CASE STUDY · PROPTECH SOLUTIONS
Building a digital real estate marketplace from scratch.
- 85%Launched with 1,200 listings, 85% listing completeness, and traffic and conversion tracked from day one
01 · PROJECT OVERVIEW
The client and the brief.
An anonymised real estate company. Name withheld under confidentiality.
A marketplace with search, listing pages and agent onboarding. Buyers could filter by location, price and property type, view photos and send an enquiry. Agents got a simple way to create and manage listings, and a review step for quality. Analytics tracked traffic and conversion from the first day.
- 1The company sold and let property through agents, but had no digital presence for its listings.
- 2Buyers found properties through word of mouth and third-party sites that the company did not control.
- 3Listing details lived in agents' spreadsheets and phone galleries, and photos and descriptions varied widely in quality.
- 4Management could not see which listings drew interest or which led to enquiries.
- 5They wanted their own marketplace, built from nothing, with agents who would actually keep it up to date.
02 · WHAT WENT WRONG
What went wrong, and how we fixed it.
Every engagement hits problems. These were the ones that mattered here, and what we changed so they did not come back.
- PROBLEM 01Our first bulk import copied agent data as it was
Search then showed duplicate listings, inconsistent locality names and photos in odd sizes. Buyers would have lost trust quickly. We paused the launch date, wrote normalisation rules for localities and property types, and added duplicate detection on address and unit.
- PROBLEM 02Agents received a list of records to fix, and nothing was published until it passed the checks
The delay was short, and the launch was cleaner for it.
- PROBLEM 03We hit a second issue after launch
Some agents uploaded dark or cropped photos that passed the field checks but made listings look poor. We added minimum image size and a simple brightness check, plus a manual review for the first listing from each new agent. Quality complaints from buyers dropped, and agents learned the standard quickly.
- PROBLEM 04Quality complaints from buyers dropped, and agents learned the standard quickly
03 · THE PROCESS
How we ran it.
We spent the first phase working with agents and the sales head to define what a good listing contains. That became a required-field checklist. We then built search and listing pages first, because they carried the most risk, and agent tools next. We shipped in weekly increments with a demo to the company's leadership. Before launch we loaded existing inventory in batches, and agents fixed flagged records with our team on short calls. After launch we reviewed traffic, enquiries and listing quality every week.
- 01Step 1
We spent the first phase working with agents and the sales head to define what a good listing contains.
- 02Step 2
That became a required-field checklist.
- 03Step 3
We then built search and listing pages first, because they carried the most risk, and agent tools next.
- 04Step 4
We shipped in weekly increments with a demo to the company's leadership.
- 05Step 5
Before launch we loaded existing inventory in batches, and agents fixed flagged records with our team on short calls.
- 06Step 6
After launch we reviewed traffic, enquiries and listing quality every week.
04 · RESULTS
What changed.
Measured against the way the work ran before the engagement began.
- NOW 01
Listings are created in one system, with a minimum standard, instead of in private spreadsheets.
- NOW 02
Agents see how their listings perform.
- NOW 03
Leadership reviews traffic, enquiries and listing quality each week and decides where to push.
- NOW 04
The company owns its audience and its data rather than renting both from third-party sites.
- 85%
Launched with 1,200 listings, 85% listing completeness, and traffic and conversion tracked from day one
05 · WHAT WE BUILT
How it works.
- The platform has a web front end, an API and a relational database, with a dedicated search index for fast filtering by location and price.
- Images are uploaded to object storage, resized on upload and served through a CDN.
- Agent accounts have roles, and a listing moves through draft, review and published states.
- A completeness score is calculated per listing from required fields and photo count, and low-scoring listings are held back from search ranking.
- Pages are server-rendered so they can be indexed by search engines.
- Event tracking records searches, listing views and enquiries, so conversion could be measured from launch.
06 · QUICK ANSWERS
The short version.
- What problem did the client have?
- The company sold and let property through agents, but had no digital presence for its listings. Buyers found properties through word of mouth and third-party sites that the company did not control. Listing details lived in agents' spreadsheets and phone galleries, and photos and descriptions varied widely in quality. Management could not see which listings drew interest or which led to enquiries. They wanted their own marketplace, built from nothing, with agents who would actually keep it up to date.
- What did Brandsmashers build?
- A marketplace with search, listing pages and agent onboarding. Buyers could filter by location, price and property type, view photos and send an enquiry. Agents got a simple way to create and manage listings, and a review step for quality. Analytics tracked traffic and conversion from the first day.
- How was the work run?
- We spent the first phase working with agents and the sales head to define what a good listing contains. That became a required-field checklist. We then built search and listing pages first, because they carried the most risk, and agent tools next. We shipped in weekly increments with a demo to the company's leadership. Before launch we loaded existing inventory in batches, and agents fixed flagged records with our team on short calls. After launch we reviewed traffic, enquiries and listing quality every week.
- What were the results?
- Launched with 1,200 listings, 85% listing completeness, and traffic and conversion tracked from day one.
YOUR TURN
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