Expanding across geographies is one of the most powerful ways an enterprise can grow, but it’s also one of the most complex. Different regions operate at different levels of digitization, sales teams often rely on inconsistent data, and organizations struggle to maintain visibility across multiple markets. The companies that break through these challenges all share one foundational element: they rely on high-quality, globally consistent data.

Traditionally, companies have had to choose between two types of providers: those with strong places, also known as point-of-interest (POI), data or those with strong foot traffic data. High-quality, globally consistent places data gives teams a clear picture of what exists. Foot traffic shows how people actually interact with those places. But to truly understand market dynamics, competitive environments, and real-world consumer behavior, organizations need the strength of both datasets. But, it’s rare to find a partner that consistently delivers both.

When global coverage, accuracy, and trend patterns come together, organizations can make sharper decisions, open new markets with confidence, and dramatically increase the productivity of their sales teams. We explore how this combination of global reach, reliable data quality, and sales enablement transforms performance across industries.

Global Coverage Without Compromise

For global enterprises, incomplete or inconsistent data is more than an inconvenience, it’s a barrier to intelligent expansion. Many vendors offer basic places data, but fall short once you move beyond a handful of well-digitized markets. Others offer foot traffic insights, but only in select regions, leaving major gaps in global strategy.

A unified dataset solves this by ensuring every market is supported with the same level of quality and standardization. This allows organizations to:

• Evaluate total addressable markets more accurately
• Standardize data structure and definitions across regions
• Reduce technical effort tied to reconciling disparate datasets

This consistency gives leaders the clarity they need to prioritize the right opportunities across dozens of markets and multiple business units. When the entire organization works from the same data foundation, strategy becomes clearer and far more scalable.

Quality & Accuracy: The Foundation of Better Outcomes

Global coverage is essential, but coverage alone is not enough. The accuracy and reliability of places and foot traffic data determine whether strategies succeed or fail. A lack of robust, comprehensive data creates costly downstream effects; misleading attributes, outdated statuses, or misaligned categories can lead to wasted sales activity, flawed models, and misinformed decisions.

This is precisely why high-quality data is characterized by:

• Rigorous vetting and validation
• Standardized schemas across markets
• Reliable update cadences teams can rely on

This level of quality builds trust. It ensures analytics teams, sales leaders, and field reps all work from the same dependable bedrock. When organizations no longer worry about whether the underlying data is correct, they can redirect focus on what matters – execution and innovation.

How Teams Put Places & Foot Traffic Data to Work

Once organizations have a clear view of what exists in each market and how those locations behave, teams across industries can use this information to evaluate opportunities and reduce uncertainty. 

Financial services firms leverage places and foot traffic data to assess the commercial strength of potential markets. By reviewing business density, category mix, and visitation trends, they can identify areas with strong economic activity and steer clear of locations with weaker fundamentals. This helps them deploy capital in places with a higher likelihood of sustained performance.

Commercial real estate teams rely on this data to evaluate the viability of potential sites. They examine nearby amenities, competitive presence, and then employ foot-traffic behavior to determine whether a property is well-positioned for tenant success. This layered approach to data helps reveal market strengths, potential gaps, and long-term supply-and-demand patterns that might otherwise have gone undiscovered through surface-level observations.

Retail and CPG companies use places and foot traffic data to understand store network performance, find white space for expansion, and assess competitive saturation. A brand evaluating new store locations can analyze nearby retailers, customer movement patterns, and surrounding business mix to identify areas with strong shopper activity. This same data helps CPG teams understand where their products are likely to reach the most consumers and which markets have unmet demand.

The Future Has Yet to Be Realized

The location intelligence landscape is evolving. AI is accelerating how data is collected, and open-source mapping ecosystems are reshaping expectations around availability and cost. But even as data becomes more abundant, most providers still specialize in either places or foot traffic; very few have the infrastructure to deliver both at global scale with enterprise-quality standardization.

Organizations poised for long-term success will be the ones who invest in a strong data backbone now—one that combines global places coverage with high-quality foot traffic insights and maintains the highest standards for accuracy. Separately, these two datasets are mere inputs, combined they become a strategic advantage.

At dataplor, we’re committed to delivering our clients that advantage with the clarity, consistency, and global perspective required to grow smarter and execute faster. Let’s connect today.