Data quality will have influence not only on customer acquisition but also on customer retention and relationship development. Improving data quality costs money. Relevant customer data need to be gathered and their quality needs to be managed. Information on the identity and profile of former, current and prospective customers has to be collected and registered. Data have to be taken from different sources and bought from external data suppliers who will supply single-use data (Peelen, 2013).
The main data that has to be collected are transactional data, lifestyle data and behavioural data. Transactional data is information relating to what people spend, where they spend it, how often and how much. Lifestyle data refers to who people are, where they live, what their interests are and what’s important to them. Behavioural data relates to people’s activity, both online and offline, what they do and via which channels (Matthews, 2016).
There are two real life examples on acquiring and using data.The first case is the one of Swissair Group. Their primary data source is the frequent flyer programme database. Frequent flyer program helps to increase and award loyalty of their customers. The key program features are mileage accrual (members can earn miles for air travel, but also for activities like hotel stays, car rental and credit card usage) and mileage redemption (members can spend miles for air travel, hotel stays etc.). For each member, data about demographic figures as well as the current state within the program are collected in a database. A second database contains a list of all single past flight legs, which is consisted departure and arrival airports, booking information and members id. Supplier activities like credit card usage are also gathered in an additional database. There is no information available on passengers’ revenue, because the frequent flyer database is used only for administrative purposes. In order to complete the flight activities in the frequent flyer database with revenue data, it is relevant to assign the corresponding values to the individual flight segments from a sales information database, where revenue information about individual bookings is available (Pritcher, n.d).
In order to know which customers bring the most revenue, Swissair Group has decided to use the strategy of customer profiling. Therefore, the company has chosen to target only the members of the Frequent Flyer program. The reason for that is because members’ information are more reliable and the data about flight activities are more complete.
The second example is Boxever. Boxever is a cloud-based solution that tracks every aspect of customer intelligence. It contains a unique timeline view that contains behaviors, transactions, demographics and social data stitched together using sophisticated identity matching algorithms (Boxever, 2016). In addition, the technology also provides product recommendation, real-time interaction management and triggered communication. Therefore, a few major airlines such as Emirates, Air New Zealand and Alitalia started to use Boxever.
It can be concluded that various company track data on their own while some companies use the method of outsourcing. Working indepedently might be more reliable but also more time-consuming. However, the acquisition of the most advanced technologies that allow to analyze customer data could cost a fortune for many airline companies.
Peelen, E., & Beltman, R. (2013). Customer Relationship Management. United Kingdom: Pearson Education Limited.
Boxever (2016.). Customer Intelligence. Retrieved from: http://www.boxever.com/products/enterprise-platform
Matthews, D. (2016.). How connected data is targeting consumers. Retrieved from: http://raconteur.net/business/how-connected-data-is-targeting-consumers
Pritcher, L. (n.d.). Data Mining And Strategic Marketing In The Airline Industry. doi: 10.1.1.124.7062.