Nairobi Development
Inventory & Booking Tracker
A developing view of how selected Nairobi apartment projects are moving, what inventory remains, and which price and unit segments appear to be attracting buyers.
Developer availability sheets can be stale, corrected or inconsistently coded. For these graphics, “sold” includes units marked reserved or paid because they are no longer available. Detailed project data still separates reserved from paid/booked where the developer provides that distinction.
What the current dataset suggests
Use the filters to compare projects. Booking share is the percentage of observed units marked as booked or deposit paid on the latest available sheet.
Share of Project Units Sold
Sold includes units marked reserved or paid on the developer’s latest availability sheet. This shows current project position, not sales speed.
Units Sold Over Time
Sold includes reserved and paid units. A falling count means units returned to availability or the developer corrected the sheet.
What is each project actually made of?
Project sold share is easier to interpret when we know the underlying inventory mix. A development dominated by compact one-bedrooms serves a different buyer pool than one built mainly around two- and three-bedroom homes.
As unit-level history grows, each segment can show its own current availability, booked share, net 30-day booking speed, 20% deposit benchmark price and price per sqm by neighborhood. Hephe pipeline movement remains separate until its four transaction stages are fully split.
Latest inventory, pricing and confidence
Price comparisons use the developer’s 20% deposit payment-plan asking price where available. Cash discounts, larger-deposit incentives and temporary promotions should be tracked separately.
| Development | Area | Observed Units | Available | Reserved | Booked | Sold Share | Observed Price Range | Snapshots | Confidence |
|---|
Entry Price vs Share of Units Sold
This compares current entry price with the share of observed inventory marked booked. It does not by itself prove investment quality or sales speed.
How Fast Are Units Selling?
We track new bookings minus units that return to availability. This is more useful than counting every booking once and ignoring cancellations, re-releases or sheet corrections.
Observed asking price per sqm by neighborhood
The area index uses unit-level price and size pairs from the latest available project price lists. It should be read as an observed sample, not yet as a complete Nairobi market average.
Current project sample
Comparable pricing, not just headline prices
| Neighborhood | Observed Projects | Low KES/SQM | Median KES/SQM | High KES/SQM | Current Sample | Coverage Note |
|---|
Which unit types appear to move in each area?
This is the core long-term value of the tracker: demand by neighborhood, bedroom type, sqm band, total price and price per sqm.
| Area | Unit Segment | Size | Total Price | Price per SQM | Sold Share | 30-Day Sales Speed | Current Signal |
|---|
Diplomat Layout Sales Share
This is a project-specific signal, not yet a Nairobi-wide conclusion. As Berkeley, Belgravia, Cheval and more developments gain unit-level history, this section can compare like-for-like layouts across Westlands, Kileleshwa, Riverside and other areas.
What is useful already
Marketing claims can be tested
“Selling fast” becomes measurable when we retain dated sheets instead of relying on a single current availability list.
Re-releases become visible
When booked inventory later appears available again, the system can separate gross bookings from net inventory absorption.
True market-wide unit preference
Reliable studio versus one-bedroom versus two-bedroom conclusions require more projects and consistent weekly snapshots.
Pricing elasticity
We need repeated price lists to test whether price increases slow bookings or whether strong demand continues through increases.
How Almasi interprets developer availability
The goal is a consistent observed-market measure, not a claim that every developer sheet is perfectly accurate.
Archive every dated sheet
Old sheets are never replaced. Each file becomes a historical inventory snapshot.
Normalize each legend
Developer colours and labels are translated into Available, Reserved, Booked or Unknown.
Compare units between dates
New bookings, status corrections, re-releases and price changes are tracked separately.
Score data confidence
Structured spreadsheets and confirmed legends receive more weight than scans or visually inferred colours.
Data notes, confidence and developer status rules
This information matters for auditability, but it is not the main buyer-facing insight. It explains how each developer’s availability markings were normalized.
For these market graphics, a unit is counted as sold when the developer marks it reserved or paid, meaning it is no longer available. Reserved and paid/booked remain separate secondary stages in the detailed data. Decorative price lines or formatting that do not mark a unit are ignored.
Market movement is useful. Unit-level judgment still matters more.
Almasi helps buyers compare the project, specific unit, price, payment plan, legal terms, view, floor, competing supply and realistic rental strategy before committing.