Alteryx provides airline analysts with the unique ability to easily discover, prep, blend and analyze all of their data using a repeatable workflow, which can be deployed and shared at scale for deeper insights, insights that come within hours, not weeks. Airline analysts can utilize the Alteryx platform in a multitude of ways, including connecting to and cleansing data from their data warehouses, sending and receiving data sets from cloud applications, as well as gleaning information from spreadsheets or a whole host of other sources. Airlines analysts can easily join their data together, then perform analytics—descriptive, dignostic, predictive, prescriptive, statistical and spatial—using Alteryx's intuitive user interface, which is, if not a code free environment, then a very code friendly one.

Southwest Airlines uses Alteryx to build a self-service environment to ensure their analysts' time is spent on analysis not on data wrangling and data cleansing.  

For the airline industry in particular, Intelligencia has built a set of almost plug-and-play solutions that can simplify a multitude of business challenges, including the following:

Customer Segmentation

Customer segmentation is a deceptively simple-sounding concept. Broadly speaking, the goal is to divide customers into groups that share certain characteristics. There are an almost-infinite number of characteristics upon which you could divide customers, however, and the optimal characteristics and analytic approach vary depending upon the business objective. This means that there is no single, correct way to perform customer segmentation. That being said, customer segmentation is often performed using unsupervised, clustering techniques (e.g., k-means, latent class analysis, hierarchical clustering, etc.), but customer segmentation results tend to be most actionable for a business when the segments can be linked to something concrete (e.g., customer lifetime value, product proclivities, channel preference, etc.).

Customer segmentation is the process of dividing customers into groups based upon certain boundaries; clustering is one way to generate these boundaries. There is an important caveat though—clustering assumes that there are distinct clusters in the data. Oftentimes, customers are distributed more or less continuously in multivariate space, and they aren’t in neatly defined groups. A customer segmentation model provides a view of the airline from a customer perspective: such models have many and varied applications. Customers are segmented according to what they present to the airline. Views include:

·       Interests and needs

·       Gender and age

·       Marital status

·       Spending history

·       Demographics

·       Psychographics

Generally, the data is used to determine the appropriate segments for these views. The result of this analysis presents a detailed view of the airline customer demographics, which can help the airilne make appropriate strategic decisions out of the data. These decisions could be a function of marketing, operations or strategy. The output is also used for the building of acquisition models.  Other potential for analysis would be a master segmentation model that uses the preference results described. Customers are clustered based on their preferences to gain a global view of the airline that is concise and understandable. Furthermore, such models can help measure the impact of strategic decisions.

Alteryx's K-Centroids Cluster Analysis Tool allows users to perform cluster analysis on a data set with the option of using three different algorithms: K-Means, K-Medians, and Neural Gas.

Natural Language Processing

Natural language refers to language that is spoken and written by people, and natural language processing (NLP) attempts to extract information from the spoken and written word using algorithms. NLP encompasses active and passive modes: natural language generation (NLG), or the ability to formulate phrases that humans might emit, and natural language understanding (NLU), or the ability to build a comprehension of a phrase, what the words in the phrase refer to, and its intent. One of the major use cases for AI is sentiment analysis, which uses NLP to gain insight into how a business is seen on social media. For airlines, NLP can help them understand what customers are saying about their company and their competitors. Managers can use these insights to increase customer intelligence and customer service. Intelligencia has built an Alteryx-based NLP solution for the airline industry utilizing Python that can be used as a powerful social media listening tool. 


Alteryx Workflow

RFM modelling

RFM is a method used for analyzing customer value. It is commonly used in database marketing and direct marketing and has received particular attention in the airline industry. Intelligencia has created an Alteryx workflow that can help airlines understand the breakdown of their customer database. The workflow can produce outputs that can be given to the marketing department so they can reach out to high-value customers on one end of the spectrum, as well as customers who might be ready to churn on the other end of the spectrum. See the video below as well as the three step workflow. 

Alteryx Workflow