Managing Dynamic Data to Enhance Guest Experiences

By David Sterling

David Sterling is an expert in the area of market strategy and service development for mobility and cloud-computing solutions. A Partner at i3m3 Solutions, a boutique services consulting firm specializing in mobile, web-centric and managed solutions for clients in the US and Europe, he brings over 20 years of global network and management experience with firms such as AT&T, British Telecom and Fidelity Investments. Across his global career, David has launched and expanded business services worth over $250 million in broadband networks, data services, and Internet applications. He specializes in market strategy and go-to-market services initiatives. Under his leadership, client businesses have launched mobility services, hosted applications and streamlined business operations in hospitality and other industries. David has earned a Master of Business Administration degree from Cornell University and a Bachelor of Science degree in electrical engineering from Purdue University.

Guests’ service expectations are shifting as hotel and third party providers integrate new technologies into the travel value chain to improve guest services. Common now are expectations of greater conveniences as guests become more familiar with Web, mobile and property technologies. The next generation of Customer Relationship Management (CRM) systems, in-room media and services, locator technology, property “information hubs”, and IT monitoring and repair processes are several of the hottest technologies that serve these expectations. ¹

With all of this information potential, how do service providers maximize the ROI of these systems? How is the right information mix applied at the appropriate time for each customer engagement? This article explores the potential of applying Data Fusion methodologies and predictive marketing models to increase the success rate in leveraging existing resources to extend hospitality brand experiences and improve margins.

Industry Factors

The coming hospitality industry reflects new global travel patterns and demands greater differentiation from hotel operators. By 2015, the global hospitality market will be shaped by ² :

Rising economies in emerging markets of Brazil, Russia, India and China
Increasing brand concentration and differentiation
Growing need to manage brand transitions
Growing consumer brand agnosticism
Growing influence of disintermediation and technology

A key differentiator and ROI leverage point for hospitality providers is the extent to which technology and available market, customer and competitive information is managed for greater value. Successful providers tie together existing information sources in ways that deliver relevant views to their organization that enhance one-to-one marketing programs and guest experiences. From promotions to front desk relations to mobile-based services, these cumulative initiatives targeted to guests can combine to generate 14% to 23% higher profits than benchmarked industry players.³

Guests expect increased choice along with personalized service that adapts to their travel needs. Successful providers dynamically manage access to guests across the Internet, call centers, property locations and mobile devices. They have the capability of delivering specialized offers that build loyalty and result in increased service margins of 20% or more.⁴

In order to effectively deliver these offers, hospitality providers need to manage the onslaught of digital data as well as identify and “fingerprint” specific customer needs. By 2015 the digital universe (total amount of digital information created worldwide) is expected to increase forty-four fold, and double every 10 minutes!⁵ Given this environment, tracking the right information and delivering it to the right location requires new IT and networking methods that work in conjunction with existing databases and systems.

Special Offer Scenarios

With the coming deluge of information, opportunities to better serve guests by leveraging these new sources of input (i.e., video clips, mobile-based services, user-generated content, etc.) are enormous. Guest service scenarios will proliferate with increased mobility and access to information. Therefore, in addition to current operational support requirements, IT systems will need to support new customer-related data inputs. A sample includes:

Promotions, reservations and travel logistics:

Guest going online to select and book hotel and airline reservations based on user community blogs
Guest updating estimated arrival time by cell phone
Guest self-check-in / check-out

Closed guest communities using mobile applications to deliver special offers:

Listing available restaurants and booking reservations
Receiving concierge promotions and locale information
Delivering discounts with service partners based on mobile-based solutions

Property and locale-wide information displays:

Delivering in-room promotions over hotel Internet and TV/cable
Sharing hotel dining or health club hours over guest room and common areas

Finding Customer “Fingerprints”

These inputs need to integrate over a range of IT management systems that collect, track and process hotel data – content management, reservations, customer relations and property management systems – to name a few. Finding the desired customer data “fingerprint” requires reconciling disparate data records that change independently over time. It requires knowing where data resides as well as processing and delivering it in a timely manner.

Useful solutions must:

Keep source data whole without modifying or disrupting it while allowing for independent updates
Provide timely capture of data elements
Link associates across disparate information sources covering both simple and complex databases
Normalize and track the aggregate view
Allow users to apply relevant business rules dynamically to get meaningful results
Keep track of changing data elements on a real-time basis

Targeting Your Guest

Finding your guest “fingerprint” amongst the deluge of data requires a solution that leverages existing systems while addressing gaps between disparate information sources. Data Fusion is one such solution that copies and aggregates information “silos” for a full view of available data records. It enables users to view the complete, relevant set of guest information.

To obtain this guest “fingerprint” in real-time, the Data Fusion solution:

Engages a fast information search and discovery capability
Identifies a unique view of all relevant information, and
Quickly updates changes in data

To arrive at an extremely fast information search and discovery capability, the Data Fusion model and software combines i) a business rule-based search engine, ii) an object oriented software structure and iii) an architecture comprised of multiple in-memory caches. The method begins by copying either structured or unstructured data from your selected sources of information.

Once collected, a normalized information record with a unique identifier is created reflecting the aggregate view. Based on the rules applied to determine a guest “fingerprint”, only the best fit results are stored. This speeds resolution time and minimizes the number of records needed for the “fingerprint”. These rules can be adjusted on the fly, enabling users to quickly refine their search.

The solution tracks both the source data locations as well as how long data are relevant with time stamps and time flags. These time parameters are assigned by users to data elements to indicate how often information should be checked and updated. Only updates to changed elements are processed, while source information continues to update independently. “Off-line” caches are used to copy information updates, thereby avoiding read/write contention issues typically seen with other methods. This enables the right data to be available at the right time for users.

The solution can provide real-time discovery across hundreds of applications. Using easily defined business rules, it progressively refines its inferences and does not require clean data to initiate searches. Therefore, valuable time and resources are saved that would otherwise cleanse and organize data inputs.

Output from this method can also be utilized as input to existing business intelligence systems. This can help drive better understanding of customer patterns, increase customer loyalty and generate higher margins.

Data Fusion methodology can:

Link internal and external data for a correct real-time view enabling service differentiation
Leverage new sources of guest information for higher margins
Manage changes in guest and business information over time
Allow rules to be dynamically built and applied that adjust to customer needs
Integrate best-fit inferences with predictive models to refine customer targeting and build loyalty

Enabling Personalized Service

Data Fusion methodologies and predictive marketing models enable faster response to changes in customer behavior – for serving, selling and managing guest experiences. Fast and personalized information is brought to bear across organizations, while providing full audit trails to quickly resolve disputes and enable service recovery.

¹ “Top 5 hospitality trends”, Microsoft, www.microsoft.com/hospitality, June, 2010.
²The School of Hotel Administration at Cornell University and the Gilbane Group, May, 2010.
³The Hotel Yearbook 2010, ed. Ecole hotelier Lausanne and Wade & Company, S.A., December, 2009.
⁴The Hotel Yearbook 2010.
⁵IDC Digital Universe Study, IDC, May 2010.