A prominent travel and leisure destination developer builds, maintains and markets dozens of four-star, high-end ski villages, golf resorts and beach properties. Each year, the company hosts millions of visitors at these luxury destinations, and to enhance these customer relationships, the company focuses on retentions and return visitors. To keep customers interested and informed, the company is also striving to find new and innovative ways to promote existing services to their client base.
Like all marketers of high-end products, the resort developer had a problem: how do you market to an audience that expects – if not demands – highly personalized interactions? To accurately communicate with its customer base, the company had to build a more usable store of customer data. This store of customer data could then be used to segment customers, personalize customer communications, and market to customers more effectively.
Because each property had its own business systems, including customer relationship management (CRM) and operational applications, customer data was available in separate “silos” throughout the company. The company had no easy way to understand that the Smith family that hit the slopes at one of its ski resorts in the winter and the Smith family that relaxed at one of its beach properties in the summer was, in fact, the same Smith family. On top of this, there were separate systems within each resort that captured transactional data on lodging, retail, food and beverage and so forth.
As a result of this disparate network of data sources, the company had duplicate, redundant or unaffiliated data from system to system. The company needed to clean up their data to build a unified, accurate and reliable customer master file to build a true view of the customer.
Many companies implement customer data integration (CDI) programs without understanding the role of data quality in building the reference master file. If the result of the integration project allows multiple records per customer, a marketing campaign may send the same person several duplicate mailers. More importantly, the company might fail to realize the true lifetime value of the customer. This resort developer chose DataFlux to help build robust customer profiles that could better support personalized marketing campaigns.
The company uses DataFlux to analyze, correct, integrate and enhance customer data as it enters the master customer database. With DataFlux’s sophisticated matching technology, they can link to information in the legacy, resort-specific CRM applications, creating an aggregate record that contained all the details about the customer’s account history.
From hotel reservations to ski lift tickets, information from each resort rolls up into the master reference system. Regular use of DataFlux helps correct and validate information to ensure the customer data is an asset for the entire organization.
After implementing DataFlux technology, the company can now build more effective marketing campaigns. Customer data is now centralized into one system, allowing marketers to segment customers according to similar interests, hobbies and spending patterns. Since the data is much more reliable, they can create more accurate, personalized campaigns.
The ultimate goal of the resort developer is to create a lifetime relationship with its customers. As data is collected over time, they can offer promotions for different stages of life. For instance, a 40-year-old person who is a frequent skier at the resorts would receive promotions for time-share opportunities at the developer’s newest ski resort. By utilizing more accurate customer data, the company can build better marketing programs – and create more profitable lifetime relationships.