Introduction: The Evolution of "The Where"
For over a decade, location intelligence derived from mobile phone data has promised to revolutionise how we understand the physical world. The premise is simple: by analysing how devices move through space, organisations can understand foot traffic, catchment areas, and dwell times with a precision, coverage and efficiency that manual surveys could never match.
However, as the industry has matured, a paradox has emerged. While the demand for location insight has expanded beyond specialist GIS teams to include commercial property & investment teams, retail & hospitality operators and precinct planning & design, the access to that insight has remained surprisingly high friction.
Due to the sheer storage size of the data and complex processing, organisations today are typically faced with two binary choices: build an expensive specialist internal data science pipeline, or subscribe to comprehensive Software as a Service (SaaS) platforms that require onboarding, training, and annual contracts. The costs and overhead commitments of SaaS subscriptions can easily become a barrier to organisations wanting to access location intelligence.
But what happens when you just need the answer quickly, or as a one-off investigation?
A new entrant to the market, BizziRex, is challenging this binary by offering a third way: on-demand, expert-interpreted location intelligence reports without the SaaS platform overhead. This article explores the current friction in the location intelligence market, the rising fatigue with subscription models, and how BizziRex is positioning itself to fill the gap using high-quality data streams.
The Challenge of Raw Data
At the foundational level, location intelligence relies on massive datasets of mobility traces—latitude, longitude, and timestamps generated by mobile devices.
While this data is "ground truth," it is inherently complex to derive insights. It is not decision ready. Quadrant does the heavy lifting of sophisticated cleansing, hygiene, and processing to be ready to ingest for insights. The industry challenge, potentially restricting the number of insight providers to the market is that location data includes billions of data records, requiring complex location data science storage and processing pipelines to manage high-frequency updates, the demanding computer processing and privacy preservation. On top of that are the proprietary approaches to derive insights.
For most businesses, building the internal capability to ingest raw data (like that provided by Quadrant) and turn it into answers is time and cost prohibitive. It requires not just data access, but a team of highly specialised analysts with the ‘know-how’ and research and development over years of the proprietary approaches to produce the insights
The Limits of SaaS: Subscription Fatigue
To solve the raw data complexity, the market responded with SaaS (Software as a Service) platforms, such as online interactive web platforms and dashboards. These tools aggregate data into user-friendly dashboards, allowing users to click on a map and see charts.
While powerful, SaaS platforms introduce their own friction. They are built for "power users"—analysts and technical operators who log in daily. However, for an organisation who only needs to evaluate a site once a quarter, or a retailer deciding on a single new location, an annual subscription is often overkill.
Recent statistics paint a stark picture of "SaaS fatigue" in 2025:
• License Waste: Organisations waste an estimated $21 million annually on unused licenses, with nearly 53% of SaaS licenses going unutilised.
• Procurement Friction: Buying a new platform often triggers months of IT security reviews, legal negotiations, and onboarding.
• Complexity: Even with a dashboard, stakeholders often struggle to interpret the charts and gain insights. As noted by industry veterans, "teams are asked to interpret complex outputs without the time or support to do it properly".
There is a demonstrated "data literacy gap" in business decision-making. Access to data does not guarantee effective use. Without the on-demand timely and expert assembly of the insights, it is often not decision ready when it is needed.
The On-demand Decision Ready Insights Gap
This landscape leaves a significant gap in the market. There is a distinct need for "decision-ready" insights that do not require a SaaS platform subscription login, associated fees or annual commitment.
Consider a property developer assessing a single site. They don't need a 12-month license to a global location intelligence platform; they need a validated report for their investment committee - this week. "Imagine a no lock in, fixed fee location intelligence report with a 1–2-day turnaround time. All the customer has to do is simply draw the area of interest in 5-minute online order checkout.
This is where the "Consultancy-Lite" or "On-Demand" model finds its product-market fit. It trades the "always-on" capability of SaaS for the "high-impact" specificity of expert reporting.
Enter BizziRex: Clarity Without Complexity
BizziRex (www.BizziRex.com) has launched specifically to address this friction. Founded by industry specialists, the company positions itself not as a software platform, but as a provider of easy and accessible "decision-ready location insights".
Their model is distinctively low-tech in delivery but high-tech in processing:
1. No Subscriptions: It operates on a pay-per-report model, treating location intelligence as a project expense (OPEX) rather than a capital software investment.
2. No Platform Training or Hiring Experts: BizziRex does all this – Why hire in-house experts when you can leave it to the BizziRex experts and save on all the overhead costs.
3. No Dashboards: Users do not log into a tool. They submit a site boundary and receive an insights PDF report.
4. Up-front Fees: Consumers want to know costs –upfront. BizziRex are pioneering the market by publishing fees publicly on their website. There is a shift away from hidden costs and extensive discussions to just know how much it costs.
5. Expert Interpretation: The reports are assembled by expert geospatial analysts and quality assured in a 1-2 day delivery turnaround time.
As co-founder Nicholas notes, "I’ve seen teams commission large platforms when what they really needed was a clear, site-specific understanding of how a location is actually used".
Under the Hood: Powered by Quality Data & High Precision Processing
The level of granularity of BizziRex reports are unparalleled due to their innovative processing. As each insights report is generated from the raw Quadrant location data, the location boundary captures all the data exactly within the area of interest. SaaS platforms usually pre-process data then upload it to the platform for subscribers to interrogate. The pre-processed data is aggregated into larger unit areas like hexagon tessellation patterns – effectively diluting the SaaS raw data and derived insights.
While the delivery mechanism is simple, the engine relies on high-resolution mobility data. BizziRex uses Quadrant location data—rather than modelled or theoretical data.
This distinction is critical. "Modelled" data often relies on census assumptions that may be outdated. "Observed" data (or Ground Truth) shows actual movement patterns. By utilising high-quality Quadrant data, BizziRex can answer complex questions like:
• Targeted advertising: “Where do visitors come from and what is the catchment area”
• Resource allocation: “What are the busiest times of the day”
• Leasing: "Which site has the highest passer by foot traffic?"
• Asset utilisation: "How are waterways and marine assets being utilised?" (A unique niche for BizziRex).
• Competitor analysis: "What are the return visitor rates and stay time of nearby competitors? "
• Return on investment: "Did the advertising campaign increase visitor rates, stay times and return visitors? "
• Who is your typical visitor: "Demographic profile of the average visitor detailing gender, age, income and family composition, compared to the countries average."
Comparing the Models
For organisations weighing their options, the choice between SaaS, Raw Data, and On-Demand Reports (BizziRex) depends on frequency and internal capability.
Table 1: Comparative Approaches to Location Intelligence
Demonstrated Need in Real Estate & Planning
The "18-month valley of death" for micro-SaaS startups suggests that tools failing to deliver immediate value are quickly discarded. In contrast, the service-based delivery of data allows for higher flexibility.
Real estate professionals are moving away from "gut feeling" toward "location, data, intelligence". However, they often lack the time to become data experts. By outsourcing to BizziRex, these professionals can leverage Quadrant-level data granularity without the technical overhead. Saas subscription tend to be absorbed as a business overhead, whereas individual property reports, with published pricing can be a value add to a proposal or on-charged to a customer or project.
BizziRex is built on expert knowledge, by leading analyst. In the instance where more technical solutions are required, BizziRex has the option for custom requests, backed by the team who built the product. Highly specialised data scientists and analyst who can tackle the complex issues.
Conclusion: The Democratisation of Insight
The launch of BizziRex signals a maturing of the location intelligence market. We are moving away from a "one-size-fits-all" software era into an era of specialised access.
For heavy users, SaaS platforms remain essential. For data science teams, raw feeds are the gold standard. But for the vast middle ground—the leasing agents, the planners, and the operational managers—the future looks like BizziRex: fast, accessible, accurate, and human-interpreted.
By removing the friction of contracts and logins, BizziRex proves that you don't need to be a data scientist to make data-driven decisions. You just need the right partner to interpret the signal.
About the Author
Dr Nicholas Patorniti is the founder of UACS consulting – an urban analytics specialist consultancy services company operating for 10 years. He is a senior adjunct research fellow at Griffith University, Australia. Over 20years experience researching, developing and applying urban analytics methods helped identified this market gap and provided the ‘know-how’ to meet the market demand with BizziRex.
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