Traffic Data Valuation from In-flight Passenger Connectivity

November 4, 2010
Principal Author: Furio Ciacci
Contributors: Curt LaMontagne, Brian Cimaglia


Airline executives regularly face adoption decisions for new technologies such as in-flight passenger Internet connectivity. Key decisions factors include timing, aspects of possible functionality to privilege, and marketing/sales of the ensuing services.

Often, the inability to base decisions on from available data and an understood framework results in too cautious or too generic approaches, which may prove problematic later.

By applying fareENOUGH’s proprietary quantitative methodology fQOM only to already available traffic and travel data, it is possible to obtain quantitative, readily actionable answers tailored to an individual airline and its customers.


From time to time, airline executives must consider technologies that although relatively untested in the market, have at least the potential to significantly affect their future returns. One of those now undergoing rapid adoption is airborne internet service, or more generally, In-flight Passenger-Ground Connectivity (IPGC). As with every new service, the decision relies on limited information. The outcomes of similar technologies adopted in the past are potentially relevant, but only as much as their relevant factors relate to critical factors of the new situation. As to earlier adoptions of the same technology, even within the same airline, the problem is compounded by perception biases of the outcome itself, and of the differences in relevant factors. The risk is that a technology adopted under faulty or unclear premises will also be inadequately marketed, and eventually underperform relative to its profitability potential like cabin seat power outlets, if not ultimately ending up in rejection like Connexion by Boeing.

How to get returns from the traffic data that is purchased from aviation data services, and from a carrier’s own travel data, is a perennially open question. Such data represents an option to add value through better decisions, but one that is often not exercised properly for lack of suitable ways to apply it to actual decisions.

fareENOUGH’s proprietary fQOM methodology solves both these dilemmas simultaneously, leveraging the investment in obtaining or maintaining data on one hand, and in the new functionality on the other, for a specific case. fQOM does that by identifying carrier- and passenger-specific parameters that are relevant to the evaluation of IPGC, and by finding our how those specific parameters modulate the relationship between performance metrics for the new functionality and measures of additional economic value that are affected. Unlike ad-hoc, conventional marketing studies that even requiring additional expense and time, offer limited systematic or quantitative application, fQOM provides reliable answers from information already inherent in the flight and passenger data available to aviation operators.

Figure 1 - Value vs. Selected Airline Parameters

Figure 1 - Value vs. Selected Airline Parameters

In the case of IPGC, fQOM distinguishes five contributors to carrier value:

  1. IPGC creates passenger savings via access to information for operations that would have to be done on the ground; Additionally, IPGC enables travel-related information exchange and operations involving the passenger, which in turns enables savings to:
  2. passenger, through delay avoidance;
  3. carrier, through fewer ground resources;
  4. carrier, through rebooking avoidance;
  5. offset by the negative savings (costs) of solution deployment.

While carrier savings and costs go directly to the bottom line, passenger savings must first be extracted as revenue. Although all contributors depend on implementation with the proper objectives, their importance depends to a large extent on the operations of the carrier where IPGC is installed, and on the installation’s performance targets. Figure 1 shows the effect of two carrier operating metrics on overall value potential.

Evaluating the Technology

Figure 2: Value vs. Selected Performance Measures

Figure 2: Value vs. Selected Performance Measures

fQOM considers several IPGC technology parameters as influencing the deploying carrier’s profit potential:

  • operation processing speed, relative to the ground;
  • sign-on delay, the time required to recognize a user;
  • speed of the ground link, defined as the amount of information that can be exchanged in a given time;
  • number of different device types that can be reached;
  • number of requests that can move through each aircraft installation simultaneously;
  • airborne equipment weight.
Figure 2 shows the relationship between overall value potential per aircraft, and two of these parameters.

Airline-Specific Implementation

For the purpose of understanding individual airline potential, fQOM was applied to 3 distinct airline types, differentiated by measures that relate to IPGC and can be extracted from traffic data.

Figure 3: Value for 3 Specific Airline Types

Figure 3: Value for 3 Specific Airline Types

Type A1 airlines have a relatively elaborate route structure, serving prevalently high-traffic endpoints relatively far apart, with a relatively low percentage of departures from any single airport. International legacy airlines with limited domestic markets tend to fit this type. Type A2 airlines serve a mix of high and low traffic endpoints, mostly within the same region, with a relatively homogeneous fleet. Large, newer operators in densely populated areas tend to fit this type. Type A3 airlines serve prevalently low-traffic, relatively closely-spaced airports. Regional airlines tend to fit this type.

While every airline has a different combination of relevant operating parameters, whatever its business model, for the purpose of this analysis, all necessary information is available from traffic data.

Passenger-Specific Marketing

Figure 4: Value for 3 Specific Itinerary Profiles

Figure 4: Value for 3 Specific Itinerary Profiles
Figure 5: Difference between Flights and Itineraries

Figure 5: Flights vs. Itineraries

Identifying the relevant passenger types through available metrics is essential to extracting value from the service provided in the form of additional revenues. Passengers are endlessly categorized on subjective, ad-hoc indicators (psychometric, socioeconomic, etc.), which involve additional expense to collect and maintain and are not necessarily useful. Although fQOM can incorporate those, in this case fQOM extracts all the possible relevant information only from objective, quantitative travel data available at least for each airline’s own passengers.

fQOM was applied to three itinerary profiles. Profile P1 has high shares of direct connections, and long connecting times between endpoints with high departure frequencies. Profile P3 has a low percentage of direct connections, short connecting times, and at least one low-frequency endpoint. Profile P2 is in-between the other two.

Although flights traffic and passenger itineraries have a lot in common, the two do not determine each other, as the simple example in Figure 5 shows.

Interpreting the Results

From the results as shown in Figure 3, the net benefit per aircraft of IPGC are generally positive, but with an order of magnitude difference between airline type. This is due predominantly to the passenger data access component over longer airborne stretches above 10,000 ft., even constrained by a passenger’s finite workday and constrained ground link speed. Schedule-related savings are proportionally the greatest for Type A3 carriers, which have shorter airborne passenger times but more daily arrivals. Overall, the returns on IPGC will be much faster for airlines close Type A1, which can get most of those returns by focusing on the infrastructure to enable non-travel-related passenger activity that would otherwise be possible only on the ground. Airlines close to Type A3 should be much more cautious, and probably would need IPGC to help reduce operating costs. That requires integrating passenger communications with the broader flight management and scheduling resources, implying that effective IPGC deployments at Type A3 airlines would lag those done elsewhere.

From the results shown by itinerary type, (Figure 4) it is clear that while current industry pricing is consistent with the general average of extractable passenger value, itinerary type heavily influences total value per passenger, especially involving the access to travel information. This indicates how to extract value more fully for significant additional returns. Also, the itinerary specifics to be used for pricing are instantly and reliably known.

Irrespectively of traffic and travel patterns, most of the immediate benefits are received first by the passenger. This means that charging passengers for IPGC is essential to retaining enough of the value created to justify deployment of an IPGC solution.

Actionable Results

fQOM gives airlines the ability to use their own passenger data and traffic data of other airlines to select and optimize onboard wireless capability, as well as benchmarking the benefits of their own solution relative to the industry. To travel technology providers, fQOM gives the ability to refine their capabilities in ways that match the specific requirements of an airline customer

Figure 6: Relative Value Added from Relative
Increases in Solution Performance Indicators

Figure 6: Relative Value Added from Relative Increases in Solution Performance Indicators

An airline is able to set the right balance of its solution’s performance to suit its own characteristics. For example, F6 shows the relative value added from relative increases in processing speed and ground link speed.

When the cost of acquiring and maintaining the additional performance is considered, at the return on $1 spent on faster transaction processing is almost 400 times that of $1 spent on greater ground link speed.

Within a specific airline, whatever other pricing basis may be available, in any case, eventual returns can be significantly improved further by pricing the service consistently with the itinerary, i.e., per flight hour with a minimum and a maximum, but with discounts for connections that are very long (more passenger alternatives) or very short (greater direct carrier savings).