Digital Natives: LCCs still rule in online engagement
Piotr Spiewanowski flexponsive
September 1, 2015
Introduction
One innovation that low-cost carriers (LCCs) brought to the airline industry is a staunch focus on direct online sales, at a time when the established full-service carriers (FSCs) still relied largely on the Global Distribution Systems.
But strategy differences are narrowing, with Lufthansa looking to slap a surcharge on indirect bookings, and Ryanair opening up its seat inventory for third party sales partners.
What does this strategy shift mean for airline online engagement? Do LCCs have a towering lead in online visits, or did the legacy carriers catch up with their direct brand traffic?
As we discuss in the companion blog post to this note - Digital Natives: LCCs still rule in online engagement, Low Cost Carriers’ (LCC) lead in digital performance is unquestionable. However, a number of Full Service Carriers (FSC) already compete with the leading LCCs in attracting visitors to their websites.
Dataset: We use our dataset of 40 leading airlines, already introduced in our prior note.
Comments, questions, remarks or corrections? Don’t hesitate to get in touch: contact details here.
Airline Business Types
Based on inspection of the data, we classify airlines into four categories:
- Full Service Carriers: the flag carriers, also less kindly known as legacy carriers
- LCCs by birth: “real” LCCs established to or turned to the lowcost model at the early stage. This group includes also those lowcost airlines that have been purchased by an FSC group.
- LCC charters, includes airlines that combine scheduled operations with charter flights.
- Spin-off LCCs: low cost airlines established and owned by traditional airlines.
Descriptive Stats
Comparing the groups of FSC and LCCs by birth, it is clear that on average the FSC are still bigger, with 1.3 times the passenger volume in 2014. Despite the lower passenger volume the ‘real’ LCCs have marginally higher online engagement. The other two carrier categories are much smaller.
d<-t(summaryBy(annualTraffic + Passengers14 ~ Type2, data=dds, FUN=summary))[-1,]
#d<-t(summaryBy(annualTraffic + Passengers14 ~ Type2, data=dds, FUN=summary))[-1,]
colnames(d) <- c('Full Service Carrier', 'LCC by birth', 'LCC charter', 'spin-off LCC')
kable(d)| Full Service Carrier | LCC by birth | LCC charter | spin-off LCC | |
|---|---|---|---|---|
| annualTraffic.Min. | 2800000 | 8690000 | 4625000 | 4115000 |
| annualTraffic.1st Qu. | 32730000 | 24970000 | 5943000 | 4168000 |
| annualTraffic.Median | 64990000 | 48370000 | 6651000 | 4221000 |
| annualTraffic.Mean | 83440000 | 86700000 | 8489000 | 4221000 |
| annualTraffic.3rd Qu. | 119800000 | 96070000 | 10700000 | 4274000 |
| annualTraffic.Max. | 207900000 | 334500000 | 14520000 | 4327000 |
| Passengers14.Min. | 1600000 | 1800000 | 6700000 | 3200000 |
| Passengers14.1st Qu. | 17280000 | 7100000 | 7030000 | 5650000 |
| Passengers14.Median | 28170000 | 16000000 | 7800000 | 8100000 |
| Passengers14.Mean | 39250000 | 29730000 | 8026000 | 8100000 |
| Passengers14.3rd Qu. | 52280000 | 27850000 | 8100000 | 10550000 |
| Passengers14.Max. | 129200000 | 135800000 | 10500000 | 13000000 |
To explore the question of the “engagement gap” in more detail, we need to turn to a
Regression Model
We extend the airline traffic regression introduced in prior post with a dummy variable for airline type
reg3<-lm(log(annualTraffic) ~ log(Passengers14) +Type2, data=dds);
summary(reg3);##
## Call:
## lm(formula = log(annualTraffic) ~ log(Passengers14) + Type2,
## data = dds)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.95543 -0.28015 -0.01843 0.27301 1.06226
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.63268 1.25859 1.297 0.20304
## log(Passengers14) 0.94341 0.07362 12.815 8.9e-15 ***
## Type2LCC by birth 0.44490 0.17356 2.563 0.01482 *
## Type2LCC charter -0.75264 0.25988 -2.896 0.00647 **
## Type2spin-off LCC -1.16966 0.37595 -3.111 0.00370 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4866 on 35 degrees of freedom
## Multiple R-squared: 0.8831, Adjusted R-squared: 0.8697
## F-statistic: 66.1 on 4 and 35 DF, p-value: 8.003e-16Difference between FSCs and other carrier types
diffs <- t(t(c(paste(round(100*(exp(reg3[[1]][[c(3)]])-1), 2), "%", sep=""),paste(round(100*(exp(reg3[[1]][[c(4)]])-1), 2), "%", sep=""),paste(round(100*(exp(reg3[[1]][[c(5)]])-1), 2), "%", sep=""))))
rownames(diffs) <- c("LCC by birth","LCC charters","spin-off LCCs")
colnames(diffs)<-c("Difference relatively to FSC")
kable(diffs)| Difference relatively to FSC | |
|---|---|
| LCC by birth | 56.03% |
| LCC charters | -52.89% |
| spin-off LCCs | -68.95% |
What we can conclude from the regression:
- airline types are important to understanding traffic patterns: Adjusted R^2 jumps from 75% to 88%
- relative to FSC
- LCCs by birth are much stronger online. The estimate for difference in traffic between ‘real’ lcc and fsc is significant at 5%level (+56%).
- charter airlines have little online engagement (-53%).
- their low-cost daughters are also weaker online than FSC (-69%)
The results can be best seen on the plot below:
Plot: Airline Business Structure and Online Engagement
Appendix: Airline Business Model Classification
| Airline | Type2 | |
|---|---|---|
| AFL | Aeroflot | FULL SERVICE |
| KZR | Air Astana | FULL SERVICE |
| BER | Air Berlin | LCC by birth |
| ACA | Air Canada | FULL SERVICE |
| AEA | Air Europa | LCC charter |
| BTI | AirBaltic | LCC by birth |
| AZA | Alitalia | FULL SERVICE |
| AAL | American Airlines | FULL SERVICE |
| AUA | Austrian | FULL SERVICE |
| BRU | Belavia | FULL SERVICE |
| BAW | British Airways | FULL SERVICE |
| DAL | Delta | FULL SERVICE |
| EZY | easyJet | LCC by birth |
| UAE | Emirates | FULL SERVICE |
| BEE | flyBe | LCC by birth |
| TCX | FlyThomasCook | LCC charter |
| GWI | Germanwings | LCC by birth |
| HOP | Hop! | spin-off LCC |
| IBE | Iberia | FULL SERVICE |
| IBS | Iberia Express | spin-off LCC |
| EXS | Jet2 | LCC by birth |
| KLM | KLM | FULL SERVICE |
| DLH | Lufthansa | FULL SERVICE |
| MON | Monarch | LCC charter |
| NAX | Norwegian Air Shuttle | LCC by birth |
| PGT | Pegasus | LCC by birth |
| RYR | Polskie Linie Lotnicze LOT | FULL SERVICE |
| SAS | Ryanair | LCC by birth |
| SWA | SAS | FULL SERVICE |
| SWR | Southwest | LCC by birth |
| TOM | Swiss | FULL SERVICE |
| TRA | Thomson | LCC charter |
| TUI | Transavia | LCC by birth |
| THY | Tuifly | LCC charter |
| UAL | Turkish Airlines | FULL SERVICE |
| VRD | United | FULL SERVICE |
| VOE | Virgin America | LCC by birth |
| VLG | Volotea | LCC by birth |
| WZZ | Vueling | LCC by birth |
| LOT | Wizzair | LCC by birth |