional data sources aren’t always reliable. It gives a base case for how technology can provide elements of transparency that will facilitate investment into underdeveloped and emerging markets.

While the results of these studies are encouraging, there is still reason to be cautious about using Google search volume data to predict real estate movements. Here at Propeterra we conducted an internal econometric analysis on the predictive power of Google trends data on Singaporean real estate markets with disappointing results. Additionally, one should be cautious of using Google trends data where Google is not the primary search engine, such as in China or South Korea, or where levels of internet usage are weak, such as in Pakistan.


The Wrap

At Propeterra we enjoy staying on top of technology trends that will lead to new insights into the analysis of real estate markets. Sometimes, however, it is important to remain skeptical of which technologies and data sources will have a real impact on improving analytical insights.

Google trends is a promising source of data, especially in geographies where little reliable data is available. Nonetheless, for predicting real estate markets it offers mixed results.

[1] Mumbai, Delhi, Bangalore, Chennai
[2] For those who want to do a deeper dive see the notes (below) for the full econometric output (Venkataraman 2017)



1) Venkataraman's Econometric output for Indian real estate (Source: Venkataraman 2017)

Lag is indicative of how many quarters prior the data is from. For example, SalesSVI_Lag1 is the predictive power of search volume for sales (Sales Search Volume Index) from one quarter prior on current real estate prices.

HPIRet_Ab = Abnormal return on the city (lag 1 for one quarter prior)

SalesSVI_Ab = Abnormal uptick in searches for the keyword “Sales”

RentSVI_Ab = Abnormal searches for the keyword “Rent”

Pop_Growth = Annual population growth

Q = Quarterly dummy variable to remove seasonal effects

Change_CCI = Prior period increase in construction cost index

StkRet = Stock market return of the previous period

REUnsold_mths = Number of vacancy months in the past two quarters for the given city




a) "Does Internet Search Intensity Predict House Prices in Emerging Markets? A Case of India" (2017). Authors: Ekta Jalan, Venkatesh Panchapagesan, Madalasa Venkataraman

b) "Sentiment-based commercial real estate forecasting with Google search volume data" (2014). Authors: Marian Dietzel, Nicole Braum, Wolfgang Schafers

Leave a Comment
Recent Articles

Sign up to receive the Propeterra's newsletter and exclusive property news and updates. You can unsubscribe at any time by clicking on the unsubscribe links in our emails.



posts by tag

See all

Market Cover_Emerging Markets-1


Market Cover_Frontier Markets-1


Market Cover_Special Situations-1-1


Market Cover_Developed Markets-1


Recent Articles

2 minutes read

It’s Ski Season! Four Resorts to Invest In Now

The swish of skis, the powder on the slopes and the crisp mountain air… With Covid restrictions easing, many holidaymakers’ thoughts are turning to travel - and with the winter sports season in full flow, what better time to look at the resorts that offer the most bang for your investment bucks? Read on for Propeterra’s rundown of our favourite ski destinations - including some you’d never have expected!

Niseko, Japan

Japan might not seem like an obvious skiing destination, but the snow at Niseko is hard to beat. Located in the northern Japanese island of Hokkaido, the annual snowfall is a staggering 15 metres - so unlike some less fortunate resorts in warming parts of Europe, your good skiing is practically guaranteed. Niseko is also renowned for its beautiful scenery and luxury accommodations - and with New Chitose International Airport a short two hour drive away, as well as the Hokkaido Shinkansen connection coming in 2030, it’s never been easier to travel there.

Prime investment opportunities available now include the Pavilions Resort Villas and the Ginto Residences - and for more information on the area, Propeterra’s Niseko Report is available for download now.

3 minutes read

Affordable Housing - the ADB and Lessons from the UK

The Asian Development Bank (ADB) recently released a briefing paper attempting to
learn lessons from the UK as to successes and failures of affordable housing policy. It is
justifiable to critique the UK’s faltering policy of delivery over a number of decades, but
this is precisely why it is a fruitful area of enquiry from analysts considering other parts
of the world. The UK has benefitted from significant resources, and policymakers have
been under considerable pressure from the electorate to ensure adequate housing across tenures. This is why the Chief of the Urban Sector Group at the ADB, Manoj Sharma, saw fit to commission this work, and report on its conclusions.

3 minutes read

Back to desks and back to the city!