In a position paper, the Society of Consumer Affairs Professionals
shows how vital it is for the travel industry to effectively manage the millions of records about travel behavior that the industry generates each day.
Defining Big Data
Context is always murky when it comes to the nebulous concept of Big Data - it doesn't always mean the same thing to different people.
SOCAP defines Big Data as "the productive use of data in units of measure that far exceed megabytes and gigabytes." While this is a broad definition, the idea behind Big Data is crystal clear: use the information that customers are already generating to provide them with better, more targeted - and ultimately more profitable - services and products.
Travel is ripe for that sort of use. Startups and incumbents alike are attempting to leverage this data into a useful, consumer-centric stream.
However, beyond simply managing and leveraging owned data streams, travel brands need to consider how to use other indications of consumer preferences and lifestyles:
If intelligent networks hold the key to next generation travel, Internet companies enjoy a bounty of data pouring in from cookies, log files, and other sources.
Take the photos being posted on Facebook or Instagram. Would the traveler sharing snaps from a trip to Ireland be interested in information about Scotland? If shown on a mountain bike, would that individual want to know more about local biking destinations or biking clubs? If shown standing in front of a car with a bicycle roof rack, wouldn’t a trunk rack be easier to use and avoid back problems down the road?
Big data and data analytics suggest that the future may belong to those firms best able to shape and deliver the consumer travel experience.
In a series of interviews within the travel industry, the study authors are intent to show how Big Data can be used to increase impact and reduce friction across disciplines, both within a company and the industry.
Personalization is a key tenant of Big Data. With so much available information about a particular consumer, transaction or destination, the reality is one of detailed, accurate personalization.
In order to most effectively win at true personalization, large travel companies must work across silos to gather the myriad data points created by a consumer at different points, as the study emphasizes:
Information systems can be quite fragmented and even territorial, with records pertaining to a single customer showing up in reservation, post sales complaint, survey, loyalty and other systems, with little or no ability to weave together and form a complete customer profile.
Combining data from different in-house systems can help companies achieve new insights.
Call centers must interface with online consumer reviews; loyalty programs must link with booking histories; on-property preferences need to be combined with social media chatter. It's a giant firehose that first must be segmented and then packaged in a useful way for employees at each stage of the consumer lifecycle.
Michelle Mitchell, the Operations Manager for Customer Care at InterContinental Hotels Group, identifies just how vital some of this "lost" information can be. The company is working to combine survey data with actual call center metrics:
It will let us more specifically see if a particular agent is receiving negative guest comments and if there’s the possibility of a trend. Maybe that agent is in a bad mood after lunch. Are the calls coming in on a Saturday versus Friday? What time do they occur? What’s the takeaway?
By combining data clusters, organizations can actually deliver on Big Data's big promises by extracting business intelligence ripe for action.
The customer should be at the center of all Big Data efforts. If the data gathering is seen as creepy or invasive, the consumer will not be pleased and loyalty will be lost. However, all signs point to consumers willing to accept vast intrusions into their behaviors if the resulting product is more targeted and able to anticipate their needs throughout.
SOCAP names the following distinct areas that companies need to master in order to succeed at a Big Data-fueled consumer experience:
- Align company offerings and customer needs.
- Build internal consensus.
- Collapse data silos.
- Create unified, logical data views.
- Elevate the customer care role in customer experiences.
- Collect and use data responsibly.
Internal buy-in comes not only from active consensus building, but also by ensuring that the company's offerings are addressing customer needs. This makes it easier to train employees to be active in solving these needs, and to clearly understand the value that they are providing.
Aligning the company with customers also makes it much easier to eliminate silos and fiefdoms, and more easily integrate an open sharing of data and information company-wide. This also helps foster a collaborative environment focused externally on the customer and not internally on politics.
Finally, privacy is a paramount concern when it comes to Big Data. Avoiding privacy snafus is an essential component of successful Big Data implementation, and also ensures a significant level of trust on the consumer side.
Focus relentlessly on the useful implementation of the data as far as the customer's experience is concerned, and the majority will embrace a better product that more fully addresses their individual needs.
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