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When most people hear ‘data governance,’ they think of bureaucracy, approval processes, and delays.
But what if governance could help teams move faster? What if it enabled a marketing team to launch a campaign in days instead of weeks, or allowed commercial teams to act on insights confidently? 
In our webinar, <a href="https://ca.vu/insights/cavu-data-webinar/">The Data Strategy Blueprint: Laying the Foundations for Commercial Growth</a>, Paris Bielby, Data Director at CAVU, and Jamal Karim, Lead Data Engineer at CAVU, shared how airports are building governance frameworks that enable speed and confidence rather than creating bottlenecks. 
CAVU: How do you build governance frameworks that enable faster decision-making? 
Paris: 
“When we talk about data governance, many people immediately think of rules, hard controls, and bureaucracy, but the most effective governance frameworks do the opposite: they enable teams to act quickly and confidently. Good governance is about creating clarity and trust, so decision-makers know exactly what data they can use, how it can be used, and that it’s reliable. 
At a high level, governance starts with defining clear ownership and accountability for data domains: who owns passenger flow data, who owns retail transaction data, who owns partner performance metrics. Secondly, it’s standardisation, definitions and metadata so everyone is speaking the same language. When teams trust that a metric is consistent across departments, they can make decisions faster because they’re not debating which version of the truth to use. 
Governance also includes policies for privacy, compliance, and security. This protects sensitive passenger data and commercially confidential partner information while still allowing the right people access for business decisions.
The key is to automate enforcement where possible and provide frameworks that guide behaviour rather than create bottlenecks. When governance is embedded in processes and tools, it becomes an enabler rather than a barrier. 
In practice, the result is that commercial teams launching a new promotion, or optimising passenger spend, don’t have to wait weeks to get approvals or clarify definitions. They can access trusted data immediately, understand constraints, and act, which is ultimately what governance should achieve: faster, safer decision-making at scale.”

CAVU: When are data governance programmes most effective?<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;201341983&quot;:0,&quot;335559738&quot;:180,&quot;335559739&quot;:180,&quot;335559740&quot;:360}"> 
Jamal: 
“Data governance works best when it’s embedded directly into the systems and workflows teams use every day. 
For a commercial team launching a new promotion, that might look like a catalogue of ‘approved’ datasets with consistent definitions, automated quality checks, and clear flags for any sensitive fields, like PII or partner-specific data. 
From an engineering perspective, least-privilege access is critical, not just for commercial users, but even within the data team. Role-based access controls and row-level security ensure that individuals only access the datasets they are authorised to work with, preventing accidental exposure of customer or partner data. 
Our automated data quality framework also plays a key role: it checks for missing or null values, validates data types and ranges, and flags anomalies before data reaches stakeholders. This way, teams can trust the data and make decisions confidently. 
On a day-to-day basis, good governance also means observability and transparency. Teams can see when data was last updated, the lineage of key metrics, and any exceptions identified by automated quality checks. This reduces manual reconciliation work and prevents delays caused by uncertainty around data integrity. 
Equally important is how we share data. Data governance requires that information is always shared in controlled, secure ways, not via email or ad-hoc files. We use methods such as SFTP with IP whitelisting, or secure platforms like Databricks Delta Share, ensuring that sensitive or confidential data only goes to authorised recipients in a fully auditable manner.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:1,&quot;335551620&quot;:1,&quot;335559685&quot;:0,&quot;335559737&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:200,&quot;335559740&quot;:360}"> 
For example, a marketing team launching a campaign to promote lounge access or fast-track services can immediately access approved datasets on historical parking, lounge, and fast-track bookings, and upcoming travel dates, all with consistent definitions, and only for customers who have explicitly consented to be contacted. This removes the need for manual validation or ad-hoc checks, allowing teams to segment customers confidently and act quickly. 
This data governance framework enables campaigns that previously took weeks to launch to go live in days, without compromising compliance or trust. Governance here becomes an enabler of speed, confidence, and commercial impact rather than a bottleneck.”

CAVU: How can airports work collaboratively with commercial partners and share data safely?<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;201341983&quot;:0,&quot;335559738&quot;:180,&quot;335559739&quot;:180,&quot;335559740&quot;:360}"> 
Paris: 
“Good collaboration in an airport environment starts with a shared understanding of purpose. Airports and their commercial partners ultimately want the same outcome: better passenger experiences and stronger commercial performance. When everyone is aligned on that common goal, collaboration becomes far more natural and far more productive. 
In practice, the strongest partnerships are built on clarity, consistency, control, and critically, the right people and processes to support them. 
Clarity means agreeing upfront on what data is being shared, why it’s being shared, and what value each party expects to gain. But it also means being clear about roles and responsibilities: who owns which decisions, who maintains which datasets, and who is accountable when something changes. Without that human clarity, even the best technical solution will struggle. 
Consistency comes from standardised data models, shared definitions, and repeatable processes so everyone is working from the same foundation. But consistencyis also cultural. It requires partners to show up with the same mindset: transparent, predictable, and willing to follow agreed ways of working. When people behave consistently, trust builds quickly. 
Control is about ensuring data is handled securely, ethically, and in line with contractual and regulatory requirements. But governance isn’t just a set of documents. It’sa process that needs to be lived: regular reviews, clear escalation paths, and a rhythm of communication that keeps everyone aligned and accountable. 
When it comes to commercial sensitivities, the key is designing collaboration models that protect competitive information while still enabling insight. That typically means role‑based access, data minimisation, and aggregation so partners only see what they need to operate effectively. 
It also means strong contractual frameworks, i.e. data‑sharing agreements, retention rules, and transparent auditability, so every partner knows the boundaries and feels confident operating within them. 
But the people side matters just as much. Partners need to feel that their data is respected, that their concerns are heard, and that the airport is a neutral steward rather than a competitor. When you create that environment through good communication, predictable processes, and a governance model everyone trusts, collaboration stops being a risk and becomes a genuine competitive advantage.”

CAVU: How does this partner collaboration work in practice from an engineering standpoint?<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;201341983&quot;:0,&quot;335559738&quot;:180,&quot;335559739&quot;:180,&quot;335559740&quot;:360}"> 
Jamal: 
“Good collaboration isn’t just about sharing data, it’s about doing so safely, responsibly, and in a way that scales. Airports often work with multiple commercial partners, each with different sensitivities around their data, and navigating that requires strong governance. 
Practically, this starts with knowing exactly what data we hold, where sensitive fields exist, and who should have access. We tag PII and partner-specific information,apply role-level security and least-privilege access, and ensure only authorised users can view it. Before anything goes live, we run thorough testing on pipelines, dashboards, and data-sharing workflows to confirm access rules are enforced and that sensitive data cannot leak. 
For example, when bringing new product streams online, such as Travel Insurance, we collaborate closely with partners from the start to understand their requirements, operational constraints, and compliance obligations. We design the data flows so that everyone knows exactly what will be shared, in what format, and with what frequency, ensuring partner trust while enabling the product to operate smoothly. 
For our standard reporting offerings, we listen to client needs and evolve our approach over time. Many clients require similar datasets but want them updated and accessible as frequently as possible. 
Rather than maintaining slow, bespoke SFTP exports, we are moving to a standardised, scalable sharing approach using Delta Sharing. This allows clients to access the data they need, as often as they need it, within a fully governed and auditable framework. 
The result is that airports and their partners can act on insights quickly and safely, without compromising trust or compliance. By combining close collaboration, clear definition of needs, and strong governance, we’re able to unlock real value for all parties.”

CAVU: What’s the first step airports should take when building a data-led strategy?<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;201341983&quot;:0,&quot;335559738&quot;:180,&quot;335559739&quot;:180,&quot;335559740&quot;:360}"> 
Paris: 
“For airports that are right at the beginning of their data journey, the best thing they can do in the next 30 days is pick one small, meaningful win and deliver it. Not a big strategy document, not a huge transformation programme, just one practical improvement that shows people what good looks like. It could be fixing a messy data feed, giving teams a single trusted number for something they argue about every day, or creating a simple dashboard that replaces a painful manual process. That early win builds belief, and belief is what gets the whole thing moving.” 
Jamal: 
“Making that first 30-day win happen is all about turning a business problem into an operational solution quickly. We start by working with stakeholders to identify the key metric, report, or process that’s causing the most friction. Then we map exactly where the underlying data lives, who owns it, and how it currently flows. 
That allows us to build a centralised pipeline into a warehouse or analytics platform, applying automated quality checks to ensure accuracy and completeness. We then surface it through a lightweight dashboard or report so teams have one trusted source of truth that they can use to make decisions.” 
<h2 data-start="1417" data-end="1486">Create scalable, secure data foundations. Watch the full webinar.</h2>
This article highlights only part of Paris and Jamal’s conversation.
In the full session, they also explore how to:
<ul data-start="1606" data-end="1970">
<li data-start="1606" data-end="1684">
Define what “good data” really looks like in complex commercial ecosystems
</li>
<li data-start="1685" data-end="1771">
Design cross-ecosystem data strategies that connect stakeholders and commerce data
</li>
<li data-start="1772" data-end="1817">
Build scalable data governance frameworks
</li>
<li data-start="1818" data-end="1909">
Move from fragmented systems to unified architectures that reduce silos and blind spots
</li>
<li data-start="1910" data-end="1970">
Enable faster, more confident commercial decision-making
</li>
</ul>
Watch the full webinar to learn how to turn your data into a strategy built for sustainable commercial growth.

Watch the Webinar

Paris Bielby, Data Director at CAVU, and Jamal Karim, Lead Data Engineer at CAVU, share how airports can build data governance frameworks.

Alina Grubnyak ZiQkhI7417A Unsplash

How to create effective data governance frameworks

For airports at different stages of data maturity, one of the most challenging questions is: where do we start? Should you focus on the areas with the biggest commercial impact, the easiest technical wins, or the data that’s causing the most operational pain? 
In our webinar, <a href="https://ca.vu/insights/cavu-data-webinar/">The Data Strategy Blueprint: Laying the Foundations for Commercial Growth</a>, Paris Bielby, Data Director at CAVU, and Jamal Karim, Lead Data Engineer at CAVU, shared a practical prioritisation framework geared towards helping airports make smarter decisions about which data silos to tackle first, and how to sequence work for maximum impact. 
CAVU: For airports at different stages of maturity, how do you prioritise which data silos to tackle first? 
Paris: 
“When you work with airports at very different stages of data maturity, the key is not to chase a single ‘right’ starting point; it’s to apply a consistent prioritisation framework that balances value, feasibility, and urgency. 
I usually look at three dimensions: 
<ol>
<li> Commercial Value</li>
</ol>
Where can data unlock the biggest financial impact — whether that’s improving retail conversion, optimising parking yield, or reducing leakage in airline billing? High‑value domains deserve attention, but only if the data foundations are strong enough to support meaningful insight. 
<ol start="2">
<li> Operational Pain</li>
</ol>
Some silos create daily friction: inaccurate flight data, inconsistent passenger numbers, or unreliable asset information. These are the areas where fixing the data unlocks immediate operational stability and builds trust in the wider programme. 
<ol start="3">
<li> Technical Readiness</li>
</ol>
Sometimes the smartest move is to start where the data is cleanest, most accessible, or easiest to integrate. Early wins build momentum, demonstrate credibility, and help secure buy‑in for the harder work that follows. 
The art is in balancing all three, not treating them as competing priorities. A high‑value domain that is technically impossible to fix today shouldn’t be first. Equally, an easy win with no business impact doesn’tmove the needle. 
A framework that works well is a Value–Feasibility Matrix: 
Value: commercial impact + operational impact 
Feasibility: data quality + system accessibility + stakeholder readiness 
Plot each data domain on that matrix. The top‑right quadrant (high value, high feasibility) becomes your starting point. The bottom‑right quadrant (high value, low feasibility) becomes your roadmap for investment. And the low‑value areas fall away naturally. 
To illustrate this with an example: one product that we have recently built and integrated into our software platform, <a href="https://ca.vu/platform/">Propel</a>, is Travel Insurance, which is sold for a suite of client sizes, from very small to multinational. 
This means that we can help all our clients grow whilst considering the ways that we can report this into their data infrastructure safely and securely.”

CAVU: Can you explain how this prioritisation framework was used to integrate travel insurance into Propel? 
Jamal: 
“From a delivery and engineering perspective, our focus was very much on prioritisation and sequencing, not trying to solve everything at once, but breaking the work into clear phases and creating a roadmap that would get the product live as quickly and safely as possible. 
We started by mapping exactly where the data needed for the Travel Insurance product was coming from: customer platforms, order systems, payment flows, and partner integrations. This helped us to understand what data was essential for the product to function versus what data was important for longer-term reporting and optimisation. That allowed us to split the work into clear streams and prioritise what was critical to bring the product online. 
The priority was enabling the core product flow: ingesting customer orders, validating transactions, and making sure we could provide the financial and operational data required by our insurance partner. That data had to be accurate, timely, and structured in a way that met partner requirements, because without that, the product couldn’t operate. 
Quality and governance were built into every step of this process. We implemented automated checks on the data being sent to partners to ensure completeness, accuracy, and consistency. We also designed governance processes so that every order is auditable, meaning we can track, trace, and reconcile all transactions end-to-end. This gives both internal teams and partners confidence in the integrity of the data being exchanged. 
Once that foundation was in place, we layered in reporting, ensuring our stakeholders from teams such as finance had access to reports that they required – giving them details of the performance of the product. 
So the prioritisation wasn’t abstract, it was very practical: first, enable the product to operate; second, ensure partner trust and financial integrity; and third, build the reporting and optimisation layers. That sequencing allowed us to deliver value quickly, while still building a robust, governed data foundation that the product can scale on.”

CAVU: What happens when data prioritisation goes wrong? 
Paris: 
“When data prioritisation goes wrong, it usually shows up in one of three ways. You spend months working on something technically complex that delivers little business value. Or you chase a high-value opportunity, but the data quality or systems aren’t ready, so the project stalls or delivers inaccurate results. 
In the worst case, you try to tackle everything simultaneously, spread your team too thin, and nothing gets finished properly. 
The framework we use prevents that by forcing honest conversations upfront. It makes trade-offs visible and helps everyone understand why certain work is happening now versus later. That shared understanding is just as important as the technical execution.” 
<h2 aria-level="2">Watch the full webinar and gain invaluable data expertise</h2>
This blog shares just part of Paris and Jamal’s conversation on how airports can take the first steps towards becoming data-driven. 
In the full webinar, they also discuss: 
<ul>
<li> How to build data governance frameworks that enable faster decision-making</li>
<li> Navigating commercial sensitivities when sharing partner data</li>
<li> What creates a truly data-driven culture in airport environments</li>
<li> The most common pitfalls mature airports should avoid as they scale</li>
</ul>

Paris Bielby, Data Director at CAVU, and Jamal Karim, Lead Data Engineer at CAVU, share a practical prioritisation framework to support smarter decisions about which data silos to tackle first, and how to sequence work for maximum impact.

Declan Sun C5 LlDVVeZ0 Unsplash

How airports should prioritise data projects: A tried-and-tested framework

Many airports today are sitting on vast amounts of data, from passenger flows and commercial transactions to flight operations and parking systems. But having data and being data-driven are two very different things. 
So, what does success look like when an airport sets out to become truly data-driven? And what separates the organisations that achieve it from those that struggle? 
In a recent webinar, Paris Bielby, Data Director at CAVU and Jamal Karim, Lead Data Engineer at CAVU, shared their insights on how airports can build data-driven cultures.
CAVU: When airports set out to become more data-driven, what does success look like? 
Paris: 
“When I think about an airport becoming truly data-driven, I see it as a fundamental shift in how decisions are made at every level. It’s not just about implementing technology or dashboards; it’s about creating a culture where data is central to how we think, plan, and act. Every team, such as commercial, operations, finance, marketing, and security, should be empowered to make informed decisions using reliable insights rather than gut instinct or anecdotal evidence. 
Success for a data-driven airport is when data is woven into everyday decision-making: 1. For commercial teams, it means understanding passenger behaviour and optimising inventory, retail and service offerings. 
<ol start="2">
<li> For operations, it means proactively managing flows, predicting congestion, and improving resource allocation.</li>
<li> For finance, it means forecasting revenue accurately and spotting trends early. It’s when each of these functions can confidently use data to make faster, better decisions.</li>
</ol>
Another hallmark of success is how questions and problems are defined. Being data-driven isn’t about collecting everything; it’s about being intentional. Which problems are most critical to solve? Which questions will deliver the highest impact for the airport, passengers, and partners? A successful organisation starts with those questions and aligns its data strategy around them, rather than starting with technology or the latest analytics trend. 
It also requires strong executive sponsorship. Data initiatives that succeed are supported from the top down; leadership invests in infrastructure, skills, governance, and platforms, and signals that using data is a core competency, not a nice-to-have. People need to see that data-driven decisions are rewarded and valued, and that the organisation is willing to change processes and roles to enable that culture. 
Finally, success isn’t just about internal decision-making; it’s about the value generated. This could be smarter commercial offers that increase revenue, operational improvements that enhance the passenger experience, or predictive insights that improve planning across the airport ecosystem. 
Essentially, it’s when the airport can demonstrably show that data is delivering measurable benefits, both in efficiency and revenue growth. 
So, in short, a data-driven airport is defined by culture, alignment to business outcomes, executive sponsorship, and the ability to translate insights into measurable impact.”

CAVU: What are the biggest blockers airports face, and how do you overcome them in practice? 
Jamal: 
“One of the first steps is understanding exactly where data is coming from &#8211; passenger systems, flight operations, commercial transactions, parking systems &#8211; and mapping how teams currently access it. 
One of the biggest blockers we see is <a href="https://ca.vu/insights/why-are-data-silos-problematic/">data silos</a>: marketing pulling numbers from one system, finance from another, operations from a third, all with slightly different definitions. That inconsistency erodes trust and slows decision-making. 
So practically, our focus is on creating a unified, governed way of bringing data into a central warehouse or analytics platform. That means mapping sources, defining ingestion patterns, ensuring data arrives on time, and preserving integrity throughout the pipeline. The goal is to give stakeholders a single, trusted view of the truth, whether they’re in finance, marketing, or commercial, so they can focus on solving problems rather than reconciling numbers. 
Trust is foundational. We build that through utilising a modern data platform, ensuring we have reliable ingestion pipelines, automated data-quality checks and can serve the data consistently. 
 knowing what data we hold, tagging sensitive fields, and controlling access appropriately and only when required. When teams trust the data and know it’s up-to-date, they’re far more willing to use it to drive decisions, build new products and essentially generate value. 
A practical example of this is how we provide client airports with access to data they often haven’t had visibility of before. From our central data warehouse, we deliver regularly refreshed reporting through tools like AWS QuickSight, giving airports a clear, consistent view of what’s happening across their commercial and operational estate. 
We also analyse patterns over time, for example, daily car-park arrivals, to identify seasonality, long-term trends, and relationships with external factors such as flight schedules. That insight not only supports day-to-day decision-making today, but also lays the groundwork for more advanced use cases like demand forecasting and predictive planning. 
So, in practice, success looks like this: reliable, governed data flowing consistently into a shared platform, trusted by teams across the airport, and actively used to make decisions or build products that deliver measurable value.”

CAVU: Why do so many data initiatives fail to achieve this vision? 
Paris: 
“The organisations that struggle often make one of a few common mistakes. They might invest heavily in technology without thinking about culture, buying the best analytics platform but not changing how teams work. Or they try to solve everything at once, creating sprawling programmes that lose focus and momentum. 
Sometimes the problem is misalignment. Leadership says data is important, but the incentive structures, ways of working, and decision-making processes don’t change. Or different parts of the organisation are solving the same problem in different ways, creating more silos instead of breaking them down. 
And without trust in the data, whether that’s because of poor quality, inconsistent definitions, or unclear governance, people simply won’t use it. They’ll fall back on instinct, anecdote, or whatever numbers they feel most comfortable with, even if those aren’t the most accurate.” 
<h2 aria-level="2">Watch the webinar in full and gain indispensable data insights </h2>
This blog is just a snapshot of the insights Paris and Jamal shared during our recent webinar on building data-driven airport cultures. 
In the full session, they explore: 
What ‘good data’ really looks like  
<ul>
<li aria-setsize="-1" data-leveltext="" data-font="Symbol" data-listid="2" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559683&quot;:0,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="1" data-aria-level="1">How to design cross-ecosystem data strategies that connect commerce data across multiple stakeholders </li>
</ul>
<ul>
<li aria-setsize="-1" data-leveltext="" data-font="Symbol" data-listid="2" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559683&quot;:0,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="2" data-aria-level="1">How to build robust data governance at scale  </li>
</ul>
<ul>
<li aria-setsize="-1" data-leveltext="" data-font="Symbol" data-listid="2" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559683&quot;:0,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="3" data-aria-level="1">The shift from fragmented systems to unified architectures that reduce silos and blind spots  </li>
</ul>
<ul>
<li aria-setsize="-1" data-leveltext="" data-font="Symbol" data-listid="2" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559683&quot;:0,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="4" data-aria-level="1">Frameworks that enable faster, more confident commercial decision-making  </li>
</ul>
Watch the full webinar and take the first step towards building data foundations for sustainable commercial growth.

Paris Bielby, Data Director at CAVU, and Jamal Karim, Lead Data Engineer at CAVU, give their thoughts on what a successful data setup looks like, common data challenges faced by airports, plus reasons why many data initiatives fail.

Pascal Meier UYiesSO4FiM Unsplash

What does it take for airports to become data-driven?

For car park operators and airports, data has become the foundation of commercial success. Yet despite collecting vast amounts of information across parking systems, booking platforms, payment gateways, and passenger touchpoints, many organisations find themselves unable to use this data effectively. 
The culprit? Data silos. 
When critical business information becomes trapped in disconnected systems, you&#8217;re not just facing a technical challenge. You&#8217;re limiting your ability to make informed pricing decisions, optimise capacity, understand customer behaviour, and ultimately maximise revenue. 
In this article, we’ll explore what data silos are, why they&#8217;re particularly problematic for car park and airport operations, and how you can overcome them to drive sustainable commercial growth.
<h2 aria-level="2">What are data silos? </h2>
Data silos are isolated pieces of information that exist within separate systems, departments, or platforms. This prevents seamless data sharing across your organisation. In simple terms, it&#8217;s when different parts of your business hold valuable data that others cannot easily access or use. 
For car park operators and airports, data silos commonly emerge between: 
<ul>
<li aria-setsize="-1" data-leveltext="" data-font="Symbol" data-listid="1" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="1" data-aria-level="1">Parking management systems and revenue platforms </li>
</ul>
<ul>
<li aria-setsize="-1" data-leveltext="" data-font="Symbol" data-listid="1" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="2" data-aria-level="1">Online booking engines and on-site payment terminals </li>
</ul>
<ul>
<li aria-setsize="-1" data-leveltext="" data-font="Symbol" data-listid="1" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="3" data-aria-level="1">Customer relationship management tools and operational databases </li>
</ul>
<ul>
<li aria-setsize="-1" data-leveltext="" data-font="Symbol" data-listid="1" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="4" data-aria-level="1">Marketing analytics and sales reporting systems </li>
</ul>
<ul>
<li aria-setsize="-1" data-leveltext="" data-font="Symbol" data-listid="1" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="5" data-aria-level="1">Multiple car park locations operating independently </li>
</ul>
When these systems fail to communicate effectively, you end up with fragmented datasets that tell incomplete stories. For instance, your parking operations team might see capacity trends, whilst your commercial team works with entirely different booking data, and your marketing department operates with a third set of customer insights. 
The result is an organisation rich in data but poor in actionable intelligence.

<h2 aria-level="2">What causes data silos in car park and airport operations? </h2>
Understanding why data silos develop is the first step towards eliminating them. In the car park and airport sectors, several factors contribute to fragmented data environments: 
<h3 aria-level="3">Legacy infrastructure and complex systems </h3>
Many car parks and airports operate with a patchwork of systems built up over years, sometimes decades. You might have inherited older parking management software, added modern booking platforms, integrated third-party payment processors, and used various analytics tools along the way. 
Each system was likely introduced to solve a specific problem at a particular time, often without consideration for how it would integrate with existing infrastructure. Such complications with technical aspects of connecting disparate systems with different data formats, APIs, and architectures create barriers to active information sharing. 
<h3 aria-level="3">Organisational structure and departmental ownership </h3>
Airport and car park operations typically involve multiple stakeholders with distinct responsibilities. Operations teams focus on capacity management and vehicle flow, commercial teams concentrate on pricing and revenue optimisation, while marketing departments track customer acquisition and retention. 
When different departments own different systems and datasets, information naturally becomes siloed. Teams may view their data as proprietary to their function rather than as an enterprise asset that should be shared across the organisation. 
<h3 aria-level="3">Rapid growth and expansion </h3>
As car park portfolios expand or airports add new terminals and facilities, data silos often multiply. Each new location or expansion might introduce additional systems without proper integration planning. 
Acquisitions can be particularly problematic. When one car park operator acquires another, merging incompatible systems and data structures becomes a significant challenge that many organisations defer, meaning no places are put in place to eradicate the data silos. 
<h3 aria-level="3">Resource constraints </h3>
Integrating systems and breaking down data silos requires investment in technology, expertise, and time. Many organisations struggle to justify the upfront costs, particularly when existing systems appear to &#8220;work&#8221; in isolation, even if they prevent optimal decision-making. 
The lack of in-house data engineering capabilities can also mean organisations rely on external vendors for each system, with limited ability to create unified data architectures.

<h2 aria-level="2">Why are data silos problematic?</h2>
Regardless of the cause, data silos directly impact your bottom line and competitive position. 
Here&#8217;s how fragmented data hinders commercial performance in the parking and airport sectors: 
<h3 aria-level="3">Suboptimal pricing strategies </h3>
<a href="https://ca.vu/insights/why-is-dynamic-pricing-in-car-parks-key-to-boosting-revenue/">Dynamic pricing</a> is crucial for maximising car park and airport parking revenue. However, effective pricing requires comprehensive data about historical demand patterns, competitor pricing, seasonal variations, local events, flight schedules, and customer behaviour. 
When this information lives in separate systems, you can’t develop sophisticated pricing models. You might be underpricing during peak demand periods or overpricing when you need to drive volume, missing significant revenue opportunities either way. 
Without integrated data, you&#8217;re essentially pricing blind, relying on outdated rules or gut instinct rather than evidence-based strategies informed by complete market intelligence. 
<h3 aria-level="3">Inefficient capacity management </h3>
Data silos prevent real-time visibility across your entire parking inventory. If your booking system doesn&#8217;t communicate effectively with your access control systems, you risk overbooking or underutilising capacity. 
For airports managing multiple car parks across different terminals and both on-site and off-site locations, fragmented data makes it nearly impossible to optimise inventory allocation. You might have empty spaces in one location whilst turning away customers at another, purely because you lack integrated capacity insights. 
<h3 aria-level="3">Missed cross-selling and upselling opportunities </h3>
Modern passengers expect seamless travel experiences and value convenience. They&#8217;re willing to pay for additional services like lounge access, fast-track security,  or premium parking locations. 
However, if your parking booking data sits separately from your ancillary product systems, you can&#8217;t effectively offer complementary services at the right moments in the customer journey. These missed cross-selling opportunities represent substantial foregone revenue, particularly when you consider the lifetime value of repeat customers. 
<h3 aria-level="3">Incomplete customer understanding </h3>
Understanding your customers is fundamental to commercial success. Which segments are most profitable? What booking patterns predict lifetime value? How do different customer types respond to pricing changes or promotional offers? 
Data silos negatively impact your customer view. Your booking system might know purchase history, your payment gateway holds transaction data, your marketing platform tracks email engagement, and your operational systems record actual usage patterns. None of these provides the complete picture you need to make strategic decisions about customer acquisition, retention, and development. 
<h3 aria-level="3">Duplicated efforts and operational inefficiency </h3>
When data doesn&#8217;t flow freely between systems, teams spend valuable time on manual data reconciliation. Finance teams might manually merge reports from multiple sources. Commercial analysts export data from various platforms into spreadsheets to create unified views. Marketing teams struggle to segment customers effectively without complete profiles. 
This wastes resources that could be better used on strategic initiatives. It also introduces human error into your data, further compromising data quality and the reliability of insights derived from it. 
<h3 aria-level="3">Slower decision-making </h3>
In dynamic markets, timing matters. Car parks and airports face rapidly changing conditions: unexpected events that drive demand spikes, competitor price changes, seasonal variations, and evolving customer preferences. 
Data silos slow decision-making because stakeholders lack immediate access to comprehensive information. By the time data is manually gathered, consolidated, and analysed, the opportunity may have passed. Your competitors operating with integrated data systems can react faster and capture market advantage. 
<h3 aria-level="3">Regulatory and compliance risks </h3>
Airports and car parks handle sensitive customer data subject to regulations like GDPR. When customer information is scattered across multiple systems, maintaining consistent security controls, managing data subject access requests, and ensuring compliance becomes significantly more complex and risky. 
Data silos make it difficult to track where customer data resides, who has access to it, and whether it&#8217;s being handled appropriately, potentially exposing you to regulatory penalties and reputational damage.

<h2 aria-level="2">Build data foundations and drive your commercial growth </h2>
Breaking down data silos isn&#8217;t a one-off project. It&#8217;s an ongoing commitment to data-driven operations that continuously evolve as your business grows and technology advances. 
The commercial benefits are substantial: better pricing strategies that maximise revenue, efficient capacity utilisation that reduces waste, deeper customer understanding that drives loyalty and lifetime value, faster decision-making that captures competitive advantage, and operational efficiencies that improve margins. 
For car park operators and airports, overcoming data silos means transforming from organisations drowning in disconnected data to agile businesses that leverage comprehensive intelligence to drive sustainable commercial growth. 
<a href="https://ca.vu/platform/">Propel, our advanced ecommerce platform</a> provides the technological foundation for eliminating data silos, with integrated booking, pricing, and analytics capabilities designed specifically for parking and airport operations. 
By consolidating your data ecosystem, you gain the insights needed to make confident commercial decisions whilst delivering seamless customer experiences.

Learn More About Propel

<h2 aria-level="3">Gain expert-led insights with our data webinar  </h2>
To dive deeper into building robust data strategies that support commercial growth, watch our webinar, &#8216;<a href="https://ca.vu/insights/cavu-data-webinar/">The Data Strategy Blueprint: Laying the Foundation for Commercial Growth&#8217;</a>.
Paris Bielby, Data Director at CAVU and Jamal Karim, Lead Data Engineer at CAVU, share their insights on how to:
You’ll learn how to: 
<ul>
<li aria-setsize="-1" data-leveltext="" data-font="Symbol" data-listid="3" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="1" data-aria-level="1">Identify what ‘good data’ really looks like </li>
</ul>
<ul>
<li aria-setsize="-1" data-leveltext="" data-font="Symbol" data-listid="3" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="2" data-aria-level="1">Design cross-ecosystem data strategies that connect commerce data across multiple stakeholders </li>
</ul>
<ul>
<li aria-setsize="-1" data-leveltext="" data-font="Symbol" data-listid="3" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="3" data-aria-level="1">Build robust data governance at scale </li>
</ul>
<ul>
<li aria-setsize="-1" data-leveltext="" data-font="Symbol" data-listid="3" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="4" data-aria-level="1">Move from fragmented systems to unified architectures that reduce silos and blind spots </li>
</ul>
<ul>
<li aria-setsize="-1" data-leveltext="" data-font="Symbol" data-listid="3" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="5" data-aria-level="1">Create frameworks that enable faster, more confident commercial decision-making </li>
</ul>

Learn everything you need to know about data silos, including what they are, why they materialise, and most importantly, how to prevent them.

Stephen Dawson QwtCeJ5cLYs Unsplash

Why are data silos problematic for airports and car parks?

Whether you operate on-site airport parking, manage an off-site car park, or oversee commercial operations at an airport, understanding your customers isn’t just about tracking bookings or counting vehicles.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:200,&quot;335559740&quot;:360}"> 
In 2026, data plays a critical role in delivering true customer intelligence. By connecting the right data points, organisations can uncover patterns, make better decisions, and take targeted actions that drive revenue across the entire passenger journey, from <a href="https://ca.vu/insights/5-ways-digital-integration-will-transform-pre-trip-in-2026/">pre-trip</a> and <a href="https://ca.vu/insights/real-time-data-airport-experiences/">in-airport</a> to <a href="https://ca.vu/insights/four-destination-onward-travel-opportunities/">in-destination and onward travel</a>.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:200,&quot;335559740&quot;:360}"> 
In this article, we’ll highlight eight critical data points that consistently deliver measurable results, and more importantly, exactly how to use them.

<h3>1) Booking behaviour and lead time patterns</h3>
The window between when a customer books and when they need your service reveals who to target and when, enabling you to provide a <a href="https://ca.vu/insights/personalised-travel/">personalised travel experience</a>. For example, business travellers booking within 7 to 14 days need different messaging than leisure travellers booking months ahead.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
Use this data to build automated email sequences triggered by booking windows. Someone who just booked a flight four months out should receive a parking offer within 24 hours, emphasising early-bird discounts and long-stay value. Likewise, that same person should get a reminder 14 days before travel with fast-track and lounge upsells.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
A business traveller booking two days out needs immediate confirmation of availability and premium options, not discounts. Industry data shows pre-booking converts at 3 to 4 times the rate of day-of sales, but only if you reach customers while they’re still planning. Build your marketing automation around these windows and track conversion by segment.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
If your leisure conversion rate is below 12%, your messaging or pricing is wrong. If business travellers aren’t converting above 18%, you’re not emphasising convenience strongly enough.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
<h3>2) Utilisation patterns and demand forecasting</h3>
Utilisation data tells you when to raise prices and when to offer your customers a discount. Track daily occupancy rates over at least 12 months to identify patterns.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
If your airport car park hits 85% capacity every summer weekend, you’re leaving money on the table by not implementing <a href="https://ca.vu/insights/why-is-dynamic-pricing-in-car-parks-key-to-boosting-revenue/">dynamic pricing</a>. Conversely, if your data reveals Tuesday mornings in February consistently run at 40% occupancy, that’s when you should test aggressive discounts for corporate customers or run flash sales.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
Set your system to increase prices automatically when forecast occupancy exceeds 70% for a given date, and discount when it falls below 50%. Many operators see 15 to 25% revenue increases simply by getting pricing aligned with actual demand patterns. But this requires clean historical data and the ability to predict accurately.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
If your forecasts are consistently off by more than 10%, your underlying data has quality issues that need fixing before any pricing strategy will work. Analyse forecast accuracy monthly and investigate when actual performance deviates significantly from the prediction.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}">

<h3>3) Channel performance and customer acquisition cost</h3>
Every booking channel has a different cost and value profile, but most operators only look at volume.
Calculate true revenue per booking after commissions, processing fees, and marketing costs for every channel. You might discover that bookings from aggregator platforms bring high volume but net 30% less revenue than direct bookings, and those customers rebook at half the rate.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
This intelligence should drive specific resource allocation decisions. If direct bookings deliver £8 more profit per transaction and 40% higher rebooking rates, invest in SEO, paid search for branded terms, and email remarketing to previous customers. Reduce or eliminate discounting on aggregator platforms where customers show low loyalty. Track channel performance monthly and set clear targets for direct booking percentage.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
Leading operators aim for 60 to 70% direct bookings, because every shift from third-party to direct channel typically adds 15 to 20% to net margin. If you’re below 50% direct, you have a channel dependency problem that’s costing you significant revenue. Build a 90-day plan to shift 10% of volume from your most expensive channel to direct, and measure progress weekly.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
<h3>4) Customer lifetime value and retention economics</h3>
Understanding which customers are worth retaining should shape your marketing investment decisions.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:240,&quot;335559740&quot;:360}"> 
Start by calculating lifetime value by segment: average booking value multiplied by booking frequency over 24 months. Most operators discover that the top 20% of customers generate 60 to 70% of total revenue. These high-value customers justify dedicated retention programmes.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:240,&quot;335559740&quot;:360}"> 
Set up automated win-back campaigns for customers who have booked two or more times but have not returned within six months. Incentivise their third booking with exclusive early access to sales or a targeted discount.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:240,&quot;335559740&quot;:360}"> 
Track reactivation rates and compare the ROI of retention spend versus acquisition spend. Retaining an existing customer typically costs one-fifth of acquiring a new one, yet many operators still spend up to ten times more on acquisition. Use your data to rebalance budgets accordingly.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:240,&quot;335559740&quot;:360}"> 
For customers in their first 90 days post-booking, implement a welcome series that builds loyalty and encourages repeat bookings. Include practical travel tips, reminders about your services, and a next-booking incentive.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:240,&quot;335559740&quot;:360}"> 
When executed well, retention serves as a key growth lever. Operators with strong retention programmes typically see rebooking rates increase by 20 to 30% within 12 months, making retention one of the fastest and most cost-effective ways to drive sustainable revenue growth.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:1,&quot;335551620&quot;:1,&quot;335559685&quot;:0,&quot;335559737&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:360}">

<h3>5) Ancillary attachment rates and bundling optimisation</h3>
Travel insurance, fast track, and lounges are high-margin revenue, but only if you optimise presentation and timing.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
Track attachment rates by product, booking channel, and customer segment. If insurance attaches at 8% when presented on the payment page but 22% when offered immediately after parking selection, move it earlier in the journey. Test different price points and bundle configurations monthly.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
Similarly, a parking plus insurance bundle priced at £42 might convert better than selling parking at £35 and insurance at £9 separately, even though the bundle is £2 cheaper. Oftentimes, the psychology of bundling often outperforms the maths. For airport parking operators, analyse which flights or routes show the highest insurance attachment and create targeted pre-departure campaigns for similar bookings. If families flying to Spain convert insurance at 35% but business travellers to Frankfurt convert at 11%, stop wasting marketing budget promoting insurance to the wrong segment.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
Use your data to focus offers where they’ll convert. Even a 5-percentage-point improvement in attachment rate can add tens of thousands in annual revenue.
<h3>6) Campaign performance and marketing attribution</h3>
Most operators run campaigns but struggle to prove what works. Track every campaign with unique codes or UTM parameters and measure three metrics: conversion rate, revenue per booking, and customer quality (rebooking rate).<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
A flash sale that drives 200 bookings at £25 average looks successful until you realise those customers never return, and you just trained them to wait for discounts. Compare this to a targeted campaign to previouscustomers that generates 80 bookings at £35 average with 45% rebooking within 12 months. The second campaign is far more valuable despite lower absolute volume.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
Use this insight to build a testing framework. Every month, run one control campaign (proven approach) and one test (new messaging, offer, or audience). Measure performance after 30 days and after 90 days to understand both immediate conversion and long-term value. Kill campaigns that underperform on customer quality, even if volume looks good. Operators who embrace rigorous testing improve campaign ROI by 40 to 60% within a year because they stop repeating ineffective tactics and double down on what actually drives profitable growth.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}">

<h3>7) Product and pricing sensitivity analysis</h3>
Understanding price elasticity for different products and customer segments prevents you from leaving money on the table or pricing yourself out of the market.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
Test pricing systematically by making small changes (5 to 10%) and measuring conversion impact over 30-day windows. You might discover that premium covered parking can sustain a 15% price increase with only 3% volume decline, generating immediate margin improvement.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
Meanwhile, economy parking might be highly price-sensitive, where a 10% increase causes 18% volume drop and a net revenue decline. Use these insights to set pricing rules that maximise revenue per available space.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
During peak demand, increase premium product pricing aggressively while holding economy pricing steady to capture price-insensitive customers without losing volume at the entry level. Conversely, during low-demand periods, discount selectively in segments where you’ve proven that elasticity is high. The key is moving beyond gut-feel pricing to data-driven decisions. <span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
Track revenue per space daily and investigate any week where it drops below your rolling 12-week average. Usually, this indicates either a pricing error or a capacity management issue that needs to be addressed.
<h3>8) Operational integration points driving commercial decisions</h3>
Commercial performance doesn’t exist separately from operations. For airport parking, flight schedule changes, delays, or cancellations directly impact occupancy and revenue.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
Build alerts that trigger when flight schedules shift significantly. If three major flights get cancelled, you need to immediately adjust pricing for those dates and potentially release inventory that was being held.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
Similarly, if a new route launches with strong load factors, increase parking pricing for those travel dates before demand spikes. Off-site operators should integrate event calendars into their booking systems and set automated pricing rules. For example, if a major sporting event is announced whereby more travellers will be using your airport, pricing should increase automatically for those dates.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
Track the correlation between external factors (weather, local events, school holidays) and your booking patterns. This reveals opportunities for proactive marketing. If historical data shows that rainy weather forecasts drive 25% more airport parking bookings as people avoid public transport, set up weather-triggered email campaigns promoting covered parking.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
Operators who integrate operational and commercial data forecast demand with 30 to 40% better accuracy, allowing them to optimise pricing, staffing, and marketing spend with confidence rather than guesswork.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
Data points only matter if they change what you do. Every insight in this article should trigger a specific action: a pricing change, a campaign adjustment, a process improvement, or a resource reallocation.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}"> 
The operators who win aren’t those with the most data. They’re the ones who use data to make faster, better decisions than their competitors. Start with one data point, take one action, and measure the result. Then move to the next. This is how you build a genuinely data-driven operation.<span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:400,&quot;335559740&quot;:360}">

<h3>Lay the foundation for a data-led approach with our upcoming webinar </h3>
Watch our webinar, <a href="https://signup.ca.vu/the-data-strategy-webinar/?_gl=1*sxfj4t*_ga*NzIwNTc0MjUuMTc2MDk2ODA3OQ..*_ga_QDM2BXW96D*czE3NzAwNDc0MDkkbzE2OCRnMSR0MTc3MDA0NzQxNyRqNTIkbDAkaDA.">‘The Data Strategy Blueprint: Laying the Foundations for Commercial Growth’</a>, featuring Paris Bielby, Data Director at CAVU, and Jamal Karim, Lead Data Engineer at CAVU.
You’ll learn how to: 
<ul>
<li aria-setsize="-1" data-leveltext="" data-font="Symbol" data-listid="3" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="1" data-aria-level="1">Identify what ‘good data’ really looks like</li>
<li aria-setsize="-1" data-leveltext="" data-font="Symbol" data-listid="3" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="1" data-aria-level="1">Design cross-ecosystem data strategies that connect commerce data across multiple stakeholders</li>
<li aria-setsize="-1" data-leveltext="" data-font="Symbol" data-listid="3" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="1" data-aria-level="1">Build robust data governance at scale</li>
<li aria-setsize="-1" data-leveltext="" data-font="Symbol" data-listid="3" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="1" data-aria-level="1">Move from fragmented systems to unified architectures that reduce silos and blind spots</li>
<li aria-setsize="-1" data-leveltext="" data-font="Symbol" data-listid="3" data-list-defn-props="{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}" data-aria-posinset="1" data-aria-level="1">Create frameworks that enable faster, more confident commercial decision-making </li>
</ul>

Explore eight essential data points you need to be aware of that will improve your understanding of your customers and enable informed, data-driven commercial decisions.

Jon Tyson XZgRKEwuXl4 Unsplash

8 unmissable data points that will transform your customer understanding

The in-airport experience is where expectations either hold up or fall apart. Passengers arrive with preconceptions shaped by previous experiences, online information, and pre-bookings. The gap between those expectations and terminal reality determines whether passengers feel confident and ready to spend or stressed and focused solely on reaching their gate. 
For years, airports have lacked a clear, shared view of information. They know broadly what&#8217;s happening across the terminal, such as queue lengths and gate changes, but passengers don&#8217;t. This creates uncertainty, hindering both satisfaction and commercial performance. Stressed passengers rush through terminals, bypassing retail and food outlets, making rushed decisions or avoiding them entirely. 
Real-time data changes this dynamic. When passengers access accurate, current information, they make better decisions, move confidently, and engage more readily with commercial opportunities. When airports have real-time visibility into passenger behaviour and terminal conditions, they respond proactively, optimising both operations and revenue. 
The airports that will excel in 2026 recognise real-time data as a key part of their strategy, transforming the entire in-terminal experience.

<h2 aria-level="2">Real-time information transforms passenger confidence and spending </h2>
Walk through most terminals, and you&#8217;ll see passengers constantly checking phones, seeking information on gate announcements, security waiting times, and so forth. 
Without accurate answers, passengers adopt cautious approaches, arriving at gates far earlier than necessary and missing opportunities to engage with airport services. Traditional responses, static signage and periodic announcements can&#8217;t adapt to changing conditions. When security queues suddenly lengthen or gate changes create confusion, static information actively misleads passengers and erodes trust. 
Real-time data infrastructure enables a different approach. Digital displays show current security wait times updated continuously based on actual throughput. Mobile apps send gate change notifications before passengers see them on boards. Interactive wayfinding routes passengers around congestion or towards less busy security lanes. 
The impact is significant. When passengers trust the information they receive, they feel more in control. That control reduces anxiety, and reduced anxiety changes spending behaviour. Research shows that for every 10 minutes passengers spend in security queues, their retail spending drops by 30%. Passengers who know they have 40 minutes until boarding and that security takes 10 minutes behave very differently from those uncertain whether they have time to stop. 
This has a key impact on commercial performance. J.D. Power research indicates passengers who are &#8220;delighted&#8221; with their airport experience spend an average of $44 in the terminal, compared to just $29 spent by those who say they’re disappointed, a 52% difference directly tied to passenger satisfaction. 
For smaller airports, real-time systems can seem prohibitive, but the investment increasingly pays for itself through stronger commercial performance and better operational efficiency. Technology costs have fallen sharply, making basic implementations achievable even on tight budgets. Starting with high-impact areas such as security wait times delivers clear benefits while laying the groundwork for wider deployment.

<h2 aria-level="2">Turning browsing into commercial engagement </h2>
Dwell time, the time spent in the terminal after passing through security, has always been commercially valuable, but airports have traditionally treated it passively. <a href="https://ca.vu/insights/non-aeronautical-revenue-what-it-is-why-its-essential-and-how-it-boosts-airports-earnings/">Non-aeronautical revenues</a> now account for approximately 40% of total airport income globally, with retail contributing around 30% of this revenue stream. Yet many airports leave significant value on the table through passive approaches where passengers are left to wander and browse. 
Real-time data enables airports to move from passive to active dwell time management. Instead of hoping passengers stumble across opportunities, airports can actively guide them based on current conditions and individual context. 
Consider a passenger who cleared security with 45 minutes until boarding. Real-time systems identify their location, understand remaining time, know previous purchases, and recognise that their gate is in a different terminal section. Rather than letting them wander, the system proactively suggests relevant retail or food options along their route, perhaps offering time-limited promotions to create urgency. 
This <a href="https://ca.vu/insights/data-driven-personalisation/">personalisation</a> requires integrating multiple data sources: flight information systems, positioning data, CRM systems, and point-of-sale data. When these work together in real-time, the result is contextually relevant prompts that feel helpful rather than intrusive. 
The commercial impact is measurable. Airports implementing intelligent dwell time management consistently see increased conversion rates and higher transaction values, not through pushing passengers harder but by making it easier to find what they want when they want it. 
The key is respecting passenger intent. Data should be used to deliver a helpful, memorable experience, rather than being used to bombard passengers with untargeted messaging. A passenger rushing to make a tight connection needs the fastest route to their gate, not retail suggestions. Real-time systems should recognise these contexts and adjust accordingly.

<h2 aria-level="2">Dynamic wayfinding drives satisfaction and revenue </h2>
Real-time data enables intelligent wayfinding that adapts to passenger needs and current conditions. Digital systems provide turn-by-turn directions customised to mobility needs, language preferences, and time constraints. More importantly, they route passengers dynamically based on terminal conditions. 
If one route is congested with passengers from a flight that’s recently landed, the system suggests alternatives. If construction blocks a corridor, directions update automatically. If a passenger with limited mobility needs to reach a distant gate, the system routes them past wheelchair assistance points. 
This dynamic routing creates commercial opportunities. When airports understand passenger flows in real-time, they guide traffic towards or away from retail areas based on capacity. A quiet café benefits from increased foot traffic, whilst an overcrowded retail zone gets bypassed to improve the overall experience.

<h2 aria-level="2">Live insights unlock revenue during delays and disruptions </h2>
Real-time data fundamentally changes how airports approach commercial operations. Traditional planning relies on historical patterns and broad assumptions. Real-time insights enable dynamic commercial optimisation responding to current conditions. 
When airports have live visibility into passenger volumes, demographics, dwell time, and behaviour patterns, they make informed decisions, maximising revenue. A gate change concentrating passengers in a quiet terminal section creates opportunities to activate nearby retail through targeted promotions. A delay extending dwell time allows food outlets to adjust staffing and inventory to meet increased demand. 
Consider flight delays, which can create unexpected passenger concentrations and extended dwell times. Traditional approaches let this play out. Real-time systems, however, enable a proactive response: they identify affected passengers, determine who has time for a lounge versus grab-and-go options, and send targeted messages about nearby outlets, including current wait times and relevant promotions.
The commercial uplift is substantial. Airports implementing real-time commercial optimisation consistently report double-digit increases in food and beverage revenue during irregular operations. 
Industry data shows that relaxed, happy travellers spend 7% more on retail and 10% more on duty-free than stressed passengers. This uplift comes from better connecting travellers who have time to spend with outlets that have the capacity to serve them.

<h2 aria-level="2">Real-time operations address staffing constraints and efficiency </h2>
Real-time operational data enables airports to identify and respond to issues before they escalate. Security queue management provides a clear example. Without real-time visibility, airports rely on staffing patterns based on historical averages, often meaning over-staffing during quiet periods and under-staffing when unexpected volumes arrive. Real-time queue monitoring enables dynamic staff deployment, moving resources where needed most and reducing both wait times and labour costs. 
According to IATA&#8217;s Global Passenger Survey, 70% of passengers expect to reach their gate within 30 minutes when travelling with carry-on luggage, while 74% expect no more than 45 minutes with checked baggage. Real-time systems help airports to consistently meet these expectations. 
For airports struggling with staff shortages, real-time operational data becomes critical. When resources are constrained, using them intelligently based on real-time need rather than historical patterns can partially offset capacity limitations, maximising the effectiveness of available resources.

<h2 aria-level="2">Integration and strategy matter more than technology alone </h2>
None of these applications exists in isolation. The power of real-time data comes from integration: connecting passenger journey data with operational systems, commercial platforms, and communication channels. 
Building this data foundation requires intentional strategy. It&#8217;s not enough to deploy more sensors or implement new systems. Airports need to think carefully about what data matters, how systems will connect, how insights will be generated, and most importantly, how those insights will inform action. 
The good news is that building real-time data capability doesn&#8217;t require replacing entire technology stacks. Many airports already have valuable data sources; the opportunity lies in connecting them more effectively and extracting actionable insights. 
<h2 aria-level="2">Unlock expert insights and start building your data-driven strategy </h2>
The airports that will lead in 2026 treat real-time data not as a future aspiration but as a priority in their existing strategy. Passenger expectations continue rising, shaped by digital experiences in other industries where real-time information and personalised engagement are standard. 
Real-time data reduces passenger stress, enabling more confident movement and greater commercial engagement. It enables operational efficiency, improving both experience and cost performance. It allows airports to maximise dwell time revenue by understanding and responding to passenger needs in the moment. 
Ready to identify where your airport can capture the biggest opportunities? Our infographic, <a href="https://ca.vu/insights/mapping-the-future-of-travel-experiences-infographic/">‘Mapping the future of travel experiences’</a>, highlights real-time data applications across the entire passenger journey, whilst our upcoming webinar delivers practical frameworks for building the data foundation that drives commercial growth. 
<a href="https://ca.vu/insights/mapping-the-future-of-travel-experiences-infographic/">Download your copy</a> and explore opportunities across every stage of the passenger journey, from pre-trip through to post-journey engagement. Discover where leading airports are focusing their efforts to meet evolving passenger needs and unlock new commercial potential.

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Plus, join our upcoming webinar, <a href="https://signup.ca.vu/the-data-strategy-webinar/?_gl=1*x8s2oe*_ga*NzIwNTc0MjUuMTc2MDk2ODA3OQ..*_ga_QDM2BXW96D*czE3Njg0MTE5MDckbzEzNyRnMSR0MTc2ODQxNDU0OCRqNTYkbDAkaDA.">‘The Data Strategy Blueprint: Laying the Foundations for Commercial Growth’</a>, featuring Paris Bielby, Data Director at CAVU, and Jamal Karim, Lead Data Engineer at CAVU, on Wednesday, 18 March 2026. 
You’ll learn how to define what “good data” really looks like, design cross-ecosystem strategies, build strong data governance, and enable faster, evidence-based commercial decisions. 
<a href="https://signup.ca.vu/the-data-strategy-webinar/?_gl=1*x8s2oe*_ga*NzIwNTc0MjUuMTc2MDk2ODA3OQ..*_ga_QDM2BXW96D*czE3Njg0MTE5MDckbzEzNyRnMSR0MTc2ODQxNDU0OCRqNTYkbDAkaDA.https://signup.ca.vu/the-data-strategy-webinar/?_gl=1*x8s2oe*_ga*NzIwNTc0MjUuMTc2MDk2ODA3OQ..*_ga_QDM2BXW96D*czE3Njg0MTE5MDckbzEzNyRnMSR0MTc2ODQxNDU0OCRqNTYkbDAkaDA.">Register now</a>, and we’ll email you a recording packed with actionable insights.

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Learn how leading airports use live insights to reduce stress and maximise passenger spend.

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