Engineering case study

Automating UK property-market analysis and outreach

This internal real-estate tool combined historical listing data from Zoopla and Rightmove with automated analysis and outreach workflows for the UK market.

Real EstateProperty listing automation

This case study describes commercial work at a level suitable for public sharing. Client-identifying and confidential implementation details are intentionally omitted.

The challenge

The team needed to turn a large body of historical property data into practical decisions. The workflow had to support questions such as where rents had been lowest over the previous 12 months, then carry those findings into offer generation and outreach.

Engineering approach

Built data-driven workflows on Django and PostgreSQL, including KPI calculations over a historical table described as approximately 9 GB.
Used a recorded application stack that included Selenium, HTMX, Django Channels, Redis, Caddy, and DigitalOcean.

What the product enabled

Historical rental-market KPI analysis
Area-level comparison across UK listings
Automated offer-price generation
Automated listing outreach

Delivered outcomes

Combined market analysis and follow-up actions in one internal tool.
Made historical listing data actionable for area selection and offer workflows.
Linked analysis, offer pricing, and outreach within the same workflow.

These outcomes summarize the available project record; no client metrics have been inferred.

Technology used

Django
Django Channels
Selenium
Bootstrap
HTMX
Digital Ocean
Caddy
Redis
PostgreSQL
Sentry
Ruff

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