Most PropTech companies still run marketing, product, sales, and finance data in four systems that never talk to each other. Winston Francois builds the analytics infrastructure that gives real estate tech companies one trustworthy view of what is working. Our clients stop guessing and start operating on evidence.
The Problem
Your data lives in silos that do not talk to each other
Marketing data sits in one platform, product usage in another, sales in a CRM, and financials in a spreadsheet. Nobody owns a single view of the customer journey from first touch to closed deal. When your CEO asks which channel produced your best customers this quarter, nobody can answer with confidence, so the loudest voice in the room wins the budget argument instead of the numbers.
You cannot attribute revenue to the activities that created it
Real estate tech sales cycles run long and cross marketing, sales, and product touchpoints before a deal closes. Without proper attribution you cannot tell whether a conference sponsorship, a content series, or an outbound sequence actually moved a deal forward. Spend keeps getting renewed on habit rather than evidence, and the channels quietly underperforming never get cut.
Your reporting takes too long and tells you too little
If a monthly marketing report still takes three days of manual spreadsheet work, it is stale before it reaches leadership. Manual assembly also introduces copy-paste errors that quietly erode trust in the numbers, so people start double-checking dashboards instead of acting on them, which defeats the purpose of having them.
You measure activity instead of outcomes
Impressions, clicks, and email opens are easy to track. Qualified pipeline and closed revenue are not. Most PropTech teams default to what is easy to pull rather than what predicts growth, which is how a dashboard full of green arrows ends up next to a flat revenue line in the same board deck.
How We Help
Winston Francois builds analytics infrastructure for PropTech companies that connects marketing spend, product usage, sales activity, and revenue into one model. We do not just stand up dashboards – we build the data foundation that makes those dashboards worth trusting.
We start with a data audit. We map every source across your marketing, product, and sales stack to see what you are collecting, what you are missing, and where the gaps sit. For PropTech companies this usually means reconciling listing-platform data, CRM records, marketing automation, product analytics, and financial systems. This audit feeds directly into your broader [growth strategy](/services/strategy/) by naming which metrics actually predict revenue for your business, not which ones are easiest to screenshot.
Next we design the measurement framework – not a KPI list, but a model showing how leading indicators connect to lagging outcomes. For a PropTech company that often means mapping the path from website visitor to demo request to pilot to signed contract, with conversion rate and time-in-stage at each step, so you can see exactly where deals stall.
We then build the infrastructure: event tracking, data pipelines, attribution models, and dashboards. We work with your engineering team to implement proper product event tracking, and we connect your [marketing](/services/marketing/) platforms to your CRM and your CRM to finance. The goal is one source of truth that updates on its own and never needs manual assembly.
Attribution is where most PropTech teams get stuck, and where we spend the most time. Long cycles with multiple stakeholders make simple last-touch attribution misleading. We build multi-touch models that reflect how your deals actually happen, so budget goes to the channels and activities genuinely driving revenue – not the ones that happened to touch the deal last.
We build dashboards at three levels: an executive view for business health at a glance, functional views for marketing and sales to run daily operations, and analyst views for digging into anomalies. Your CEO and your demand gen manager should never be looking at the same screen.
Finally, we train your team to use it. The best infrastructure is worthless if nobody changes behavior because of it. We run working sessions on reading the dashboards, asking better questions of the data, and deciding based on evidence. [Measurement](/services/measurement/) is a practice we install, not a project we hand off.
What we deliver
- Data audit and gap analysis – full inventory of data sources, collection gaps, and integration opportunities
- Measurement framework – a KPI model connecting leading indicators to PropTech growth outcomes
- Analytics infrastructure – event tracking, data pipelines, and attribution model implementation
- Dashboard suite – executive, functional, and analyst views built for your specific data stack
- Team training and documentation – working sessions and reference guides for daily decision-making
The PropTech companies that grow fastest in 2026 are not the ones with the most data. They are the ones that trust their data enough to act on it before the quarter closes.
Our Methodology
We build analytics infrastructure in 90-day sprints because the work has phases that need time to mature. Sprint one covers the data audit, measurement framework, and initial buildout, prioritizing acquisition source tracking and pipeline attribution first so your team starts deciding differently within weeks, not quarters.
Sprint two expands coverage and refines the models – adding product analytics, deepening attribution, and building out the full dashboard suite. This is also when we train your team and establish the rhythm: weekly reviews, monthly deep-dives, quarterly planning built on actual numbers instead of forecasts.
By sprint three, the infrastructure is stable and your team runs on it daily. We shift to optimization – tuning attribution against closed-loop outcomes, adding new sources as your stack evolves, and running the specific analyses that answer whatever strategic question your leadership is asking that quarter.
How We Work
In the first 30 days we run the data audit, interview stakeholders across marketing, sales, product, and leadership, and deliver the measurement framework. Technical implementation of the highest-priority tracking starts in parallel – your engineering team will need to free up some capacity here.
Days 30 to 60 complete the infrastructure buildout and launch the initial dashboards. Your team starts using real data in weekly decisions, and we run working sessions to build confidence in the numbers as attribution models go live and get calibrated against real outcomes.
Days 60 to 90 refine dashboards based on how your team is actually using them, expand to additional data sources, and deliver team training. The final deliverable is an analytics playbook documenting your measurement framework, dashboard guide, and data governance practices. Most clients continue on a retainer for ongoing optimization once the base is live.
Your team includes a data strategist, an analytics engineer, and a dashboard designer, with data engineers pulled in for complex integration work as needed.
- Unified data view across marketing, sales, and product
- Multi-touch attribution built for long, multi-stakeholder sales cycles
- Automated reporting that removes hours of manual spreadsheet work weekly
- Budget and headcount decisions backed by pipeline data, not anecdote
If your real estate / proptech company needs data, reporting & analytics leadership, we should talk.
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Frequently asked questions
How much does analytics infrastructure cost for a PropTech company?
Cost scales with the complexity of your data stack, the number of integrations required, and how deep the attribution modeling needs to go. We scope every engagement after the data audit so you know the investment before committing further. For most growth-stage PropTech companies, the infrastructure pays for itself within two quarters through better budget allocation alone, before counting the time saved on manual reporting.
How long before we have usable dashboards?
Initial dashboards with core metrics go live within the first 30 days. The full suite, including attribution, product analytics, and executive views, is typically complete by day 60. We sequence the most decision-relevant metrics first so your team benefits immediately instead of waiting for a full rollout.
How does your team work with our engineering team?
We work directly with your engineers on event tracking and data pipeline setup, providing technical specifications, reviewing implementation, and troubleshooting alongside them. Most PropTech engineering teams need to allocate one to two sprint cycles for initial implementation, with minimal ongoing maintenance once tracking is live.
What makes Winston Francois different from other analytics consultants?
We are growth operators, not data consultants – we build analytics infrastructure because it makes growth programs work better, not as an end in itself. We understand PropTech buyer journeys, long sales cycles, and the specific data challenges of real estate technology. Our dashboards are built for people making growth decisions, not analysts exploring data for its own sake.
How do you handle data privacy and compliance in real estate?
Real estate data often includes personal information about property buyers, sellers, and renters. We design tracking and storage with privacy by default: collecting only what is needed, anonymizing where possible, and building consent management into the infrastructure from day one. We build with real estate-specific data handling requirements in mind, not bolted on afterward.
What type of PropTech company needs analytics services?
If you are spending on growth and cannot say which channels drive your best customers, you need this. That gap is most costly from Series A onward, once spend is large enough that misallocation actually hurts. Companies with long sales cycles and multiple touchpoints see the most value, because attribution is the hardest problem to solve by hand in that environment.
