Real Estate Technology / PropTech Case Study

Property performance, turned into a decision system.

Hospitality property analytics built from the supplied 2,200-stay dataset. The case demonstrates how technology can connect asset-level revenue, pricing, channel mix and guest-experience signals into an executive dashboard.

Open full analytics dashboardDownload Excel
Scope integrity: this is a property-operations analytics proxy using the existing Hospitality Hotels data. It does not invent property prices, rents, cap rates or investment returns.

Executive KPI wall

Management filters

Booking value by property

ADR by property

Monthly booking value

NPS vs wait time

Property benchmark table

PropertyBooking ValueADRRepeatCancelNPSServiceCleanliness

Board-level decision questions

• Where is booking value concentrated, and is that concentration supported by healthy guest experience?

• Which channels combine attractive value with repeat demand and manageable cancellation?

• Which service, cleanliness or wait-time signals warrant operational intervention?

• What additional property data would be required before moving from operating analytics to a true investment underwriting model?

PowerPointPDFWordCSVProject ZIP
EXPERIMENT DESIGN LAB

A/B Test Planner & Decision Readout

Estimate a two-sided, two-proportion test sample size before launching a controlled experiment. Planning estimates are not a substitute for a pre-registered analysis plan.

01 / EXPERIMENTATION
Target conversion11.50%
Sample / variant—
Total sample—
Test setup2-sided · 1:1

Assumes independent users, a binary outcome and equal allocation. Adjust for attrition, clustering, multiple comparisons and practical significance before launch.

Experiment design lab

A/B test planner: quantify the decision before rollout

Use this planning calculator to estimate a simple two-arm test. Inputs are illustrative planning assumptions—not observed results or a substitute for a formal power analysis.

Variant A—participants
Variant B—participants
Total—participants
Target rate B—planning target

Planning method: normal approximation for two independent proportions, equal allocation. Validate assumptions with a statistical package before running a consequential experiment; account for clustering, multiple tests, attrition and business guardrails.