The Future of Real Estate Data Transparency

In an era driven by data, transparency is non-negotiable. For retail real estate professionals, the need for clarity in how data is collected, handled, and shared has never been more critical. With millions of dollars often hinging on location-based decisions, understanding the quality and reliability of data inputs is fundamental to building trust in the insights that guide those decisions.

Over the coming months, I will explore various data-sets, predictive modeling types, and the evolving role of transparency—not only in the inputs and outputs but also in the decisions and strategies they drive.

Navigating the Reliability Crisis in Mobile Location Data

One of the most debated topics in the location intelligence industry today is the reliability of mobile location data. While mobile data has opened up opportunities to understand foot traffic patterns and consumer behavior at a granular level, its accuracy is increasingly being called into question.

Concerns stem from several factors:

• Fragmentation of Data Sources: With multiple vendors and varying collection methods, consistency is difficult to achieve.
• Privacy Legislation: Laws like GDPR and CCPA, alongside shifts in device tracking permissions, continue to erode the volume and granularity of mobile data.
• Black-Box Methodologies: Many data providers fail to disclose their collection processes, leaving users in the dark about how much trust to place in the insights they provide.

The future of mobile location data is uncertain. As legislation evolves and consumer awareness around privacy grows, real estate professionals must ask themselves: Are we relying on data that may not stand the test of time?

At PiinPoint, mobile data is an input to our models, along with other datasets. To address these concerns, we actively seek partnerships with organizations that uphold the highest standards in data quality and privacy. Environics Analytics, is a great example of an industry leader known for their rigorous privacy practices and commitment to transparency. Their methodologies serve as a benchmark for how data can and should be collected, ensuring reliability and compliance even as privacy regulations evolve.

Below, we outline how we de-risk the use of mobile data, while providing clients with results you can trust and feel confident in.

Upholding Higher Standards for Data Accuracy

At PiinPoint, we recognize that our users’ success relies on the accuracy of the insights we provide. Location decisions aren’t just for today—they’re investments in the future, with outcomes measured in years, not months.

That’s why we’ve taken a deliberate approach to the data we use in our models:

• Rigorous Data Vetting: Every data source we integrate undergoes thorough scrutiny to ensure reliability and consistency over time.
• Transparency in Methodologies: We prioritize openness about how data is collected and modeled, empowering our users to understand the inputs behind their results.
• Beyond Mobile Data: While mobile location data is one piece of the puzzle, PiinPoint incorporates a broader range of inputs—demographics, market trends, and custom client data—providing a more holistic view of each location’s potential.

This commitment to accuracy and transparency isn’t just a feature—it’s a cornerstone of our approach to empowering real estate professionals with tools they can trust.

Building Trust Through Transparency

We understand that skepticism around data quality is a barrier for many teams. To address this head-on, we’re committed to initiatives that foster trust and clarity:

• Data Trust Webinar Series: These casual conversations between PiinPoint and our data partners dive into how data is collected, handled, and maintained for accuracy. By making these processes visible, we aim to instill confidence in the insights our platform provides.
• Building Trust Through Exemplary Partnerships: One such partner, Environics Analytics, sets a gold standard in the industry for privacy compliance and data quality. Their rigorous approach to safeguarding privacy and ensuring data reliability aligns with our with providing our clients with trustworthy insights.
• Data Suitability: Our collaborative approach with customers means we deeply understand your business use case. Just because a dataset exists doesn’t mean it’s suitable for you.?
• Customer-Centric Transparency: We prioritize user education on our data models, ensuring that even non-technical users feel empowered to understand the “why” behind their results.

Why Transparency Matters for Your Bottom Line

The stakes for data accuracy are high in retail real estate. Location decisions informed by unreliable data can lead to costly mistakes, from underperforming sites to missed market opportunities.

In contrast, decisions guided by transparent, reliable data allow your team to operate with confidence, knowing that the insights are grounded in accuracy. This reliability translates to better site performance, optimized expansion strategies, and ultimately, stronger returns on your investments.

Looking Ahead

As the demand for data transparency grows, we see a shift in the industry:

• Providers will be held to higher standards of accountability.
• Teams will prioritize tools that offer clarity, not just insights.
• The balance between privacy and actionable data will continue to evolve, shaping how we approach location intelligence.

At PiinPoint, we’re proud to lead this charge. By holding ourselves—and our data—to the highest standards, we’re equipping real estate professionals to make confident, informed decisions, now and in the future.

What are your biggest concerns about data transparency in 2025 and beyond? Let’s continue the conversation—leave your thoughts below or reach out directly.