Every piece of analysis on this site begins with a simple question: what would I need to know if I were putting my own money into this market? That question shapes everything — from the data sources we choose to the way we interpret a quarterly price index or a shift in rental demand.
Over the years, I’ve learned that good research isn’t about having the most data. It’s about knowing which numbers actually matter and which ones are just noise. This page outlines how we approach that distinction — and how we turn raw information into something you can act on.
Where the data comes from
We draw on a mix of primary and secondary sources, always prioritising transparency over convenience. When a government dataset has gaps — and in the Indian context, it often does — we say so rather than smoothing over the cracks.
Our core sources include:
- Reserve Bank of India — for housing price indices, credit flow to the real estate sector, and macroeconomic indicators that shape property cycles.
- National Housing Bank — for RESIDEX data tracking price movements across major cities and tier-II markets.
- Ministry of Housing and Urban Affairs — for policy announcements, affordable housing statistics, and urban development frameworks.
- Municipal corporation records — for project registrations, completion certificates, and local supply-side signals that rarely make headlines.
- Property listing platforms — for real-time asking prices and rental data, cross-referenced against registered transaction values wherever possible.
- Field-level inputs — conversations with local brokers, developers, and property managers across Mumbai, Bangalore, Pune, Hyderabad, and Delhi-NCR.
The last source on that list — the ground-level conversations — often proves the most valuable. A spreadsheet can tell you that prices rose 6% in a quarter. It won’t tell you that buyers in a particular micro-market are holding back because of water supply issues, or that a new metro line is about to reshape rental demand in three neighbourhoods.
How we analyse the numbers
Raw data rarely speaks for itself. A housing price index needs context: what’s happening with employment in that city? Are banks lending more or less to developers? Has stamp duty changed? We layer multiple indicators to build a picture that reflects how these forces interact in practice.
Our analytical approach rests on a few consistent principles:
- City-level, not just national. India’s real estate market isn’t one market — it’s dozens of distinct local markets with their own supply dynamics, cultural preferences, and regulatory environments. We break everything down to the city and neighbourhood level where the data allows.
- Affordability over price alone. A rising price per square foot means little without reference to incomes, interest rates, and rental yields. We track the relationship between property costs and what people actually earn.
- Supply-side realism. Demand forecasts are easy to make and often wrong. We pay equal attention to what’s actually being built, what’s stalled, and what’s in the pipeline — because oversupply has shaped India’s property story as much as demand ever has.
- Longer time horizons. Quarterly data matters, but real estate moves slowly. We default to multi-year trends and avoid drawing conclusions from short-term fluctuations that may reverse in six months.
Connecting macroeconomics to property
This is where my own background shapes the work most directly. Spending years immersed in economic club discussions — where the focus was on business cycles, employment patterns, and policy shifts — trained me to see housing not as a standalone sector but as something deeply embedded in the broader economy.
When the RBI changes interest rates, we don’t just note the impact on home loans. We look at what that rate signal means for developer financing, for rental yields relative to fixed deposits, for the psychology of buyers who’ve been sitting on the fence. When employment data shifts in Bangalore’s tech sector, we trace the implications for residential demand in Whitefield, Sarjapur Road, and the northern suburbs — because those are the places where software professionals actually live.
This kind of connective analysis takes time. It can’t be automated or outsourced to a dashboard. But it’s what separates a useful insight from a recycled press release.
What we don’t do
Being clear about limitations is as important as explaining methods. Here are a few things we deliberately avoid:
- Price predictions. We analyse trends and assess probabilities, but we don’t claim to know where prices will be in twelve months. Anyone who does is either guessing or selling something.
- One-size-fits-all advice. A property that makes sense for a first-time homebuyer in Pune may be a poor investment for someone building a rental portfolio in Chennai. Context always matters.
- Cherry-picked data. If an indicator moves against our previous analysis, we acknowledge it rather than finding a different metric that tells a more convenient story.
How often we update
Major data releases — RBI policy statements, housing price indices, employment reports — trigger updates within days. But the deeper analytical pieces, the ones that synthesise multiple indicators and field-level observations, follow their own rhythm. They come together when the picture has genuinely shifted, not when the content calendar demands a post.
Some of the most important work happens in the gaps between updates: revisiting old assumptions, checking whether a trend we flagged six months ago actually materialised, and staying in touch with people on the ground who see things before the data catches up.
A note on trust
I’ve been on the other side of this equation — reading market analysis, trying to make decisions with incomplete information, wondering whether the author had an agenda they weren’t disclosing. That experience shapes everything about how this site operates.
We don’t take commissions from developers. We don’t run sponsored content disguised as research. If we ever have a relationship with any organisation mentioned in our analysis, we’ll state it plainly. The only thing we’re trying to sell is the quality of our thinking — and that has to earn its place every time you visit this site.
If you have questions about our methods, or if something in our analysis doesn’t add up for you, reach out directly. I read every message and I’m always open to being challenged on the numbers.
— Anjali Desai