A media buyer launches a £50,000 digital billboard campaign, only to later discover that half the sites are underperforming; however, by that time the budget is already exhausted. A transport network manager watches helplessly as crowds build dangerously at the station during the disruption, failing to see the problem until complaints flood in. The venue operator is holding an event for 60,000 people based on last year’s gathering patterns and crowd movement, unaware that this year’s audience is concentrated in different areas, creating security risks that won’t be apparent until it’s there.
These scenarios have a common thread: businesses make important decisions without knowing where people are right now. And the cost of this blind spot is significant. Traffic congestion in London alone costs the economy £5.1 billion a year, largely due to reactive rather than proactive management. The advertising industry has historically relied on intuition and estimated impressions rather than actual audience measurement, leading to wasted spend and unmeasurable ROI. And in our increasingly complex society, public safety organizations face increased challenges due to a lack of situational awareness during large gatherings, where the difference between knowing and guessing can mean the difference between a successful event and disaster:
- For ads and out-of-home media buyersthe challenge is to demonstrate value. You pay for your audience based on modeled estimates and historical traffic numbers, but the industry is crying out for a single, accurate and deduplicated number that demonstrates real reach. Without real-time data on who is actually present in your placements and whether they match your target demographics, you can’t optimize campaigns throughout the process, demonstrate ROI to clients, and confidently justify premium placements.
- For traffic planners and operations teamsthe fundamental challenge is the ability to share and process data from different systems to gain real-time visibility. You manage networks designed to move millions of people, but often react to problems such as bottlenecks, overcrowding, disrupted dispersal patterns, only after they have already affected passengers. Without understanding real-time travel patterns and crowd movements at major hubs, you are forced to manage your network reactively rather than proactively, and miss opportunities to prevent problems before they escalate.
- For venue operators and public safety teamsthe stakes are even higher. Whether you’re managing planned stadium events or responding to unplanned gatherings, you need to monitor real-time crowd numbers and compare them to historical baselines. The ability to detect abnormal behavior (either in the overall crowd size or within specific demographic cohorts) can be the difference between maintaining safe conditions and facing a crisis. Yet many organizations still lack the tools to track crowd dynamics as they evolve.
Converting mobile network data into useful statistics
This is where O2 Motion Real Time Location Insights (RTLI) changes the equation. By transforming aggregated and anonymised mobile network data collected from over 25 million customers into actionable information, we enable businesses to understand population density, movement patterns and demographics across the UK during events, not hours or days later when it is too late to act. With the Databricks Data Intelligence Platform, we’ve built a platform that processes one of the UK’s largest mobile networks at scale, turning raw signals into real-time insights that drive smarter resource allocation, more effective marketing, safer operations and measurable business results.
However, the power of RTLI goes beyond the O2 Motion platform itself. Through Delta Sharing, organizations can access this real-time location intelligence directly within their own data ecosystems without the need for complex ETL pipelines, API integrations or data duplication.
This seamless integration closes the critical gap between centralized processing of massive data volumes and availability for demanding organizations, enabling data teams to combine RTLI data with their own datasets to unlock sophisticated analytics scenarios:
- Transport authorities can build predictive ML models that predict congestion by combining real-time traffic data with weather, scheduled events, and historical incident data.
- Advertisers can create dynamic attribution models that link campaign exposure to actual physical traffic in retail stores, proving ROI with unprecedented accuracy.
- Venue operators can develop anomaly detection algorithms to flag unusual crowd formations or demographic distributions before they become security issues.
- Public Safety Teams they can run thousands of scenario simulations, compare current crowd dynamics with historical events and identify emerging risks.
And because the data arrives in real-time within their Databricks lake, organizations can immediately put these insights to work, trigger automatic alerts, adjust digital signage, redirect resources or optimize campaigns, all while maintaining the governance, security and provenance control required.
We bring the end of guesswork to your business
The era of making high-stakes decisions based on guesswork, assumptions and historical data is coming to an end. Real-time location information is no longer a competitive advantage; it becomes the stakes for organizations that need to understand where people are, how they move, and what that means for operations, security, and revenue.
Whether you’re optimizing media spend, managing complex transportation networks, or ensuring public safety at large, the question is no longer whether you have access to real-time location information; it’s about whether you can afford it. Visit the Databricks Marketplace to learn more about Real Time Location Insights from O2 Motion and discover how Delta Sharing and the Databricks platform can transform your organization’s approach to location information.
Visit the Databricks Marketplace to learn more about O2 Motion’s real-time location statistics