Ai Editorial: Overcoming gaping holes in data strategy for ascertaining buying journey

First Published on 17th January, 2018

Ai Editorial: Constant refining of a core data asset, plus embracing latest developments in the ad tech arena is must as airlines attempt to understand the planning and buying journey of travellers, writes Ai’s Ritesh Gupta


Be it for managing data from disparate sources or multiple devices and channels or avoiding siloed device-graph data, airlines need to make continuous progress in order to attain a single view of the traveller.

The complexities associated with a travel-related buy are tough to handle, and data can help in understanding a prospective traveller’s interest, intent and conversion behavior across multiple devices.

We assess 4 key areas that demand attention on a regular basis:

1.     Look beyond the digital side of the traveller: The importance of cookies, mobile device IDs, email addresses, registrations in apps or on websites etc. can’t be under-estimated, but is it enough? What about interactions with the staff at the airport or at the gate on the day of travel? The data platform needs to pave way for online and offline inputs. Specialists point out that offline data is more likely to be structured and come through batch file transfers. What’s the mechanism for real-time inputs and how the same can be made available for use? The sort of questions that are being scrutinized pertaining to data strategy and the serving platform are going deeper. For instance, how to unite anonymous profiles with personal identifiers that enables the system to append specific features such as age, location, interests, purchase history etc. to manage such profiles better. So let’s say a passenger is an infrequent traveller, who isn’t part of an airline’s loyalty program. What if he made a request for a particular seat on two journeys, but he wasn’t allotted due to unavailability. Can the same be done by identifying this traveller, at the time of his next booking, by connecting trails of data available?

So how ingestion of data (airlines need to act on online sources, offline sources of data, plus structured as well as unstructured data), connecting with external sources for updating profiles or even connecting anonymous visitors with their past record, analytics and extraction for real-time use (includes profiles to be connected in real-time to transactions and to events), visualization etc. is going to transform customer-centricity is an interesting area to watch out for.

2.     Don’t be device-centric: A user looking at a trip itinerary from two different devices and being counted as “two different users” only results in a gap in delivery of content, deals and overall experiences. It is said that on an average a consumer moves between devices up to 20-25 times an hour and uses three or more different devices to complete a task.

So what sort of content to show? What time and how many times? To answer these queries, travel marketers need to craft a unified device graph, based on account log-ins plus identification of a pattern via algorithms (through variables such as IP address) that link devices to one user. This blend brings accuracy as well as scale. Adobe recommends that the device graph needs to work with the existing marketing stack to avoid siloed device-graph data and be embedded within existing marketing tools. This when works gives better picture about how a user, rather than his or her devices, is interacting with digital assets, plus also provides valuable information about attribution, how to work on efficiency of ads (frequency capping) etc.

3.     Solid enterprise data platform: Airlines need to blend digital and offline consumer identities into an omni-channel identity, and this has to be supported by an astute data platform. This forms the basis for connecting online cookie and profile data with offline customer data into a single identifier. So not only airlines have to be prepared for call centre interactions or at the boarding gate, but they also need to possess a platform that is proficient at cleansing, deduping, refining of omni-channel customer data profiles, and comprehensive inclusiveness of digital and offline data. Retailers are already counting on such offerings for hyper-personalized messaging via linking of mobile ID, email addresses, web cookies etc. to validate customers. Only this can lay a strong foundation for advanced machine learning to facilitate meaningful interactions across the passenger journey. As for analytics and machine learning,  both supervised and unsupervised models are increasingly coming to the fore in order to optimizing messaging and offers/ deals to customers. These platforms pave way for unified, identifiable customer data.

            4.     Keeping pace with advancements in ad tech: Travel marketers can embrace emerging ways to assess how many customers rather than devices visited their digital assets and interacted with their brand. For instance, there is emergence of cross-device audience extension over the last couple of years. The goal is to enlarge any set of audience or segments by going beyond their existing or unique group of identifiers and related them with additional cross-device IDs - cookies and device IDs to the original set. This is imperative considering the ownership and use of multiple devices, and since today’s traveller is always connected, this means it is important to make the most of both deterministic as well as probabilistic matches.

Another area is location extension. According to Drawbridge, this refers to capitalizing on location data with retargeting. This way travel companies can reach travellers based on where they’ve been – not just where they are – and do so on all of their devices.


Gain an insight into the latest trends pertaining to data strategy and travellers’ buying journey at the upcoming Ancillary Merchandising Conference in Edinburg, Scotland (9-11 April, 218).

Follow Ai on Twitter: @Ai_Connects_Us


  • Ai Editorial: 6 stringent measures for dealing with loyalty fraud +

    First Published on 18th February, 2019 Ai Editorial: Rather than relying on archaic methods, travel companies should look at dynamic multi-factor authentication, behavioral analytics and machine learning to combat loyalty Read More
  • Ai Editorial: Making mobile app count - easyJet shows the way +

    First Published on 13th February, 2018 Ai Editorial: Rather than only focusing on incremental revenue, easyJet has been looking at ways to capitalize on what role mobile devices can play Read More
  • Ai Editorial: Flirting in aircraft or points for quality sleep – what entices you? +

    First Published on 8th Feb, 2019 Ai Editorial: The last few days have been exciting. Delta and Coca-Cola apologized for introducing flirtatious napkins on-board, whereas Qantas chose to offer frequent Read More
  • 1
  • 2
  • 3
  • 4
  • 5