ANALYTICS

The Analytics module is Leaseora's central intelligence layer. It aggregates data from operational modules and turns it into filtered dashboards, calculated metrics, predictive outputs, AI-assisted explanations, alerts and exportable reports.

Leaseora Jul 30, 2026 49 min read 15 views

LEASEORA

ANALYTICS

Detailed User and Technical Operations Guide

Properties • Finance • Predictive Cash Flow • ROI • Payment Patterns • IoT • CRM • Mortgage • Insurance • Syndication • Reports • AI Chat • Realtime Intelligence

For real estate companies, landlords, asset managers, finance teams, operations teams, portfolio analysts, property managers, investors, compliance teams and authorised platform administrators

Version 1.0 | July 2026

Purpose of this guide

This guide explains how a real estate company uses Leaseora's Analytics module from isolated portfolio dashboards and property performance through finance, predictive cash flow, ROI, payment behaviour, IoT, wallet, mortgage, insurance, syndication, CRM, land sales, utilities, fraud, settlements, disputes, webhooks, AI insights and report scheduling. It also provides a detailed technical reference based on the supplied controllers, models, services, event and reporting flows.

1. Purpose, Audience and Scope

Item	Description
Primary users	Real estate companies, corporate and private landlords, asset managers, property managers, finance teams, CRM teams, operations teams, analysts and SuperAdmins.
Core scope	Properties, financial performance, predictive analysis, ROI, payment behaviour, portfolio metrics, cost optimisation, gateways, reconciliation, settlements, disputes and reporting.
Cross-module scope	Leases, wallet, CRM, IoT, mortgage, insurance, syndication, land sales, utilities, marketplace, fraud and other platform modules.
Outputs	Dashboards, JSON APIs, WebSocket updates, AI insights, alerts, charts, PDF, CSV and Excel reports.
Security	DataIsolation and authorisation should ensure that each landlord sees only their own portfolio.
Operational boundary	Analytics and AI outputs support management decisions. They do not guarantee investment returns, collections, occupancy, approvals, savings, tax outcomes or future performance.

2. Analytics Operating Principles

· Start from complete and reconciled source records.

· Apply landlord, property and role isolation before aggregation.

· Preserve original currency, transaction date and source identifiers.

· Define every metric, denominator, date range and reporting basis.

· Separate historical fact, calculated metric, forecast and AI interpretation.

· Compare predictions with actual outcomes.

· Do not make high-impact decisions from a single score or alert.

· Retain report parameters and audit evidence.

Source of truth

Operational records in Properties, Leases, Payments, Finance, CRM, IoT and other modules remain authoritative. Analytics should be regenerated or refreshed after material source corrections.

3. Complete Analytics Lifecycle

Figure 1. Complete Analytics lifecycle

4. Roles and Separation of Duties

Role	Responsibility	Recommended control
Portfolio Viewer	Reads approved dashboards and reports.	No configuration or recategorisation rights.
Analyst	Builds filters, comparisons and exports.	Cannot alter source financial transactions without separate authority.
Finance Reviewer	Validates revenue, expenses, P&L and cash flow.	Reconcile before publishing investor or tax reports.
Property Manager	Uses occupancy, lease, maintenance and market analytics.	Can access only assigned portfolio scope.
CRM Manager	Uses lead, pipeline and campaign analytics.	No access to unrelated financial or Client data.
Payments Operator	Reviews gateways, settlements, disputes and reconciliation.	Operational changes should be separately approved.
AI Insight Reviewer	Reviews and actionises AI output.	Must validate source data and impact.
Report Administrator	Creates templates and schedules.	Recipient and export access must be controlled.

5. Data Isolation and Real-Time Controls

Figure 2. Data isolation, real-time and export controls

Apply isolation everywhere

DataIsolation must cover dashboard queries, JSON endpoints, AI prompts, WebSocket payloads, exports, scheduled reports, webhook logs and drill-down records.

6. Phase 1 - Access the Analytics Dashboard

1	Open Analytics -> Dashboard Primary user: Landlord / authorised analyst

AnalyticsController@index is the primary entry and redirects to /analytics/properties. CurrencyService and the configured OpenAI API key support amount display and AI functions. The DataIsolation trait restricts landlord data.

Entry point	Purpose
DashboardController@index	Unified dashboard.
DashboardController@corporateIndex	Corporate landlord dashboard.
DashboardController@privateIndex	Private landlord dashboard.
DashboardController@getDashboardData	JSON dashboard refresh.
DashboardController@getApplicationData	Listings, applications and lead data.

Real-time event

FinancialAnalyticsUpdated implements ShouldBroadcast and sends financial dashboard updates through WebSocket. Confirm that broadcast channels are private and landlord-scoped.

7. Analytic Model

Field	Purpose
landlord_id	Owning landlord or company.
metric	Metric identifier.
data	JSON payload containing metric data and context.
recorded_at	Time the metric was recorded.

· Use a stable metric name.

· Include units, currency and period in data or metadata.

· Avoid storing cross-landlord aggregates in a landlord-owned record.

· Define retention and refresh frequency.

· Do not treat stale Analytic records as live source data.

8. Phase 2 - Properties Analytics Overview

2	Review Portfolio Property Performance Primary user: Landlord / asset manager

AnalyticsController@properties and PropertyAnalyticsController@index combine Property, Lease, Transaction, MaintenanceRequest and PropertyMarketData records. CurrencyExchangeService and OpenAIService support comparison, conversion and advisory insights.

Dashboard metric	Meaning and operational use
Total portfolio value	Aggregate property value under the configured valuation basis and reporting currency.
Occupancy rate	Occupied units divided by eligible units for the selected period.
Revenue per property	Recognised or collected revenue under the selected financial basis.
Vacancy rate	Vacant eligible units divided by total eligible units.
Average rent	Average rent across selected leases, units or properties.
Maintenance frequency	Number of maintenance requests per property and period.
Maintenance cost	Recorded maintenance expense or approved cost per property.
Market comparison	Portfolio pricing compared with PropertyMarketData records.

Metric definitions matter

Occupancy, revenue and maintenance cost can differ depending on whether the denominator uses units, leases, days, invoices, cash receipts or accounting records. Confirm the production formula before publication.

9. Property Performance Analysis

PropertyAnalyticsController@performance displays per-property performance. @getPerformanceData returns raw occupancy, revenue and NOI information. @getAIPerformanceInsights asks OpenAIService to identify top performers, underperformers and improvement opportunities.

· Select a date range appropriate to the property type.

· Confirm property and unit status records are current.

· Separate gross revenue from net operating income.

· Include only approved operating expenses in NOI.

· Compare like-for-like properties where possible.

· Review one-off repairs or vacancies before classifying underperformance.

· Validate AI recommendations against leases, budgets and local conditions.

Performance output	Recommended interpretation
Top-performing properties	Review whether performance is sustainable or driven by one-off income.
Underperforming properties	Investigate vacancy, rent, arrears, expenses, maintenance and market position.
Revenue opportunity	Test rent, occupancy, ancillary income and collection assumptions.
NOI comparison	Use consistent accounting basis and expense classification.

10. Export Property Performance Analysis

PropertyAnalyticsController@exportPerformanceAnalysis exports the selected performance data as CSV, Excel or PDF under the configured route or export implementation.

· Include the report period, reporting currency and generation time.

· Include selected property filters.

· State the NOI, occupancy and valuation definitions.

· Do not include another landlord's properties.

· Protect exports containing Client, lease or financial details.

11. Property Market Analysis

3	Compare Portfolio Pricing with Market Data Primary user: Asset manager / pricing analyst

PropertyAnalyticsController@market and @getMarketData retrieve PropertyMarketData records. @getAIMarketInsights produces market-positioning, demand and pricing observations.

PropertyMarketData field	Purpose
country, city, region	Geographic matching.
property_type	Comparable property category.
price	Market price or rent value supplied by the source.
currency	Currency of the observation.
price_per_sqm	Normalised area-based comparison.
source	Origin of the market observation.

Market data requires freshness and comparability

A market record is not automatically comparable merely because it shares a city. Review date, source, neighbourhood, condition, amenities, size, tenure and property type.

12. AI Market Insights

· Confirm the market records used by the request.

· Confirm currency and unit-of-area consistency.

· Separate asking price from achieved transaction price.

· Treat demand trends as directional unless the sample supports stronger conclusions.

· Do not automatically change rents from AI output.

· Review lease law, notice requirements and affordability implications before pricing action.

13. Portfolio Overview and Diversification

PropertyAnalyticsController@getAIPortfolioInsights analyses portfolio concentration, diversification and potential adjustments. @exportOverview produces a portfolio overview report.

Portfolio lens	Questions to review
Geography	Is income concentrated in one city, district or country?
Property type	Is the portfolio concentrated in residential, commercial or another type?
Client concentration	Does one Client or employer represent a material share of income?
Lease expiry	Are many leases expiring in the same period?
Currency	Is income or debt exposed to a limited set of currencies?
Maintenance risk	Are major ageing assets concentrated in one group?

Diversification is context-dependent

A concentrated strategy can be intentional. AI output should identify exposure, not dictate a transaction or investment decision.

14. Phase 3 - Financial Analytics Dashboard

4	Review Portfolio Financial Performance Primary user: Finance team / landlord

AnalyticsController@finance opens the financial analytics view. @financeData returns revenue, expenses and net income by currency. @financeMatrix and @financePropertyMatrix compare performance across the portfolio and at property level.

Endpoint	Purpose
finance	Main financial analytics view.
financeData	JSON revenue, expenses, net income and currency data.
financeMatrix	Cross-property financial comparison.
financePropertyMatrix	Detailed property financial matrix.
getFinancialInsights	AI revenue, anomaly, forecast and tax-efficiency observations.

Reconcile before relying on financial analytics

Unposted journals, incomplete expenses, duplicate payments, unreconciled bank items or incorrect currencies can materially distort revenue, expenses and net income.

15. Financial Matrix Review

· Choose cash or accrual basis where the dashboard supports the distinction.

· Confirm report period and timezone.

· Confirm the preferred reporting currency.

· Preserve original currency and exchange-rate date.

· Separate recurring operating income from deposits, financing and capital receipts.

· Separate operating expenses from capital expenditure.

· Investigate material property-to-property differences.

16. AI Financial Insights

Insight type	Meaning	Required review
Revenue trend	Direction and change in revenue.	Check seasonality, lease changes and one-off transactions.
Expense anomaly	Unusual expense level or category.	Check invoice, classification, period and duplicate entry.
Profitability forecast	Estimated future net result.	Review occupancy, rent, expense and FX assumptions.
Tax efficiency score	Advisory indicator.	Use professional tax review and jurisdiction rules.

Tax output is not tax advice

The Analytics module can highlight patterns, but tax liability, deductibility and filing treatment require the underlying Finance and Tax records and professional review.

17. Property Financial Reports

PropertyFinancialReportController provides statement-style reports used by the Analytics module.

Report	Purpose
cashFlow	Property inflows and outflows.
expenseCategories	Expense analysis by category.
taxReport	Tax liability or tax-related reporting by property and period.
profitLoss	Revenue, expenses and profit or loss.
forecast	Forward-looking financial report.
budgetComparison	Budget versus actual variance.

18. Cash Flow Report Review

· Opening and closing cash reconcile to source accounts.

· Rent and other receipts are separated.

· Payouts, refunds and transfers are not double-counted.

· Financing cash flow is separated from operating cash flow where supported.

· Pending gateway settlements are not treated as available cash without disclosure.

19. Profit and Loss Review

· Revenue recognition is consistent.

· Expenses are posted to the correct property and category.

· Depreciation, financing and tax treatment are clearly stated.

· Capital expenditure is not incorrectly treated as routine expense.

· The period is closed or clearly marked provisional.

20. Budget Versus Actual

· Use the approved budget baseline.

· Do not edit the baseline merely to remove adverse variance.

· Explain material rent, vacancy, maintenance, utility and insurance variances.

· Assign an owner and action for material variance.

· Separate timing variance from permanent variance.

21. Phase 4 - Advanced Analytics Suite

Figure 3. Advanced Analytics suite

AdvancedAnalyticsController injects PredictiveCashFlowService, ROICalculationService, PaymentPatternAnalysisService, AuditTrailService, SettlementService, DisputeService, ExchangeRateService and ReconciliationService.

22. Phase 4 - Predictive Cash Flow Analysis

5	Generate a Cash Flow Forecast Primary user: Finance team / asset manager

AdvancedAnalyticsController@cashFlowAnalysis combines historical and predicted cash flow. @generateCashFlowForecast calls PredictiveCashFlowService@generateForecast. @predictiveCashFlow and @generateCashFlowPrediction provide the predictive dashboard and generation endpoint.

1. Select the forecast period in days.

2. Choose whether to include seasonality.

3. Select all or specific properties.

4. Review the historical cash flow baseline.

5. Generate the forecast and confidence information.

6. Review assumptions and expected receipts or expenses.

7. Compare with operational payment schedules and budgets.

8. Export only after validation.

23. PredictiveCashFlowService Reference

Method	Purpose
generateForecast	AI forecast for the selected period and seasonality.
generatePrediction	Detailed prediction and confidence intervals.
getHistoricalCashFlow	Historical baseline.
getPropertyPrediction	Forecast for one property.
compareActualVsPredicted	Variance between realised and forecast cash flow.
getCashFlowInsights	Pattern explanations.
analyzeTrends	Portfolio cash-flow trend analysis.
getRecommendations	Advisory cash-flow optimisation recommendations.
exportForecast	CSV, Excel or PDF export.

24. Cash Flow Forecast Assumptions

· Opening cash balance is correct.

· Lease payment schedules are current.

· Expected arrears and collection delays are considered.

· Known capital and maintenance outflows are included.

· Gateway settlement timing is considered.

· Currency assumptions are documented.

· Seasonality is supported by sufficient history.

· Confidence intervals are not presented as guaranteed ranges.

Forecast is not cash on hand

A prediction of rent collection or future inflow does not mean funds are available, cleared or unrestricted.

25. Actual Versus Predicted Review

1. Select the comparison period.

2. Compare actual receipt and expense records with the prior forecast.

3. Calculate absolute and percentage variance.

4. Separate timing differences from model error.

5. Record major drivers such as vacancy, arrears, repairs or FX.

6. Update assumptions and monitor forecast drift.

26. Phase 4 - ROI Analysis

6	Calculate Property and Portfolio Returns Primary user: Asset manager / investment analyst

AdvancedAnalyticsController@roiAnalysis and @roiCalculation display ROI tools. @calculatePropertyROI, @calculateIRR, @compareROI, @calculateRoi, @roiDetails and export endpoints use ROICalculationService.

Metric	General meaning	Inputs requiring confirmation
Cap rate	NOI divided by property value.	NOI basis and valuation date.
Cash-on-cash return	Annual pre-tax cash flow divided by invested cash.	Debt, deposits, acquisition and capital costs.
Total return	Income plus value change under the configured formula.	Valuation method and transaction costs.
IRR	Discount rate that sets net present value to zero.	Cash-flow dates, terminal value and sign convention.

27. ROICalculationService Reference

Method	Purpose
calculatePropertyROI	Full property ROI including cap rate, cash-on-cash and total return.
calculateIRR	Internal Rate of Return.
compareProperties	Ranked comparison.
getPortfolioROI / calculatePortfolioROI	Portfolio return summary.
getInvestmentRecommendations	AI investment observations.
getPropertyROIs	Individual property returns.
getROITrends	ROI over a selected number of months.
getIndustryBenchmarks	Comparison with benchmark data.
exportROIReport / exportAnalytics	Export analytics.

28. ROI Calculation Procedure

1. Select the property and analysis period.

2. Confirm acquisition or valuation amount.

3. Confirm rental and other income.

4. Confirm operating expenses and NOI.

5. Confirm financing costs and invested cash.

6. Enter or review capital improvements and sale assumptions.

7. Calculate returns.

8. Review calculation detail and sensitivity.

9. Compare only properties with consistent inputs.

ROI is sensitive to assumptions

A small change in property value, terminal value, vacancy, debt, capital expenditure or cash-flow timing can materially change the result.

29. ROI Benchmarks and Recommendations

· Identify the benchmark source and period.

· Match geography, property type, leverage and risk.

· Do not represent a benchmark as a guaranteed market return.

· Review whether the recommendation is based on current or historical data.

· Use qualified investment and financial review before transactions.

30. Phase 4 - Payment Pattern Analysis

7	Analyse Collection and Payment Behaviour Primary user: Collections manager / finance analyst

AdvancedAnalyticsController@paymentPatterns and @analyzePaymentPattern use PaymentPatternAnalysisService for portfolio, property and Client payment behaviour.

Method	Purpose
analyzePaymentPatterns	Comprehensive pattern analysis.
analyzeTenantBehavior	Client-level payment behaviour across the portfolio.
getPaymentMethodAnalysis	Gateway, wallet and bank-transfer usage.
detectPaymentAnomalies	AI anomaly detection.
predictPaymentBehavior	Predicted late-payment risk.
comparePropertyPatterns	Property-level pattern comparison.
getRecommendations	Advisory collection recommendations.

31. Payment Behaviour Metrics

Metric	Recommended definition
On-time rate	Payments completed by due date divided by eligible due payments.
Average days late	Average delay for late payments only or all payments - label the basis.
Partial-payment rate	Partially paid obligations divided by eligible obligations.
Method mix	Payment count or value by gateway, wallet or transfer.
Failed attempt rate	Failed initiation or verification attempts divided by attempts.
Payment streak	Consecutive on-time payments under a documented rule.

32. Payment Anomaly Detection

· Investigate unusual amounts, timing, frequency or method changes.

· Confirm duplicate callbacks or reversals before treating activity as Client behaviour.

· Review currency conversion and fee effects.

· Use a human review before fraud, blacklist or adverse action.

· Do not use protected personal characteristics in risk scoring.

· Record investigation outcome to measure false positives.

Prediction is not a default decision

A predicted late-payment risk should support early communication and review. It should not automatically deny housing, financing or service without lawful and fair process.

33. Export Payment Pattern Analysis

· Limit Client identifiers to authorised recipients.

· Include the period and status definitions.

· Separate prediction from observed payment history.

· Protect exported behavioural data.

34. Phase 4 - Portfolio Metrics

8	Review Portfolio KPI Cards Primary user: Asset manager / executive

Portfolio metric	Purpose and control
Portfolio value	Use a stated valuation basis and date.
Valuation growth	Compare like-for-like assets and periods.
Gross yield	Gross annual income divided by value under the configured formula.
Net yield	Net operating income divided by value.
Vacancy rate	Vacant eligible units over total eligible units.
Days to fill vacancy	Time from available date to lease activation or agreed milestone.
Client retention	Renewed or retained Clients divided by eligible expiries.
Average lease duration	Average contracted or actual duration - state the basis.
Maintenance cost ratio	Maintenance cost divided by revenue.
Debt-to-equity	Debt divided by equity where mortgage data exists.
NOI and cap rate	Operating profitability and yield.

KPI cards require drill-down

An executive metric should link to properties, periods and source records so the team can explain the number.

35. Phase 4 - Cost Optimisation

9	Identify Cost Drivers and Opportunities Primary user: Finance / operations manager

AdvancedAnalyticsController@costOptimization provides expense benchmarking, high-cost property analysis, maintenance trends, insurance and utility recommendations. @generateOptimizationReport creates an action report. @expenseCategorization and @recategorizeExpense support classification review.

· Confirm expenses are classified correctly before benchmarking.

· Compare similar properties and regions.

· Separate one-off capital work from recurring costs.

· Estimate implementation cost and risk for each recommendation.

· Assign action owner, target date and expected saving.

· Measure realised savings after implementation.

Do not recategorise to improve appearance

Expense recategorisation should reflect accounting substance and preserve audit history, not merely change reported performance.

36. Optimisation Report Structure

Report section	Content
Baseline	Current cost by property, category and period.
Benchmark	Comparable portfolio or market reference.
Driver	Reason for the variance.
Recommendation	Proposed operational action.
Expected impact	Estimated saving, time and confidence.
Risk and dependency	Service, safety, contract or compliance implications.
Owner and review	Responsible person and outcome date.

37. Phase 4 - Gateway Performance Analytics

10	Review Payment Gateway Reliability Primary user: Payments operator / finance team

AdvancedAnalyticsController@gatewayPerformance analyses configured payment gateways. It includes gateway failover history and operational controls.

Metric / action	Purpose
Success rate	Successful verified transactions divided by eligible attempts.
Processing time	Average or percentile transaction processing time.
Fee cost	Gateway charges by value and transaction.
Error rate	Failures and reasons.
Geographic usage	Gateway use by country or region.
gatewayFailover	Failover configuration and history.
configureFailover	Set thresholds and rules.
failoverStatus	Current gateway failover condition.
toggleGateway	Enable or disable a gateway.
testGateway	Connectivity test.
viewEventDetails	Inspect a gateway event.

Operational change control

Disabling a gateway or changing failover rules can affect live payments. Require authority, impact review, audit logging and rollback.

38. Gateway Metric Review

· Use verified payment outcomes rather than redirects alone.

· Separate Client declines, technical failures and timeout uncertainty.

· Review result by country, currency and payment method.

· Consider settlement delay in addition to transaction success.

· Do not compare fee percentages without flat fees and FX costs.

· Use a defined time window and minimum sample size.

39. Phase 4 - Transaction Reconciliation

11	Reconcile Platform and Bank Transactions Primary user: Finance reconciliation user

AdvancedAnalyticsController@transactionReconciliation and ReconciliationService identify unreconciled items, matched totals and reconciliation rate. @reconcileTransactions runs the process, and @reconciliationDetails opens a specific record.

1. Select bank account, gateway, currency and statement period.

2. Load platform transactions and bank or settlement records.

3. Run deterministic and configured matching rules.

4. Review unmatched, duplicate or amount-different records.

5. Approve valid matches.

6. Create controlled adjustments where authorised.

7. Complete the reconciliation and retain evidence.

Analytics does not replace ledger control

Reconciliation analytics supports investigation. Accounting records should reflect approved settlement, fees, refunds, chargebacks and adjustments.

40. Phase 4 - Settlement Tracking

12	Monitor Gateway Settlement Status Primary user: Payments / treasury team

SettlementService method	Purpose
getSettlementStats	Total, pending and completed settlements.
getUpcomingSettlements	Expected upcoming due dates.
getGatewayBreakdown	Settlement amounts by gateway.
getSettlementHistory	Paginated settlement history.
getSettlementAnalytics	Settlement patterns and timelines.
getSettlementAlerts	Delayed or failed settlement alerts.

· Confirm settlement currency and gross/net basis.

· Identify gateway fees and withholding.

· Review pending settlements past expected date.

· Do not count expected settlement as cleared cash.

· Investigate failed or partially settled batches.

· Export with selected filters and reconciliation status.

41. Phase 4 - Dispute Management

13	Create and Resolve Payment Disputes Primary user: Payments / support team

AdvancedAnalyticsController@disputeManagement displays open, resolved and escalated disputes. DisputeService provides statistics, active records, details, creation and resolution.

Method	Purpose
getDisputeStats	Total disputes, win rate and resolution time.
getActiveDisputes	Filtered active-dispute list.
getDisputeDetails	Full landlord-scoped dispute detail.
createDispute	Create a dispute record.
resolveDispute	Record the resolution.

· Link the dispute to the correct transaction and property context.

· Record reason, amount, currency and evidence.

· Track response deadline and gateway or bank case reference.

· Record provisional and final financial impact separately.

· Require authorised resolution and audit notes.

· Measure win rate only on closed eligible disputes.

42. Phase 4 - Webhook Management

14	Monitor Analytics and Payment Webhooks Primary user: Technical administrator

Operation	Purpose
webhookManagement	List endpoints and logs.
createWebhook	Create endpoint configuration.
updateWebhook	Change endpoint settings.
deleteWebhook	Remove under controlled process.
testWebhook	Send a test delivery.
viewWebhookLogs	Inspect attempts and responses.
editWebhookEndpoint	Update endpoint URL.

Webhook security

Use HTTPS, authentication or signatures, replay protection, timeouts, retry limits and secret rotation. Do not expose credentials in logs or exports.

43. Webhook Delivery Review

· Endpoint belongs to the authorised landlord or platform integration.

· Test payload contains no live sensitive data unless approved.

· Logs record status, response code, attempt and timestamp.

· Retries are idempotent.

· Repeated failure creates an operational alert.

· Disabled or deleted endpoints stop future delivery.

44. Phase 5 - Predictive Analytics Hub

15	Open Predictive Analytics Primary user: Landlord / analyst

AnalyticsController@predictiveAnalytics displays the predictive hub. @fetchPredictiveData returns predicted rent collection, vacancy, Client churn, maintenance cost, market rent movement and portfolio value trajectory.

Prediction	Decision support use
Rent collection	Treasury and collection planning.
Vacancy	Leasing and marketing preparation.
Client churn	Renewal outreach and service review.
Maintenance cost	Budget and preventive maintenance planning.
Market rent movement	Pricing and market-positioning review.
Portfolio value trajectory	Scenario planning, not a guaranteed valuation.

45. Predictive Data Quality Checklist

· Sufficient historical records exist.

· Missing periods and outliers are identified.

· Property status changes are reflected.

· New properties with limited history are flagged.

· Seasonality and structural changes are separated.

· Predictions include period and confidence information.

· Actual outcomes are captured for back-testing.

46. AI Portfolio Insights

AnalyticsController@getAiInsights generates portfolio-wide observations covering revenue opportunities, risk, market position and investment opportunities.

Insight category	Examples
Revenue	Collection improvement, vacancy reduction or pricing review.
Risk	High-risk payments, expiring leases or maintenance backlog.
Market	Portfolio rent position and changing local demand.
Investment	Potential acquisition, disposal or capital-allocation questions.

Action requires evidence

An AI suggestion should link to supporting properties, metrics and dates. The reviewer should be able to reproduce the underlying calculation.

47. AI Analytics Chat

16	Ask a Natural-Language Analytics Question Primary user: Landlord / analyst

AnalyticsController@aiChat answers questions such as which property performs best or which Clients show late-payment risk. The output is powered by the configured OpenAI API and selected analytics context.

1. Choose the relevant period, currency and property scope if the interface provides them.

2. Ask a specific question.

3. Review the stated answer and supporting data.

4. Open the relevant dashboard or source records.

5. Correct ambiguity and re-run where necessary.

6. Do not treat the answer as a final legal, credit, tax or investment decision.

Prompt isolation

Do not place another landlord's data, secrets, API keys or unnecessary Client personal data in the AI prompt.

48. AI Alerts

AnalyticsController@getAiAlerts and @aiAlerts provide generated alerts for lease risk, expense anomalies, market changes and Client behaviour changes.

Alert type	Recommended response
Payment risk	Review payment record, contact history and due date before outreach.
Lease expiry	Confirm contractual expiry and notice timetable.
Expense spike	Inspect invoice, category and period.
Market change	Review source freshness and comparable properties.
Behaviour change	Check operational causes and avoid unsupported adverse action.

49. Property AI Analysis

AnalyticsController@getPropertyAiAnalysis and @propertyAiAnalysis produce a property health score, risk factors, market comparison, pricing observations and maintenance priorities.

· Confirm the property belongs to the landlord.

· Review the source period and data completeness.

· Separate financial, operational and market components.

· Do not hide critical maintenance behind an aggregate health score.

· Assign action owners for accepted recommendations.

· Review score movement after source data changes.

50. Phase 6 - AI Dashboard and AiInsight Records

17	Review Centralised AI Insights Primary user: Landlord / AI reviewer

AIDashboardController@index aggregates generated insights. AiInsight records support structured display and traceability.

AiInsight field	Purpose
landlord_id	Owning landlord.
query	Question or generation prompt context.
source	Analytics source or module.
region	Market or geographic context.
category	Insight category.
insight / content	Generated text.
metadata	Supporting data in JSON.
published_at	Publication time.
created_by	User that triggered generation.
title, priority	Structured display and prioritisation.
actionable_tip	Suggested next step.
icon, color	UI display properties.

51. AI Insight Management

Controller	Operation
AIInsightController@index	List landlord-owned insights.
AIInsightController@show	View a single landlord insight.
AIGlobalInsightController@index	List global or market-level insights.
AIGlobalInsightController@show	View one global insight.

Global insight must not expose private data

Platform or market insights should be aggregated, anonymised and subject to minimum group-size or disclosure controls.

52. AI Insight Review Workflow

1. Review title, source, period, region and priority.

2. Inspect metadata and supporting metrics.

3. Confirm that the insight belongs to the landlord or is approved global content.

4. Classify the insight as informational, actionable or high-impact.

5. Assign a human reviewer for high-impact actions.

6. Record outcome and actual result where implemented.

7. Archive or regenerate stale insights.

53. Predictive and AI Analytics Flow

Figure 4. Predictive and AI analytics flow

54. Phase 6 - IoT AI Insights

18	Generate Insight from Smart-Property Data Primary user: Property operations / energy manager

IoTAIInsightsController and IoTAIInsightsService analyse IoT data for energy, anomalies, predictive maintenance and cost opportunities.

Operation	Purpose
helpAssistant	AI help for IoT questions.
getInsights	Generate insights from analytics data.
getEnergyRecommendations	Energy reduction recommendations.
getPredictiveMaintenanceInsights	Potential equipment-failure indicators.
streamAnalysis	Real-time streaming data analysis.

IoT alert is not a safety diagnosis

Use qualified technicians and established safety procedures. A sensor anomaly can reflect device error, communication loss, environmental change or actual equipment risk.

55. Phase 7 - Lease Analytics

19	Review Lease and Collection Performance Primary user: Property manager / lease manager

LeaseAnalyticsController@index uses Lease, LeasePayment and Payment records with CurrencyService.

Lease analytic	Purpose
Status distribution	Active, expiring, expired and terminated leases.
Payment overview	Paid, pending and overdue by currency.
Average duration	Lease term or actual occupancy duration under the configured basis.
Renewal rate	Renewed leases divided by eligible expiries.
Lease health	Composite score based on configured factors.
Client retention	Retention and churn patterns.
Revenue	Revenue per lease, property and unit type.

Preferred-currency display

Currency conversion improves readability, but source currency, exchange-rate date and conversion method should remain available for audit.

56. Lease Analytics Review Procedure

1. Select the lease period and property scope.

2. Review status distribution and expiring leases.

3. Review overdue amount and count separately.

4. Review renewal eligibility and outcomes.

5. Inspect low lease-health scores at source-record level.

6. Compare revenue by property and unit type.

7. Export with currency and status definitions.

57. Phase 8 - IoT Device Analytics

20	Review Device, Energy and Performance Analytics Primary user: Smart-property operator

IoTAnalyticsController uses IoTDevice, IoTDeviceData and IoTAnalytics with IoTAIInsightsService and currency services.

Analytics section	Purpose
index	IoT analytics overview.
energy	Energy consumption, cost, carbon and efficiency.
performance	Uptime, errors, response time and maintenance events.
usage	Peak hours and usage frequency.
comparative	Period-over-period and benchmark comparison.
analyticsData	Raw data API.
chartData	Chart-formatted data.
refreshAIInsights	Regenerate AI insight.
exportReport	Export IoT analytics.

58. IoTAnalytics Model Field Groups

Group	Representative fields
Classification	analytics_type, category, subcategory.
Data payload	metrics, insights.
Energy and cost	total_energy_consumed, total_cost, cost_per_kwh, energy_efficiency_score.
Sustainability	cost_savings, carbon_footprint.
Performance	uptime_percentage, error_count, response_time_avg.
Events	total_events, maintenance_events.
Usage	peak_usage_hours, usage_frequency.
Comparison	vs_previous_period_pct, vs_benchmark_pct, benchmark_type.
Anomalies	anomalies_detected, anomaly_details, alerts_generated, alert_categories.
Prediction	predictions, recommendations, confidence_level, data_points_analyzed.

59. IoT Analytics Data Quality

· Device time and timezone are synchronised.

· Missing data and offline periods are identified.

· Meter units and calibration are correct.

· Energy tariff and currency are current.

· Benchmark is appropriate for device and property type.

· Anomaly confidence and false positives are tracked.

· Carbon factors are sourced and dated.

60. Phase 9 - Wallet Analytics

21	Review Wallet Activity and Balance Trends Primary user: Finance / wallet operations

WalletAnalyticsController operation	Purpose
index	Wallet analytics overview.
trendChart	Volume, amount and frequency trends.
interactionGraph	Payment relationships between platform users.
balanceTrend	Daily, weekly or monthly balance snapshots.
gatewayPerformance	Gateway metrics for wallet transactions.
export	Wallet analytics export.

Interaction graphs contain sensitive relationship data

Restrict access, minimise identifiers and do not expose unrelated user-to-user transaction relationships.

61. Wallet Analytics Controls

· Use posted wallet transactions rather than transient UI state.

· Separate available, pending, held and restricted balances.

· Exclude internal transfers from revenue where appropriate.

· Treat reversals and chargebacks consistently.

· Apply landlord scope and user privacy.

· Reconcile gateway and wallet totals.

62. Phase 10 - Mortgage Analytics

22	Review Mortgage Portfolio Performance Primary user: Mortgage portfolio manager

MortgageDashboardController@index provides portfolio overview. MortgageAnalyticsController@index and MortgageAnalyticsService provide detailed performance and AI risk analysis.

Metric / AI function	Purpose
Loan book value	Total originated or active principal under the configured basis.
Outstanding balance	Remaining principal or payable amount.
Collected payments	Confirmed mortgage collections.
Approval / rejection rate	Application decision analytics by product and profile.
Default / late rate	Payment performance.
Processing time	Application-to-decision duration.
Mortgage fee revenue	Recorded platform or product fees.
predictLoanApprovalProbability	Advisory prediction.
performEnhancedRiskAssessment	Enhanced application risk scoring.
generateMarketAnalysis	Mortgage market context.

High-impact decision boundary

Mortgage approval and risk decisions should not rely solely on AI output. Apply consent, credit, fairness, explainability, policy and human underwriting controls.

63. Phase 11 - Insurance Analytics

23	Review Insurance Cost, Claims and Risk Primary user: Insurance / risk manager

Insurance analytics	Purpose
costAnalysis	Annual premium, trend and premium-to-coverage analysis.
claimsAnalytics	Frequency, amount, approval, denial and settlement timeline.
riskAssessment	AI property risk score and factors.
policyOptimization	Coverage gaps, over-insurance and consolidation opportunities.
reports / export	Custom reports and export.

Insurance analytics is advisory

Coverage and claims depend on policy wording, insurer decisions, evidence and jurisdiction. Analytics does not prove coverage or settlement entitlement.

64. Phase 12 - Syndication Analytics

24	Measure Listing Channel Performance Primary user: Marketing / listing manager

SyndicationAnalyticsController uses Property, SyndicationChannel and SyndicationLog.

Operation	Purpose
index	Overview across all channels.
property	One property across channels.
channel	One channel across properties.
roi	Revenue, acquisition cost and channel ROI.
realTimeData	Live channel metrics.
export	Syndication analytics export.

65. Syndication Metrics

Metric	Definition to confirm
Views	Channel-reported or deduplicated listing views.
Inquiries	Qualified or all contact actions.
Applications	Applications attributed to the channel.
Conversion rate	Applications divided by views or inquiries - label the denominator.
Cost per lead	Channel cost divided by eligible leads.
ROI	Attributed revenue or value divided by cost under the configured formula.

Attribution can be incomplete

A Client may interact with multiple channels before applying. Channel ROI should state the attribution method.

66. Phase 13 - CRM Analytics

25	Review Lead, Pipeline and Agent Performance Primary user: CRM manager / sales manager

CrmAnalyticsController@index and @getData provide lead volume, source, pipeline conversion, stage drop-off, agent performance, time-in-stage and campaign attribution.

CRM metric	Purpose
Lead volume	Number of leads by selected period.
Source distribution	Lead origin.
Pipeline conversion	Movement from New Lead to Closed.
Stage drop-off	Where leads exit or stall.
Agent performance	Assigned activity and outcomes.
Time in stage	Pipeline velocity.
Campaign attribution	Marketing source linked to lead and outcome.

67. CRM Reporting

CrmReportingController@index, @getData, @show and @export support report types including leads, pipeline, campaigns, tasks, communications and revenue.

Report type	Purpose
leads	Lead volume and quality.
pipeline	Velocity and conversion.
campaigns	Campaign performance.
tasks	Completion and overdue tasks.
communications	Channel performance.
revenue	Revenue attributed to CRM activity.

Agent metrics require fair interpretation

Assignment mix, territory, product, lead quality and workload can materially affect outcomes. Do not rank employees from raw conversion alone.

68. CRM Analytics Review

· Duplicate leads are controlled.

· Lead source is captured consistently.

· Closed-lost reasons are structured.

· Time-in-stage excludes paused periods if required.

· Attribution method is stated.

· Revenue is verified and not merely pipeline value.

· Personal performance access follows employment policy.

69. Phase 14 - Land Sales Reporting

26	Review Land Sales and Instalment Collection Primary user: Land sales manager / finance team

LandSalesReportController operation	Purpose
dashboard	Parcels sold, in progress, available, revenue and outstanding.
revenueTracking	Revenue by parcel, period, location, size and zoning.
paymentCollection	On-time rate, days late and collection rate.
overduePayments	Risk-sorted overdue instalments and buyer profiles.
exportSales	CSV or Excel export.

Risk-sorted overdue lists require care

Use payment facts and lawful collection policy. Do not use unsupported AI or protected characteristics to determine enforcement.

70. Phase 15 - Report Generation

27	Generate an On-Demand Report Primary user: Analyst / report administrator

ReportController@index provides the report library. @generateReport creates a Report record and sends generation to the background queue.

Figure 5. Report generation and scheduling lifecycle

71. Report Model Fields

Field group	Fields and purpose
Ownership	user_id, landlord_id.
Identity	name, type, format.
Output	file_path, file_size, generated_at, expires_at.
Selection	parameters, filters, properties, date_from, date_to.
Lifecycle	status, progress, error_message.
Sharing	is_shared.
Schedule link	scheduled_report_id.

72. Report Status Lifecycle

Status	Meaning
pending	Request created and waiting for processing.
processing	Background generation in progress.
completed	Output file generated.
failed	Generation failed with error_message.

· Progress is updated without exposing internal errors to unauthorised users.

· Failed jobs can be retried safely.

· Completed files match the selected filters.

· Expired files are removed or blocked under retention policy.

· Shared reports are explicitly authorised.

73. Report Types

ReportController operation	Purpose
scheduled	Scheduled report library and history.
leaseTermination	Upcoming terminations, notice periods and deposit refunds.
performance	Property performance.
financial	P&L, cash flow, expense and revenue.
custom	Custom report builder.
multiPropertyReport	Consolidated properties.
investorReport	Portfolio, return, occupancy and market-value presentation.

Investor-grade does not mean audited

Label whether data is provisional, management-prepared, reconciled, independently valued or audited.

74. Generate a Custom Report

1. Choose the report type.

2. Choose PDF, CSV or Excel.

3. Select the date range.

4. Select one or more properties.

5. Apply status, currency or module filters.

6. Choose whether charts should be included where supported.

7. Review the estimated scope.

8. Generate the report.

9. Monitor status and progress.

10. Open and validate the completed file before sharing.

75. Scheduled Reports

28	Configure Recurring Report Delivery Primary user: Report administrator

ScheduledReport field	Purpose
user_id, landlord_id	Owner and scope.
template_id	Reusable template.
name, description, type, format	Report identity.
frequency, cron_expression	Schedule.
parameters, filters, properties	Selection criteria.
recipients	Approved recipient list.
next_run_at, last_run_at	Scheduling state.
run_count, success_count, failure_count	Run history.
last_status, last_error	Latest outcome.
is_active	Enable or disable.
archive_after_days	Retention rule.

Recipient review

A scheduled report may continue after staff, investor or vendor access changes. Review recipients regularly and remove access immediately when no longer authorised.

76. Report Templates

ReportTemplate field	Purpose
landlord_id	Owner of private template.
name, description, type	Template identity.
configuration	JSON layout or settings.
filters	Saved selection filters.
columns	Selected output columns.
output_format	Default format.
is_public	Platform or shared visibility.
usage_count, last_used_at	Usage tracking.

Public templates should contain configuration, not private data

Do not publish landlord-specific filters, property IDs, recipients or embedded results.

77. Phase 16 - Fraud Report

29	Download the Fraud Analytics PDF Primary user: Authorised fraud / risk user

FraudReportController@downloadPDF produces a PDF covering flagged transactions, fraud alerts, wallet freezes and suspicious activity by property.

· The user is authorised for fraud data.

· Flags are distinguished from confirmed fraud.

· Case outcome and false positives are included where available.

· Client identities are minimised for recipients.

· The PDF is protected and retained securely.

· No automatic adverse decision is made solely from the report.

78. Phase 17 - Marketplace Analytics

30	Review Marketplace Performance Primary user: Landlord marketing / vendor manager

MarketplaceDashboardController@index combines listing views, inquiries, applications, vendor marketplace activity, visibility-campaign impressions and clicks, and comparisons with marketplace averages.

Marketplace area	Metric examples
Listings	Views, inquiries and applications.
Vendors	Hire requests and acceptances.
Visibility campaigns	Impressions, clicks and conversions.
Benchmark	Comparison with approved marketplace averages.

79. Phase 18 - Utility Analytics

31	Review Utility Revenue, Consumption and Efficiency Primary user: Property / utility manager

UtilityAnalyticsController operation	Purpose
revenueAnalytics	Utility-billing revenue.
consumptionPatterns	Usage trends by utility type.
costEfficiency	Property cost-efficiency metrics.
predictiveAnalytics	Future consumption and cost prediction.
propertyAnalytics	Per-property utility analysis.
exportData	Utility analytics export.

Meter and allocation quality

Utility analytics depends on verified readings, billing periods, tariffs and allocation rules. An AI forecast cannot correct incorrect meter data.

80. Phase 19 - Master Analytics Export

32	Export Analytics Data Primary user: Analyst / authorised recipient

AnalyticsController@export is the master endpoint. It supports CSV, Excel through Maatwebsite\Excel and PDF through Barryvdh\DomPDF. Filters include property, date range, currency and analytics type. PDF can include charts.

Format	Best use	Control
CSV	Data exchange and analysis.	No formatting; protect sensitive rows.
Excel	Structured workbook and further analysis.	Validate formula and sheet output.
PDF	Read-only presentation with charts.	Label filters, period and basis.

ROICalculationService@exportAnalytics can export selected analytics type, period and charts for the landlord.

81. Export Validation Checklist

· Landlord and role scope is correct.

· Property and date filters are shown.

· Currency and conversion basis are shown.

· Metric definitions are available.

· AI output is labelled as advisory.

· Prediction and actual data are visually distinct.

· Sensitive Client and employee data is minimised.

· File expiry and access are enforced.

· The report is visually inspected before external distribution.

82. Analytics Data Source Map

Figure 6. Analytics data sources and services

83. Core Models Reference

Model	Purpose
Analytic	Landlord-owned metric, JSON data and recorded time.
AiInsight	Generated insight, metadata, priority and actionable tip.
Report	Generated report status, filters and file.
ScheduledReport	Recurring report configuration and run history.
ReportTemplate	Reusable report layout and filters.
PropertyMarketData	Market price, currency, geography and source.
IoTAnalytics	Device analytics, cost, performance, anomalies and prediction.
SyndicationChannel / SyndicationLog	Listing-channel activity and performance.

84. Core Controllers Reference

Controller	Purpose
AnalyticsController	Properties, finance, predictive, AI chat, alerts and master export.
AdvancedAnalyticsController	Cash flow, ROI, payments, portfolio, cost, gateways, reconciliation, settlements, disputes and webhooks.
PropertyAnalyticsController	Performance, market, AI and property exports.
LeaseAnalyticsController	Lease status, payments, retention and revenue.
IoTAnalyticsController	Energy, performance, usage, comparison, charts and export.
IoTAIInsightsController	IoT AI assistant, energy, predictive maintenance and stream analysis.
WalletAnalyticsController	Wallet trends, relationships, balances and gateways.
MortgageAnalyticsController	Mortgage performance and AI risk.
InsuranceAnalyticsController	Insurance cost, claims, risk and optimisation.
SyndicationAnalyticsController	Property, channel, ROI and real-time syndication.
CrmAnalyticsController	Lead, pipeline and agent analytics.
CrmReportingController	CRM report types and export.
LandSalesReportController	Land revenue, collection, arrears and export.
PropertyFinancialReportController	Cash flow, expenses, tax, P&L, forecast and budget.
ReportController	Reports, schedules, templates, custom and investor outputs.
UtilityAnalyticsController	Revenue, consumption, efficiency and prediction.
AIDashboardController	Central AI dashboard.
AIInsightController / AIGlobalInsightController	Landlord and global insight views.
FraudReportController	Fraud PDF.
MarketplaceDashboardController	Listing, vendor and visibility performance.

85. Services Reference

Service	Purpose
PredictiveCashFlowService	Forecast, property prediction, actual comparison, trends, recommendations and export.
ROICalculationService	ROI, IRR, portfolio return, benchmarks, trends and export.
PaymentPatternAnalysisService	Patterns, behaviour, methods, anomalies and prediction.
SettlementService	Statistics, upcoming items, gateway breakdown, history, analytics and alerts.
DisputeService	Statistics, active disputes, details, creation and resolution.
IoTAIInsightsService	IoT-generated insights and recommendations.
MortgageAnalyticsService	Approval probability, risk and market analysis.
CurrencyService / CurrencyExchangeService	Display and convert analytics amounts.
ExchangeRateService	Exchange-rate input.
OpenAIService	Portfolio, market, finance, alert and conversational insight.
AuditTrailService	Analytics action audit.
ReconciliationService	Transaction matching and reconciliation.

86. FinancialAnalyticsUpdated Event

Aspect	Requirement
Type	ShouldBroadcast event.
Purpose	Push financial analytics updates to the dashboard.
Channel	Private, authenticated and landlord-specific.
Payload	Minimum necessary analytics data.
Frequency	Controlled to avoid excessive refresh and stale race conditions.
Failure handling	Dashboard can refresh through the JSON endpoint.

Broadcast isolation is critical

A correct database query is not enough if the event is broadcast to a shared or guessable channel.

87. AI-Powered Features Reference

AI feature	Controller / service	Purpose
Financial insights	AnalyticsController@getFinancialInsights	Trends, anomalies and forecasting.
Portfolio insights	PropertyAnalyticsController@getAIPortfolioInsights	Diversification and concentration.
Performance insights	PropertyAnalyticsController@getAIPerformanceInsights	Property comparison and opportunities.
Market insights	PropertyAnalyticsController@getAIMarketInsights	Positioning, demand and pricing.
Predictive cash flow	PredictiveCashFlowService@generateForecast	Forecast with seasonality.
ROI recommendations	ROICalculationService@getInvestmentRecommendations	Investment observations.
ROI benchmarks	ROICalculationService@getIndustryBenchmarks	Benchmark comparison.
Payment anomalies	PaymentPatternAnalysisService@detectPaymentAnomalies	Unusual payment patterns.
Payment prediction	PaymentPatternAnalysisService@predictPaymentBehavior	Late-payment risk.
Portfolio-wide insight	AnalyticsController@getAiInsights	Cross-portfolio recommendations.
AI chat	AnalyticsController@aiChat	Natural-language analytics answers.
AI alerts	AnalyticsController@getAiAlerts	Risk and opportunity alerts.
Property analysis	AnalyticsController@propertyAiAnalysis	Property health and recommendations.
IoT energy insight	IoTAIInsightsService@generateInsights	Energy pattern analysis.
IoT maintenance	IoTAIInsightsController@getPredictiveMaintenanceInsights	Equipment-failure signals.
IoT recommendations	IoTAIInsightsController@getEnergyRecommendations	Energy reduction.
IoT stream analysis	IoTAIInsightsController@streamAnalysis	Real-time analysis.
Insurance risk	InsuranceAnalyticsController@riskAssessment	Property risk scoring.
Insurance optimisation	InsuranceAnalyticsController@policyOptimization	Coverage analysis.
Mortgage approval	MortgageAnalyticsService@predictLoanApprovalProbability	Approval probability.
Mortgage risk	MortgageAnalyticsService@performEnhancedRiskAssessment	Enhanced risk scoring.

88. AI Governance and Review

· Document the data source and period used for each AI output.

· Do not include cross-landlord or unnecessary personal data.

· Label generated output clearly.

· Review high-impact recommendations before action.

· Provide a path to inspect supporting data.

· Monitor error, bias, false positives and drift.

· Record actual outcome where possible.

· Allow stale insights to expire or be regenerated.

· Do not claim guaranteed predictions or investment outcomes.

89. Currency and Exchange-Rate Controls

· Store or retain original currency for every source amount.

· Use a defined landlord reporting currency.

· Record exchange rate, source and effective date.

· Do not mix spot rates and historical rates without disclosure.

· Handle missing rates and unsupported currencies explicitly.

· Avoid reconverting an already converted amount.

· Use consistent rounding.

· Show currency on charts, tables and exports.

Multi-currency portfolio totals are calculated views

They should not replace original-currency ledgers or bank balances.

90. Audit Trail and Change Management

· Record who generated or exported a report.

· Record changes to expense categories, failover rules, gateways and webhooks.

· Record report-template and schedule changes.

· Record AI insight generation user and time.

· Record dispute creation and resolution.

· Record reconciliation actions.

· Record SuperAdmin or technical overrides where applicable.

· Preserve prior values for material configuration changes.

91. Worked Example 1 - Monthly Portfolio Performance Review

Scenario

A company manages 30 residential properties and prepares a monthly executive review.

Stage	What the team does
1. Close source data	Post transactions, expenses and lease updates.
2. Reconcile	Match bank, gateway and platform transactions.
3. Property view	Review occupancy, vacancy, rent and maintenance by property.
4. Finance view	Review revenue, expenses, NOI and budget variance.
5. Risk	Review arrears, expiring leases and anomaly alerts.
6. Forecast	Generate 90-day cash-flow prediction.
7. Action	Assign pricing, collection and maintenance actions.
8. Report	Generate a PDF executive report with filters and definitions.

92. Worked Example 2 - Underperforming Property Investigation

Scenario

One property shows lower NOI and higher vacancy than comparable properties.

Stage	What the team does
1. Drill down	Open property performance and source transactions.
2. Validate	Confirm vacancy, rent and expense classification.
3. Market	Compare rents with current PropertyMarketData.
4. Maintenance	Review repeat repair frequency and cost.
5. AI	Review performance and market insight as advisory.
6. Scenario	Test rent, occupancy and cost changes.
7. Action	Approve a leasing, maintenance or cost plan.
8. Measure	Review actual results after the action period.

93. Worked Example 3 - Cash Flow Risk and Settlement Delay

Scenario

Forecasted rent is strong, but a gateway settlement is delayed.

Stage	What the team does
1. Forecast	Review expected rent and scheduled outflows.
2. Settlement	Open delayed-settlement alert and gateway breakdown.
3. Reconcile	Confirm the transactions are successful but not settled.
4. Cash view	Exclude expected settlement from available cash.
5. Treasury	Adjust near-term payment plan.
6. Gateway	Investigate event details and support case.
7. Actuals	Update actual-versus-predicted variance after settlement.

94. Worked Example 4 - CRM and Syndication Channel ROI

Scenario

The landlord wants to decide which listing channels deserve the next marketing budget.

Stage	What the team does
1. Syndication	Review views, inquiries, applications and cost by channel.
2. CRM	Confirm lead source and pipeline conversion.
3. Attribution	Choose and state the attribution model.
4. Revenue	Use verified lease or sale outcomes, not pipeline value.
5. Cost	Include channel, campaign and handling cost.
6. Compare	Rank channels with sample-size and quality context.
7. Budget	Approve budget changes and monitor future performance.

95. Worked Example 5 - IoT Energy and Maintenance Insight

Scenario

A smart commercial building shows rising energy use and HVAC anomalies.

Stage	What the team does
1. Validate	Confirm sensor availability, calibration and tariff.
2. Energy	Review consumption, cost per kWh and peak hours.
3. Comparative	Compare with prior period and benchmark.
4. AI	Generate energy and predictive maintenance insight.
5. Technician	Request qualified inspection.
6. Action	Approve maintenance or control changes.
7. Measure	Track energy and error-rate change after intervention.

96. Implementation and Onboarding Checklist

Data and access

· Landlord, role and property scopes are tested.

· DataIsolation is applied to all analytics routes and services.

· Broadcast channels are private.

· Source model relationships are complete.

· Metric definitions and date rules are documented.

Finance and currency

· Reporting currency and exchange-rate rules are approved.

· Revenue, expense, NOI and cash-flow bases are defined.

· Gateway, settlement and reconciliation sources are connected.

· Budget and accounting category mappings are reviewed.

AI and predictive

· OpenAI configuration is secure.

· AI prompt redaction and data boundaries are configured.

· Human review and advisory labels are enabled.

· Prediction back-testing and expiry rules are defined.

Reports and exports

· PDF, CSV and Excel generation is tested.

· Queue workers and failure retry are configured.

· Scheduled report recipients and retention are controlled.

· Investor and shared-report labelling is approved.

97. User Acceptance Testing and Go-Live

Test area	Acceptance test
Data isolation	Landlord cannot access another portfolio through dashboard, API, export or broadcast.
Dashboard redirect	Analytics index opens the property analytics entry point.
Unified dashboard	Corporate, private and JSON refresh return correct scope.
Realtime event	Correct private channel and payload.
Property performance	Occupancy, revenue and NOI reconcile.
Market analytics	Correct geography, type, currency and source.
Property AI	Supporting data and advisory label.
Financial data	Revenue, expense and net income by currency.
Financial matrices	Cross-property and property drill-down.
Cash flow reports	Opening, movement and closing cash.
P&L	Revenue and expense classification.
Budget comparison	Approved baseline and variance.
Cash-flow forecast	Period, seasonality, confidence and export.
Actual vs predicted	Variance calculation.
ROI	Cap rate, cash-on-cash, total return and IRR.
ROI comparison	Consistent property inputs.
Payment patterns	On-time, method and anomaly analysis.
Payment prediction	No automatic adverse action.
Portfolio KPIs	Value, yield, vacancy, retention, NOI and debt.
Cost optimisation	Expense recategorisation audit.
Gateway analytics	Success, fee, error and failover.
Gateway changes	Authority, audit and rollback.
Reconciliation	Match, exception and detail.
Settlement	Pending, completed, upcoming and alerts.
Disputes	Create, detail, resolve and stats.
Webhooks	Create, test, logs, authentication and deletion.
Predictive hub	Collection, vacancy, churn, maintenance and value.
AI chat	Scope, source support and safe response.
AI alerts	Priority, evidence and expiry.
AiInsight	Ownership, metadata and global-data protection.
IoT analytics	Energy, performance, usage and benchmark.
Lease analytics	Status, payments, renewal and retention.
Wallet analytics	Balances, trends and interaction privacy.
Mortgage analytics	Risk and approval advisory controls.
Insurance analytics	Cost, claims and policy optimisation.
Syndication	Channel and property ROI.
CRM	Leads, pipeline, agent and attribution.
Land sales	Revenue, collection and overdue.
Utilities	Consumption, cost and prediction.
Fraud PDF	Authorisation and flag labelling.
Report lifecycle	Pending, processing, completed and failed.
Scheduled reports	Cron, recipients, history and archive.
Templates	Private and public configuration.
Master export	PDF, CSV, Excel, filters and charts.
Audit	Exports, AI, configuration and operational actions.

Go-live gate

Do not publish investor, tax, credit, fraud or high-impact risk analytics until data isolation, source reconciliation, metric definitions, AI review, report security and audit controls have passed testing.

98. Daily, Weekly and Monthly Operating Procedures

Frequency	Recommended activities
Daily	Review failed refreshes, broadcast errors, high-priority AI alerts, settlement delays, gateway issues and report failures.
Weekly	Review occupancy, arrears, payment patterns, expiring leases, open disputes, cost anomalies and predictive changes.
Monthly	Close and reconcile finance data, compare forecast to actual, refresh ROI, review portfolio KPIs and issue management reports.
Quarterly	Review metric definitions, AI drift, market-data sources, benchmark suitability, access, schedules, templates and retention.

99. Common Issues and Troubleshooting

Issue	Recommended action
Dashboard is empty	Check landlord scope, source records, date filter and data refresh.
Another landlord data appears	Stop access, inspect DataIsolation and broadcast channel, and treat as a security incident.
Financial totals differ	Check accounting basis, reconciliation, currency, duplicate transactions and date range.
Occupancy is wrong	Check unit status, lease activation and eligible-unit denominator.
Market comparison is misleading	Check source date, property type, area, neighbourhood and currency.
AI answer has no evidence	Open supporting dashboards or regenerate with explicit scope.
Forecast is too optimistic	Review arrears, vacancy, settlement timing and seasonality.
ROI differs from finance report	Check valuation, NOI, debt, capital costs and cash-flow dates.
Payment risk false positive	Review callbacks, reversals, currency, due date and actual history.
Gateway success looks low	Separate technical errors, Client declines and verification timeouts.
Settlement is missing	Check gateway batch, currency, date, fee and reconciliation.
Reconciliation duplicates	Review matching rules and idempotency.
Scheduled report not sent	Check is_active, cron, next_run_at, queue, recipient and last_error.
Report remains processing	Check worker, timeout, file permissions and job failure.
PDF chart is missing	Check chart generation, includeCharts and renderer.
IoT anomaly repeats	Check sensor quality, threshold and event deduplication.
CRM revenue is inflated	Use verified closed outcomes rather than pipeline value.
Syndication ROI conflicts	Check attribution method and channel cost.

100. Frequently Asked Questions

Does Analytics show all of Leaseora?

It aggregates many supplied modules, subject to the user's role, data availability and configured integrations.

Can landlords see each other's analytics?

No. DataIsolation and authorisation should restrict every view, API, broadcast and export.

Are dashboard numbers real time?

FinancialAnalyticsUpdated supports real-time broadcast, but source data and service refresh timing still determine freshness.

Can Analytics predict rent collection?

Yes, the supplied predictive service supports forecasts, but they are estimates rather than guaranteed receipts.

What returns can be calculated?

The supplied service includes cap rate, cash-on-cash, total return and IRR.

Can the system predict late payment?

Yes, as advisory risk. Human review and fair process remain required.

Can AI answer questions about the portfolio?

Yes, through AnalyticsController@aiChat using authorised portfolio context.

Can Analytics change gateway settings?

AdvancedAnalyticsController includes failover and gateway controls. These should use operational change approval.

Can reports run automatically?

Yes, ScheduledReport stores frequency, cron, recipients and run history.

What formats are supported?

The supplied flow supports PDF, CSV and Excel.

Can an investor report be created?

Yes, ReportController@investorReport provides a formatted portfolio report.

Are reports audited?

Report generation can be logged, but the output is not independently audited unless a separate audit occurs.

Can IoT data be analysed?

Yes, energy, device performance, usage, anomalies and predictive maintenance are included.

Can global AI insights be shown?

Yes, but they should be aggregated and must not expose private landlord data.

101. Technical Matters to Confirm Before Production

Area	Confirmation required
Metric formulas	Exact occupancy, vacancy, NOI, yield, retention, collection and ratio formulas.
Data refresh	Live query, cached metric and refresh schedule per dashboard.
DataIsolation	Coverage of controllers, services, queues, exports, AI and broadcasts.
Broadcast channels	Private naming, authorisation and payload.
Analytic model	Metric naming, retention and time-series aggregation.
Currency	Rate provider, date, original amount, rounding and unsupported currency.
Market data	Source, freshness, licence, coverage and confidence.
Financial basis	Cash versus accrual and treatment of deposits, capital and financing.
Forecast model	Inputs, confidence, seasonality, version and back-testing.
ROI formulas	Valuation, NOI, cash invested, IRR dates and terminal value.
Payment pattern model	Features, thresholds, consent, fairness and false-positive review.
Portfolio value	Valuation source and effective date.
Benchmark data	Source and matching logic.
Gateway analytics	Attempt, success, fee, timeout and failure definitions.
Gateway controls	Approval and rollback for toggle and failover.
Reconciliation	Matching rules, tolerances and adjustment authority.
Settlement	Gross/net, expected date, fee and bank-receipt linkage.
Dispute	Statuses, evidence, financial impact and resolution authority.
Webhook	Authentication, signature, retry and log retention.
OpenAI	Model, prompt, retention, regional processing and cost limits.
AiInsight	Expiry, archive, review and outcome tracking.
IoT	Units, calibration, missing data and carbon factors.
Mortgage analytics	High-impact decision and fairness controls.
Insurance analytics	Policy and claim amount bases.
Syndication attribution	First, last, linear or another model.
CRM revenue	Verified revenue versus pipeline value.
Report queues	Timeout, retry, concurrency and failure notifications.
Report sharing	Recipient access, link expiry and download audit.
Scheduled reports	Timezone, cron validation and recipient review.
Fraud output	Flag versus confirmed case and adverse-action controls.
Retention	Analytics records, AI prompts, exports, logs and generated files.

Specification basis

This guide preserves the terminology, controllers, services, models and workflow supplied for the Leaseora Analytics module. Undefined production behaviour is listed for confirmation rather than silently assumed.

102. Quick Reference - 45-Step Analytics Operating Flow

1. Open Analytics and confirm the landlord scope.

2. Choose corporate, private or unified dashboard as applicable.

3. Confirm reporting period and preferred currency.

4. Review data freshness and source completeness.

5. Review property value, occupancy, vacancy and revenue.

6. Compare property performance and NOI.

7. Review current market data and comparables.

8. Review portfolio concentration and diversification.

9. Open financial analytics.

10. Review revenue, expense, net income and matrices.

11. Review cash flow, P&L, tax, forecast and budget comparison.

12. Generate predictive cash flow.

13. Review confidence and seasonality.

14. Compare actual cash flow with prior prediction.

15. Calculate property ROI and IRR.

16. Compare properties and benchmarks.

17. Review payment behaviour and method mix.

18. Investigate anomalies and predicted late risk.

19. Review portfolio KPI cards.

20. Review cost drivers and optimisation recommendations.

21. Review gateway success, fees, errors and failover.

22. Reconcile transactions.

23. Review settlement status and alerts.

24. Create or resolve payment disputes.

25. Review webhook configuration and logs.

26. Open the predictive analytics hub.

27. Review vacancy, churn, maintenance and value predictions.

28. Use AI chat for a specific authorised question.

29. Review AI alerts and supporting data.

30. Review property-specific AI health analysis.

31. Review central AiInsight records.

32. Review lease analytics.

33. Review IoT energy, performance and usage analytics.

34. Review wallet trends and balances.

35. Review mortgage and insurance analytics.

36. Review syndication channel ROI.

37. Review CRM pipeline and reporting.

38. Review land sales and utility analytics.

39. Generate fraud report only for authorised users.

40. Create an on-demand report.

41. Validate the completed PDF, CSV or Excel file.

42. Create or review scheduled reports and recipients.

43. Export master analytics with filters and definitions.

44. Assign actions and owners.

45. Measure actual outcomes and update assumptions.

Business value

Leaseora's Analytics module gives a real estate company one connected intelligence environment for portfolio performance, financial control, forward planning, operational risk, market insight, payment infrastructure, smart-property data, customer acquisition and management reporting.

LEASEORA

ANALYTICS

Turn connected real estate operations into explainable, actionable and reportable intelligence.

Support and onboarding

For analytics onboarding, KPI definition, currency setup, predictive services, AI governance, report templates, scheduled reports, WebSocket dashboards, IoT analytics or export assistance, contact Leaseora through support@leaseora.com.

leaseora.com

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Article Info

Category ANALYTICS

Reading Time 49 min

Published Jul 30, 2026

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