Conversations at this year’s CREtech conference revealed the real estate industry is ready to modernize—especially around how data, AI, and predictive modeling can drive better investment and property decisions.

Themes like site selection, property valuation, and localized market analysis dominated discussions. But underneath those topics was a shared recognition: the industry can’t continue to lean on instinct the way it has in the past. Reliable, transparent, and up-to-date data continues to expand as the foundation for competitiveness.

Urgency for Data Confidence

Across panels and networking sessions, it was made clear that data quality directly determines decision quality. Many attendees shared their frustrations with incomplete or unreliable datasets, especially around foot traffic, multi-tenant properties, and fast-changing markets.

This trust gap has created hesitation. Commercial real estate (CRE) professionals know they need to adopt modern data strategies but remain skeptical after years of inconsistent vendor performance. The priority now is confidence, not just access to data, but assurance in its accuracy, origin, and freshness.

dataplor helps bridge that gap by delivering accurate, current, and context-rich datasets that reflect real market conditions. Each record is consistently validated and refined to ensure reliability across regions and property types. This level of precision gives CRE teams the confidence to evaluate opportunities, benchmark performance, and guide investment strategies with data they know they can depend on.

AI is Only as Good as its Inputs

AI and predictive modeling were the most discussed technologies at CREtech. Yet the excitement came with a warning: without reliable inputs, advanced modeling can produce misleading results.

Many organizations are rushing to adopt AI for site selection, portfolio optimization, and property valuation, but lack the clean, consistent, and current data necessary to support those models. The takeaway is simple: AI is only as smart as the data that feeds it.

dataplor’s global POI and foot traffic datasets provide high-quality, structured data that integrates seamlessly into clients’ backend systems. This foundation ensures that predictive tools and AI-driven workflows can operate on reliable, reality-based insights.

[Local] Context is Everything

Another theme gaining momentum across CREtech was the demand for deeper local context. Investment decisions are increasingly influenced by neighborhood-level factors: nearby business openings and closures, local consumer activity, and shifts in foot traffic patterns.

Traditional CRE data often stops at financials or property-level indicators, missing these critical layers of environmental intelligence. As competition intensifies, investors and analysts need to understand not only what is happening in a market but why.

dataplor’s robust datasets deliver precisely this context through verified POI data, open and closure tracking, and reliable foot traffic insights. These inputs enable teams to evaluate areas for growth with confidence and anticipate changes before they surface in traditional metrics.

Trust Through Transparency

Perhaps the most important shift at CREtech was a philosophical one. The industry is moving away from the “black box” mentality of opaque data providers and toward collaboration and transparency.

CRE professionals aren’t just looking for more data—they’re looking for data partners who can help interpret, validate, and apply insights effectively. The emphasis has moved from buying data to building confidence.

dataplor’s commitment to transparency, human validation, and customer partnership resonated strongly with attendees. By aligning our methods with clients’ expectations and clearly communicating what our data represents, we help bridge the gap between information and action. 

If you’re in a place to see your markets more clearly, let’s connect.