Data strategySeptember 18, 2018

Customer Data Platform use cases: Travel

Travel companies need a customer data layer as flexible and agile as their services. This blog will cover common use cases to determine which CDP features are relevant and find the CDP that will help you meet current and future business needs.

Travel companies have more direct access to customers than ever before thanks to the digital era. Travel agencies have been replaced by direct customer transactions online through booking site, airline, and hotel sites and apps. In fact, online travel booking sales are expected to reach $693B in the United States by the end of 2018. While the majority of these travel sales coming from desktop, mobile booking is gaining quickly.

With interactions occurring across many devices and channels, travel companies can no longer rely on legacy systems to understand who their customer is, how and when to reach them, and how to measure the influence of marketing, product, and engineering initiatives on the bottom line. That's why many forward-thinking travel companies have started to consider using a customer data platform to unify and orchestrate their customer data.

To find the right CDP, marketers need to consider their current data maturity and how it can be used as well as what their future goals are and what data will be needed to achieve those goals. Data maturity levels can be broken down across four maturity levels, from least to most mature: Foundational, Insight and Experimentation, Omnichannel Engagement, and Continuous Optimization. This blog will take you through use cases at each level to help you determine which CDP features are relevant to your situation and find the CDP that will help you meet your current and future business needs.

Level 1: Foundational use cases

Objective:

Establishing essential data processes and deploying standard marketing technologies

Organization focus:

Centralizing of clean customer data, connection to marketing, BI, and analytics tools.

Accelerate time to value with new tools and democratize data access

Modern marketers want to innovate as quickly as their businesses and customers, but struggle to get the engineering resources needed to implement new tools. A well-instrumented CDP can democratize data access around a single source of truth, delivering and maintaining clean, complete data feeds to different business stakeholders’ systems of choice via pre-built connectors and/or API, without depending on engineering. A CDP should also be able to create, update, and send audiences to marketing and advertising platforms, without manual list pulls, enabling unparalleled speed and agility.

Use case: Launch new paid media tools

To launch new paid media tools, hotel brands need to be able to quickly and easily integrate tools with their existing infrastructure and then provide access to a subset of customer data in the right schema format. Instead of spending time and engineering resources creating a custom integration, hotel brands can use a CDP with pre-built connectors to get it integrated and running in no time. Using the segmentation page in your CDP UI, hotel brand marketers can create custom segments for targeting based on a variety of attributes to forward to the new paid media tool, like creating a segment of customers that have previously stayed at the hotel during a baseball game at home and sending them an offer for the next weekend there is a home game. Launching new channels is just as easy, using a CDP with a pre-built integration to the push notification vendor, like mParticle, marketers can connect customer data directly to send special offers to customer's phones. Taking the data integration planning and implementation process out of the equation allows marketers to test and find new engagement channels that resonate with the customer and further business goals.

This makes it faster and easier for marketers to launch new tools and initiatives, and, as a result, decrease time to ROI.

Augment legacy analytics and attribution

The majority of active internet users still interact via browsers, making it the most important digital channel for consumers. As a result, web analytics are essential for marketing organizations; however, the shift towards mobile and connected device engagement has shown brands that they also need to be able to collect and analyze data from every touch point across the entire journey to understand how interactions influence customers. This can be tough because legacy systems are not built with mobile in mind, but a CDP can help; using mobile-specific SDKs to collect data from apps then delivering it to web analytics platforms creates a complete view of the customer’s journey and enables further analysis and attribution.

With a complete view of the customer journey, marketers don’t have to rely on “last click” attribution. Instead, they can test and integrate new tools to attribute weight to each interaction using a CDP. Marketers can use data from their as input to these tools to test different algorithms and interfaces without instrumenting each attribution tool individually. A CDP can also track the long-term performance of customers acquired through advertising by associating campaign membership with full lifecycle events and attributes with acquisition source to inform strategic resource allocation decisions or direct systems that programmatically calculate bids to reflect the value of each opportunity.

Use case: Gather customer insights from above

Individual infotainment centers that allow customers to watch movies and shows, listen to music and podcasts, order food and drinks, and even learn about their destination offer airlines a unique look into customers’ preferences and experiences. Collecting and understanding this customer information requires a data management system capable of collecting data from every channel across the customer journey (no pun intended), including web and mobile data at research and booking, app data from check in to luggage retrieval, and infotainment centers during the flight. By gathering data from customers' interactions with their infotainment systems during flights, marketers can better understand how customers use their systems to create better content, refine ad placements, and measure its influence on revenue streams

Maintain roadmap integrity and ship the best product

Brands want to create a superior experience for their users, which means they need a roadmap that delivers the best product to their customers consistently. For apps, that means minimizing reliance on third-party code that requires additional instrumentation and maintenance that may burden the user experience and divert engineering time.

By serving as a centralized data hub, a customer data platform is able to capture first, second, and third-party data through a single endpoint, then share it with multiple systems without placing additional tech strain on the app. This centralized data layer ensures the end-user remains unaffected as additional tools are introduced or updated, or as data schemas are changed. Minimizing dependency on third-party code allows product and engineering to avoid unforeseen SDK implementation and maintenance projects from marketing and other business stakeholders, so they can focus on building the best, most differentiated product.

Use case: Free engineering resources to develop customer features

For many people, losing their luggage during a trip is the worst thing that can happen. Everything else can go right during a customer experience with an airline, but if their luggage is lost then the experience is soured and can cause the customer to refuse to book with that airline again. To counteract this, many customer-centric airline brands can look to their mobile app offerings as a way to offer customers peace of mind when it comes to their luggage’s whereabouts.

However, creating this feature would require integrating data from many different systems, ingesting and appending the data to a customer’s profile, then connecting it to the app and messaging systems. Each tool requires an engineer to implement an SDK, then perform continued maintenance over the long term to make sure it continues to work properly. This can quickly amount to a mountain of technical debt and forces engineers to work on maintaining current function, rather than developing core features. Instead of implementing each vendor’s standalone SDKs, airlines can implement a CDP to serve as its central mobile data layer as an “API of APIs.” By using a CDP, airlines are able to collect and connect customer profile, location, flight, luggage tracking data from their first, second, and third-party sources to their app without having to worry about how integrating these tools will affect the customer’s in-app experience and minimizing maintenance.

Level 2: Insight and Activation

Objective:

Creating structured methodology for running test-and-learn processes and creating a culture of data-driven decision making. This may include leveraging non-marketing data.

Organization focus:

Measure ROI and customer lifetime value (CLV) impact of new marketing and customer experience initiatives.

Create a customer-centric product roadmap

Brands want to understand the mobile customer journey holistically and use this knowledge to prioritize future roadmap items based on customer needs, and demonstrate the business benefits of their product recommendations. Using a CDP enables them to combine mobile product, marketing, and purchase events through a single combined data set so that they can understand bottlenecks, identify key areas of improvement, and make better roadmap decisions.

Use case: Build the features your customers want

Travel sites are typically used by leisure travelers, but more and more business travelers are beginning to use the sites recently. In fact, some travel sites found that up to 20% of their bookings were coming from business travelers. This highlighted an important new persona that had very different requirements and preferences from the existing ones created for leisure travelers. By tracking attributes, past purchases, number of rooms and occupants, length of travel, and payment information, the travel site team was able to determine that it would be worth the time and investment to create business travel-specific features.  

One site used this data to launch a free enterprise booking platform with business-travel-specific features like connecting many individual profiles to one account, price per night limits, permissioning, and reporting features that allows companies to monitor travel spend by person, team, or department. By listening to customer feedback and using tracking to understand how the booking experience could be improved, travel sites are able to tap into an entirely new target market.

Augment and activate product, marketing, and customer service experimentation

Brands want to be able to not only know what customers are doing, but how they can improve customers’ experience while they’re doing it. Improvement can only come from experimenting with new product features, content, and workflows and using a CDP allows you to do experiment with different parts of your business more easily and quickly. A CDP reduces the data wrangling required for each experiment, reducing the cost of set up failure by making it easy to revert, and making it easy to create experiment segments and holdout groups on which to experiment. Experiment variants can be created based on customer attributes and behaviors across systems, including entry channel, initial product purchased, content consumed, current sales funnel stage, etc. Variant behavior is then gathered from source systems and third-party enhancements for analysis. Whether a brand is running experiments on purpose-built software or by hand, a CDP makes experimentation easier and more scalable.

Use case: Create user-centric searching

Search is at the core of every traveling site’s capabilities and is a key driver of business, so it needs to cater directly to customers’ needs. To create a user-centric search, the team at a room booking site collected user and host data with a CDP then fed it, along with additional data, to a predictive data model that estimated the conditional probability of booking. This model enabled the product team to tailor the search demographically to better suit user search preferences. For example, tailoring search for users in Asian countries by replacing the “Neighborhoods” feature with a “Top destinations” feature, led to a 10% lift in conversion among that specific user demographic.  

Level 3: Omnichannel engagement

Objective:

Optimize organization-wide initiatives using customer data and supporting marketing campaigns

Organization focus:

Optimizing marketing, digital advertising, and product-led retention/growth leveraging customer behavior, testing, and targeting across channels and touch points.

Enable segmented marketing

Modern marketers want to personalize messages by segment or persona to improve experiences and outcomes, but many legacy systems don’t collect and store the right customer data, at the right level, in the right way, at the right time. A CDP enables marketers to collect information about customer preferences and profile information to determine what information, content, or offers are most likely to appeal to them. By using rule-based segmentation, customers are automatically placed into audience segments comprised of customers with similar profiles which can be used to power marketing campaigns across channels, including search.

Use case: Showcase the amenities that matter

For example, using a CDP, hotel marketers can create rules based on customers’ preferences and history to determine which amenities are emphasized in search results, like access to a gym or an airport shuttle. This can be helpful for customers comparing several properties for a stay and offers the hotel a leg up on the competitition. Using segmentation also allows a hotel brand’s marketing team to send tailored offers based on a customer’s history, including previous purchases or stays, loyalty status, and room availability, ensuring every interaction is relevant to the customer.

Engage known and unknown customers at specific bottlenecks to increase conversion

Brands need to know who their audience is to market efficiently. That means being able to convert a customer from unknown to known, and tying their unknown data back  can identify customers who have not yet registered and trigger messaging campaigns to encourage registration to help take customers from unknown to known. This same messaging feature enables a CDP to trigger any type of messaging to customers based on app/web behavior or other non-email behavior loaded into a CDP. Identifying known and unknown product users allows for distinct messaging based on the brand’s end-goal for the customer.

Use case: In-app offer deals and registration perks

Airline brands can use their apps to send customers all sorts of different kinds of messages. In-app and push messaging can be especially useful for customers during their trip. Customer can be sent messages with information about check-in availability, departure times and delays, gates, lounge access, and more. These messages can also be used to drive future purchases by sending offers for flight deals departing from customers’ home airports. Customers that have not registered are prompted to do so by messaging in-app before they can take advantage of the perks offered by the app like check in, seat map, and luggage tracking.

Remarket to abandoned carts or inactive users

A CDP can capture visitor behavior on one company site or app and deliver related messages when the same visitor appears on any other company-owned site or app—even if that person was anonymous when they abandoned. A CDP can also read behavior history to flag inactive customers. In addition to triggering an email or push message, it can also trigger special messages when they appear on a different app/site or the same app/site. This is especially useful because the email addresses of inactive customers may no longer be valid.

Use case: Get customers to complete flight purchases

Getting a customer to complete a purchase in an industry that has volatile pricing, like airlines, is tricky because customers will often wait until what they deem is the last moment to purchase a flight in the hopes that prices will drop. Further complicating this purchase process is that every flight has a limited number of seats and so a desired flight can suddenly no longer be available to a customer looking to purchase a ticket.

Most airlines’ ticket process requires a customer fill out all of their personal information before displaying the available seat plan and final pricing inclusionary of any taxes and fees. This prolonged in-cart process provides a key bit of information for the airline, providing they can make the data actionable. When a customer fills out the forms but does not complete their purchase, the airline can use their CDP to collect non-sensitive data like a customer’s first name and email and add it to their abandoned cart segment.  Abandoned cart segments can be pre-set with rules to trigger an email to the customer with the flight details as well as the current number of available seats on that flight if the number of seats is lower than a predetermined number, say ten seats. If the available flight seats are greater than ten, this segment can be segmented further to receive an email with a different CTA that is more likely to encourage purchase. Depending on purchase completion after receiving these abandoned flight emails, further emails can be sent at future intervals leading up to the date of the flight.

Leverage paid media to drive conversions

Brands need to be able to use paid media efficiently to push customers stuck in their journey toward conversion. A CDP can address specific bottlenecks in the customer journey by syncing customer lists to paid media platforms. This is effectively the same as list selection for traditional marketing channels, with similar requirements for complex selections, access to full customer data, and extract creation. Customer lists can be selected based on user profile attributes and historical data available within a CDP. Unlike conventional (manual) methods, lists are updated in near-real-time to maximize relevancy and effectiveness.

Use case: Target smarter

Flight cancellations strand thousands of customers every day in unplanned locations, offering hotel brands an opportunity to sell rooms in surrounding areas. Hotels looking to target stranded travelers need to be able to predict where the two to three percent of flights are likely to be canceled in real time as cancellations happen. By gathering data from a variety of sources including public weather feeds, social media, and historical flight cancellation records into a predictive model, a hotel chain is able to predict where flights are most likely to be canceled. From there, this data can be fed back into their CDP to create an audience segment comprised of travelers in that area, which can then be forwarded to paid media platforms to deliver a targeted offer for travelers affected by flight cancellations.

All of this needs to be done in real time for it to be an effective strategy, but when done well, using a CDP able to process complex data in real time, can lead to significant gains. One hotel company was able to increase its year-on-year growth by 10 percent, in part thanks to this strategy.

Re-engage and find more of your best customers based on value-based criteria

Brands know that engaging existing and identifying additional customers that fit your ideal customer profile (ICP) is a solid growth strategy, but putting this into practice can prove difficult. Using a CDP enables you to select and deliver targeted messages to different cohorts of customers based on value-based scores by passing numeric attributes and customer IDs to paid media platforms, like Facebook. You can also create lookalike audiences using the value-based scores to find more customers like your current highest value customers with higher granularity than is available in the media systems’ limited data store.

Use case: Leverage loyalty status and balances to re-engage with customers

Hotel and airline companies that employ loyalty programs can leverage loyalty balances to re-engage customers with special offers depending on a customers’ reward status, trip frequency, and reward expiration. For example, customers close to reaching a higher loyalty tier or whose rewards are nearing expiration can be targeted with a campaign to book a trip to take advantage of their status. Similarly, customers known to travel to specific destinations frequently that haven’t made a trip recently can be attributed a value score to power destination-specific offer campaigns to encourage travel booking.

Suppress current users/customers from receiving irrelevant ads

Just as you can target exactly who sees an ad, a CDP can create and sync suppression lists to paid media platforms to ensure campaign dollars are not spent targeting the wrong people. Using custom rules set by marketers, the CDP can move individual customers in and out of suppression lists as their attributes and actions qualify or disqualify them from receiving certain ad content.

Use case: Suppress ads to customers that have booked

Because customers searching for travel deals rarely book on their first visit to a site, travel sites often have to use a variety of content and channels to encourage conversions over the course of several days or even weeks. As a result, paid media purchasing makes up a significant business investment for travel brands looking to convert as many customers as possible. The two key things to keep in mind for successful paid media purchasing is ensuring that the content is delivered to the right person and that it is delivered at the right point in their customer journey. If the wrong person receives ads, you won’t see a return on that investment, and similarly if the right person is targeted at the wrong time, you also will diminish your return. For example, if a customer has been researching trips to Napa the past few days, they may have been added to an audience for ads about flights and hotels to southern California or even vineyard tours. The moment that the customer books their flight and hotel bundle, however, they need to stop receiving ads for hotels and flights. Using a CDP can help travel brands update their targeting and suppression lists in real time as customers qualify or disqualify themselves from audience lists based on user attributes or actions. When the customer purchases their trip bundle, the purchase event is added to the individual customer’s profile, which then automatically moves the customer profile from an active targeting segment to a suppression segment. Because a CDP is flexible and creates audience lists based on custom rules and conditions, marketers can refine their targeting and suppression to fit their specific business needs. Suppressing customers that have already purchased allows the marketing team to use money that would otherwise be spent targeting them with paid media on additional trip offers or other customers that have not yet converted, yielding better results for the same or less budget.

Level 4: Continuous optimization

Objective:

Engaging and improving customer experience in real time

Organization focus:

  • Incorporating algorithms for continuous optimization, managing channel-neutral customer preferences, and omnichannel attribution.
  • Leveraging consistent data, technology, and processes across all channels to develop contextual customer engagement strategies that drive corporate objectives.
  • Calibrating marketing technology capabilities for continuous adjustment based on customer needs.

At the highest stage of maturity, organizations need to focus on creating better experiences for their customers on an ongoing basis. Using a CDP allows companies to make adjustments based on data and improves how brands track attribution. A CDP’s view of product, marketing, and service interactions—and customer purchases—provides the data needed to inform bottom-up multi-touch attribution models that measure the impact of touch points on business results at the user level. Many businesses consider these models to be more reliable than top-down mix models that rely on statistical methods to discern contributions but struggle to assemble the granular data needed to make them work.

Coordinate messages across channels

A CDP can be used an orchestration layer that provides an overview of all activity across all sources, and sets rules to direct messages based on complete information about the customer. Messages can then be personalized and delivered across all channels while maintaining a consistent customer experience. CDPs can also help customers set up cross-channel frequency capping, which limits the number of times an ad is scheduled to be displayed to a customer. Frequency capping reduces ad fatigue and ensures customers won’t grow tired of seeing your brand’s communication efforts.

Use case: Understand how customers are experiencing your property as they experience it

Hospitality companies looking to take their message coordination to the next level are using CDPs to collect and orchestrate data from a variety of on- and offline customer touch points throughout a customer’s visit. Disney World, for example, provides customers with a MagicBand that sends customer data, including their names, reservation information, and preferences, to touch points during their stay. All the while, the MagicBand feeds event data like purchases, check ins, ride access, and journey through the park, to further enrich their understanding of individual customers. This data can then be used to trigger notifications like updates on reservations or wait times for favorite rides while customers are in the park for a better, more personalized customer experience. Once customers’ trips have ended, this data can be used to fuel personalized offer campaigns across push, email, social, and other channels.

Recommend products and content based on individual behavior, profiles, or value

A CDP may ingest user scores from predictive models, whether they are homegrown or machine-generated, to provide the app or site CMS with real-time support for recommendations. These recommendations can include first product, cross-sell, and upsell. Because the CDP was also used to inform the models, these recommendations are based on data captured across every channel, not just the one the user happens to be visiting.

Use case: Hotel offers based on current stay

Customers are particular about their hotel experiences and so offering recommendations for future or additional purchases only makes sense. When customers book a stay at a hotel, their purchase preferences can be saved and added to their customer profile along with customer feedback, room and meal preferences, among other attributes. When a customer leaves, hotel brands can use this information to suggest a stay at another property within the brand that shares similarities with the customers’ previous stay. For example, a customer that traveled to a beach resort property in Mexico may receive email or in-app offers for some of the brand’s other beach resort properties in similar climates and with similar amenities. When customers book their stays, previous purchase information can also provide valuable guidance on which additional services may appeal to that customer, like spa services or tickets to events or attractions arranged by the concierge. A CDP can collect, track, and feed all of this data to the hotel brand’s machine learning model to guide recommendation marketing, then orchestrate it to the appropriate channels for message delivery.

Proximity-based marketing

Brands need to reach customers not only when their messaging is relevant, but also where it’s relevant. A CDP can ingest location information from web and apps, append it with signal from location data services, apply rules to uncover opportunities, and then trigger relevant messages. This extends far beyond conventional push notification systems and helps customers receive messaging relevant to their geographic context.

Use case: Upsell customers at the right time and place

Airlines are using proximity-based marketing to improve customers’ experiences and increase the value of each customer by using beacons to determine when customers arrive at the airport. With a CDP, airlines are able to connect individual customer’s itineraries and location data with in-app and push messaging to serve customers with long layovers or late departure times with offers to upgrade to business class or discounted entrance to the business class lounge. These offers are much more relevant and enticing when customers are in the context of the airport, making customers much more likely to purchase.

Augment and activate customer journey intelligence

A CDP can assemble a complete set of interactions between the company and each customer to create maps of customer touch points over time, with separate maps built for different segments, products, tasks, or locations. With this information, a CDP can identify the most productive paths and find the points where customers are falling out of the process.

Use case: Lower the bar to purchase

Using a CDP, airline sites can track customer interactions across devices as they open email promotions, search for flight options, compare dates and departure times, as well as fare classes to get a better understanding of what drives customers to book. For some airlines, that may be offering a 24-hour free cancellation period for indecisive customers or sending a small discount via email after a customer has viewed flights with the same departure, destination, and date range. If a customer has downloaded and uses the airline’s app, they can also be sent in-app or push messages when price decreases or when the flight is close to filling up.

Augment and activate next-generation loyalty programs

Legacy loyalty programs focused on serving promotions to repeat customers rather than driving loyalty. The next-generation of loyalty programs uses web/app usage data, in-store purchases, loyalty status, points balances, redemption, and in-store inventory to make the optimal offer for each customer. A CDP makes these data points available to systems that use predictive modeling and optimization to find the best offers while balancing customer goals, business goals, and business constraints, and can help these systems deliver relevant messages across channels.

Use case: Provide personalized offers and increase convenience

Instead of forcing customers to adhere to the standard check in times and process of going to the front desk, some hotel chains have streamlined this process for loyalty program members. Using the hotel’s mobile app, loyalty program members can check the status of their hotel room, check in via the app, use their app as a room key, and check out via the app. This makes the check in process much simpler and less stressful for travelers that may be arriving or departing earlier or later than the usual check in and check out times. Increasing the convenience of staying with the hotel can make all the difference for travelers with tight itineraries or who simply dread waiting in line to check in or out, making staying with the hotel in the future an easy choice. The app can also then be used to get customer feedback and create personalized offers based on customers’ preferences and travel habits. A CDP makes connecting room inventory, customer stay information, personalization, and app functionality and messaging simple and drives customer loyalty to new heights.

Manage profile information in real time across customer service channels

A fully-enabled CDP can ingest customer transactions on web, apps, call center, retail kiosks, and other channels in real time, as they happen. Using Identity resolution features, the customer can be identified and the information about the engagement can be used to inform channel systems of the customer’s specific preferences and history to guide current and future interactions.

Use case: Proactive trip issue resolution

Using a CDP to connect user and travel data can help strengthen customer loyalty and improve customer service in real time. For example, an airline passenger that has just arrived at their destination can’t find their luggage at the appropriate carousel. This can be frustrating and color the outlook of their entire trip, especially if they are on a schedule. The flight landing may have triggered an automatic email asking the customer for feedback at the exact wrong moment when the customer is most concerned about locating their luggage.

In conclusion

Travel companies have access to unprecedented amounts of customer data thanks to customers' engagement across devices and channels. This data represents an opportunity that travel brands would be remiss to not jump on—the chance to understand how different facets of engagements influence customers' journeys towards conversion and act on those learnings. But marketers are no longer dealing with a finite number of systems; rather, marketers are dealing with legacy systems unable to keep up with the ever-increasing number of SaaS applications that house and action data. Companies need a CDP that can not only help them overcome the customer data silos and unify their data from across their stack, they also need a CDP that is able to take their insight, orchestration, and activation to the next level by providing a way to create and maintain persistent customer profiles, execute experiments, improve targeting, and power acquisition and retention.

Finding the right CDP requires that marketers consider their current and future data goals and what kind of data they need to achieve them. Using defined use cases as the basis of their search for a CDP will ensure that marketers choose and implement the right customer data platform for their business' needs, making it a safe investment.

This guide has provided some of the most common use cases for travel companies at different data maturity stages, but there are still many more advanced applications for companies looking to improve their marketing and analytics ROI. mParticle is not only able to meet all of the use cases described in this guide, it is capable of becoming the customer data hub and agility layer that brands need to succeed in the digital era thanks to its ability to:

As the customer journey continues to fragment, finding the right CDP will only become more important. If you’d like to learn how mParticle can help you unify your customer data, boost engagement, and increase advertising and marketing ROI, get in touch!

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