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big data travel agents

Big Data Becomes Real for Online Travel Agents

July 11, 2016

Big Data has been a hot topic for a while. Amadeus did a study three years ago when early adopters were working on it. Now they’ve come out with an updated study which finds that the key to success with big data is experimentation, but it’s no longer for early adopters and it’s no longer optional for companies that want a competitive advantage.

The data that a travel business needs for analytics has existed since the online travel business started but the data was scattered across different companies. Plus, managing and manipulating that data was complex and costly.

Technology changes have made storing and working with that data much less difficult. Cloud storage is available at low cost and companies can add space on demand as needed. Tools like Hadoop and Spark make implementing analytic algorithms less complicated and make it quicker to get results. Cloud service providers offer Platform-as-a-Service, enabling companies to configure analytics environments quickly and shut them down quickly too paying only for the storage and computation time used.

In addition, consumers now expect a highly personalized level of service. Every other online store they purchase from makes suggestions based on their purchase history. For online travel agents to continue to win and retain customers, an OTA’s interactions with the customer need to match the norms of the customer’s other online interactions.

Using Big Data to Sell (What the Customer Wants)

Probably the most common use of big data by OTAs is to create more sales by improving website design. With big data, logs can capture much more information about how users interact with the website—tracking things like where the mouse hovers and for how long. A/B testing can make use of those statistics, letting companies experiment with different layouts to identify the one that generates the most sales and beats the statistics that say that just a tiny fraction of visitors to travel sites actually convert.

But focusing solely on increasing sales through manipulative website designs misses the point and the potential of big data. Another main use of big data in travel is to personalize the interactions with customers to sell them experiences they want. There’s a move to reconceptualize travel sales so they don’t focus solely on the logistical aspects of travel, but on helping customers to realize the experiential aspects of travel.

To do that, companies need to understand their customers’ preferences, priorities, and values. This can mean pulling in data from other sites such as social media networks. Then companies can support the customer through features like displaying search results in an order that correlates to the customer’s preferences and suggesting changes or additions to their travel arrangements that will result in a better travel experience. This kind of personalization doesn’t just result in a better conversion rate, it makes for a happier customer—who’s likely to tell their friends about it and come back the next time they want to plan a trip.

Using Big Data to Improve How You Do Business

Doing business isn’t just about making sales. Big data can support the business in ways that reduce costs and improve how the business is run. Real-time analysis can help block fraudulent transactions before they’re accepted and costs are incurred, while analytics that monitor your networks can help defend against malware and hackers. Big data can help your data center understand its usage and performance patterns to prevent outages and other service issues.

Perhaps most importantly, understanding your customer through analytics can help you develop a business strategy that meets the customer’s needs.

Big Challenges in Big Data Aren’t Insurmountable

Even though dealing with big data is becoming easier, there are still challenges. Some of them are technical: there’s a lot of competition for hiring data scientists and you need to integrate new technology like NoSQL databases into your stack.

Other issues are cultural: customers need to trust that you’ll protect their data and that you’re not manipulating results solely to increase your profits (and that you won’t show different prices based on who manufactured their computer). The biggest cultural factor you have to overcome may be your own. Online companies typically expect results at internet speeds. The experimentation needed to create a profitable big data application can take an eternity by that metric. For companies that want to stay in business long-term, making a long-term commitment to big data projects can be vital to achieving that goal.

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