Big data brings endless opportunities for the travel industry, but this ever-changing field also brings with it many challenges. For direct booking travel businesses and travel aggregators, microscopic pricing and performance advantages will determine each sale in today’s competitive market. The key is the data. Here are three tips to help online travel booking companies as well as travel aggregators steer clear of glitches and dirty data, and raise the volume of sales.

There’s no need to explain the Online Travel Agency (OTA) business model, how it has revolutionized the travel industry, or how these companies (and later their offshoot travel metasearch engines) have utterly dominated online travel for nearly two decades.

But recently, we’ve seen a tectonic shift in online travel. The travel industry like many others have amassed an inordinate amount of data on their consumers, flights, hotels, experiences, loyalty programs, complaints etc. With customers creating so much valuable data at every stage of their journey, how can travel companies do more to collect and connect these data points to improve the customer experience?

Airlines, hotels, travel agencies, aggregators and others in the travel business need to do what they do best – provide outstanding value and respond to rapidly-changing markets. To do this, they need to ensure that the data they’re getting from all parties is clean, that each of the APIs that nourish their business are glitch-free, and that they can respond agilely yet accurately.

The thing is, when you’re running a travel business that is processing nearly 50,000 events per second and drawing on data from thousands of parallel services – it’s tough to tell if something goes wrong!

Dirty Data + Glitches = Lost Business

In general, research has shown that 40% of anticipated business value is lost owing to poor data quality. Gartner estimates that dirty data results in losses approaching $10 million a year for the average company.

Online travel businesses operate in a space where handling an extremely high volume of data from diverse and disparate sources at tremendous velocity is all in a day’s work. This sheer scale of data magnifies the impact of glitches and dirty data –  potentially cutting deep into the bottom line. It’s also what makes it nearly impossible for data analytics teams to identify and rectify revenue-siphoning problems in real time.

For example, a sudden drop in sales of travel packages during the pre-holiday rush period could be the result of a simple pricing error, a negative trend on social media, a server glitch causing slow load time, a coding error that makes checkout impossible, a handshake problem with one of the hundreds of travel provider APIs, an error in the payment gateway, an error affecting just one type of browser over one operating system…the list goes on.

The Road to Regaining Sales

More than ever, travel businesses and aggregators need to overcome the challenge of spotting dirty data and glitches before they hurt the bottom line, and maximizing the value derived from big data as a whole. This is a great first step on the road to regaining sales volume lost to direct travel providers. To start down this road, make sure that you’re:

  1. Watching customers to identify problems faster – Sound intuitive? It should be. But not all online businesses can yet track in aggregate exactly what customers are doing on the site or in their apps. This is data that tells a story. It can show you pages, page elements, or products that show sudden drops or spikes in traffic. By way of example, a sudden runup in sales offset by a drop-off in revenues for a given vacation destination could indicate page-level mis-pricing. A drop-off in sales for customers using a particular Android version might mean a version-specific glitch in your app.
  2. Closely monitoring secondary data sources – For travel businesses, nearly all data is external data. Yet beyond this mission-critical core data from hotels, airlines, car rental agencies, and others – there’s a world of relevant secondary-source data to monitor. Need examples? How about competitor advertising bid data, weather data (which can cause revenue-impacting power outages or discourage travel to certain destinations), fraud detection and security data, and more. This is data that can quickly and dramatically affect travel plans, and you need be able to analyze trends in real time to understand how to best respond to findings from it.
  3. Listening to social media buzz – Social media monitoring is not a vanity metric. Used correctly, this data has real value to sales and marketing operations. Working in real time, correlating social media data with changes in demand for travel packages or destinations, can offer valuable insights. For example, if a celeb promotes a certain destination via social media, you need to quickly identify the actual business impact to your specific business. That way, you can more effectively leverage the momentum to tailor inventory to meet expected demand, tweak pricing to further drive demand, tactically bundle products to grow overall package profitability, and more.

The Bottom Line

Identifying dirty data, catching glitches, and leveraging data assets in the hyper-complex, multifaceted travel ecosystem is a task that stretches the limits of human capability. Travel is a fiercely competitive industry where speed is always of the essence, but minimal advantages can reap great rewards. The key to unlocking those rewards will be the use of reliable data, enhancing customer experiences. To meet the challenge, direct booking players and aggregators need to seek out and adopt technological solutions that have the speed, accuracy and agility that will make difference in their bottom line and impact future operations.

Written by Anodot

Anodot leads in Autonomous Business Monitoring, offering real-time incident detection and innovative cloud cost management solutions with a primary focus on partnerships and MSP collaboration. Our machine learning platform not only identifies business incidents promptly but also optimizes cloud resources, reducing waste. By reducing alert noise by up to 95 percent and slashing time to detection by as much as 80 percent, Anodot has helped customers recover millions in time and revenue.

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