Data in the travel industry is growing at a phenomenal rate, with search requests, booking, payment and competitive pricing information and other data points being generated from both online and offline sources. By aggregating all this data in a readily available format suitable for interpretation, a great opportunity exists for travel professionals to apply the powerful tool of analytics to gain a better understanding of customers' transactional and behavioral habits.
Analytics applies recent advances in decision science, pattern recognition and statistical analysis to extract insights from raw data. It can provide travel professionals with the tools needed to gain insights into not only how something happened in the past but also what's most likely to happen in the near future, enabling those responsible for sales and marketing of travel companies to tailor "context aware" campaigns and products.
Tapping behavioral analysis
Take, for example, a travel agent who needs help cross-selling value-added services to existing customers. By analyzing past travel behavior, the agent can create a cross-selling model that scores each customer based on his or her propensity to consume certain products. Customers who cross a certain threshold could be targeted with a compelling offer. There could be multiple models built depending upon the product to be sold, including hotel bookings, air travel, corporate travel, car rentals or insurance.
Based on transactional data, a travel seller can segment high-value customers and dive deep into the engagement levels of subsets of customers to determine which ones have started disengaging. Some business questions that can be answered include:
- Who are our "valuable vulnerables"?
- What are the behavioral characteristics exhibited by valuable vulnerables?
- Which are corporate vulnerables? Which are leisure vulnerables?
- Can we proactively score customers who are likely to disengage with agents?
- How can we drive proactive outbound campaigns targeting valuable vulnerables to stimulate bookings with the agent?
Resonating product bundles
Analytics can also propel the creation of innovative product bundles with discounted pricing. For example, after deeply analyzing past travel behavior, suppliers can create customized bundles that resonate with the needs of niche customers.
These might include bundles designed specifically for business travelers, leisure travelers, international travelers, most valuable customers or frequent business travelers to the same city. Bundles can also differentiate the behaviors of most valuable customers from the behaviors of others or the behaviors of frequent and less frequent business travelers.
Optimize corporate customer costs
According to the U.S. Travel Association, Americans logged 448 million person-trips for business purposes in 2010. In addition, direct spending on business travel by domestic and international travelers, including expenditures on meetings, events and incentive programs, totaled $233 billion last year. By segmenting customers into business travelers and nonbusiness travelers, suppliers can analyze travel/stay patterns of corporate customers to various destinations and help companies optimize overall costs.
They can, for example:
• Do "what if" analyses to explore cost savings that would be possible if alternate hotels or airlines were chosen.
• Proactively advise corporate customers on alternate options to optimize cost savings based on a detailed understanding of past travel behavior.
• Offer targeted cost optimization advisory alerts to top 10 corporate customers.
By doing so, the agent becomes a trusted adviser to businesses to help them proactively optimize cost.
Assembling the parts
While data analytics offers vast opportunities for the travel industry to monetize information, several pieces need to be in place before that can happen.
First, build an analytics team. Any organization serious about using data as a competitive differentiator should consider setting up a dedicated analytics team whose only mission is to excavate revenue-impacting patterns buried in raw data, then disseminate them throughout the organization. This is a cross-functional team of domain experts, analytical modelers and very large database experts who together can build robust analytical processes.
Second, you will need a framework for tracking before-and-after metrics so the value of the analytical process can be quantified and tracked.
Third, you will need an analytical platform. Software from SAS, IBM, SPSS or Oracle Data Miner is needed to help the analytics team run processes such as segmentation, customer scoring models, text mining, etc.
The breadth and depth of data streams pouring from internal and external travel data sources might, unless managed, overwhelm the travel industry. However, by embedding the right filters and lenses, travel companies can gain insights that help optimize pricing decisions, promotional campaigns and customer treatment.
Derick Jose is the vice president of Advanced Analytics/Research within MindTree's Data & Analytic Solutions Group. He can be contacted at [email protected].