What dynamic pricing leaders can teach the travel industry

Dynamic pricing promises major change and is already being used by a variety of brands says a new report.

Brands are waking up to the possibility of dynamic pricing and driving rich rewards from doing so finds the new Dynamic and Personalized Pricing report from EyeforTravel, which is free to download now. Dynamic pricing, the process of using data to more accurately segment consumers and automatically offer them differentiated prices based on various factors, is being deployed from both within and outside the travel industry. Early adopters include many players in the airline industry, Airbnb and Amazon. So, with so many waking up to dynamic pricing, what are some of these early adopters doing and what are the main lessons?

Airbnb has already built in sophisticated dynamic pricing algorithms to those hosts that select to use them. Property owners can choose to set a price manually or utilize the dynamic pricing algorithms provided by Airbnb to automatically determine the cost per night. The three key factors involved in the automated pricing of Airbnb space are seasonality, day of the week and special events. On a broader level, the company reputedly works across more than 70 categories to create the price. It lists the following as some of those criteria:

•                     Lead-times

•                     Search behaviors both within and outside the listings market, with prices rising as search popularity increases

•                     Seasonality

•                     The popularity of the listing at any given time, including how many users view and their dwell time on the listing

•                     Listing amenities, such as WiFi, air conditioning or a pool

•                     Number of bedrooms and bathrooms.

•                     Prices paid for bookings in the past with adjustments made if host-set prices differentiate from the algorithm

•                     Host review scores over time.

This allows Airbnb to maximize bookings for all available dates. The lesson here is to monitor the widest possible purview of variables when considering pricing and to take special consideration of events occurring in destinations.

Amazon has also built heavily on its data advantage, making it a leader in dynamic pricing in the retail industry. Amazon has access not only to one of the world’s largest online marketplaces but also an entire ecosystem of sellers who it can monitor to find bestselling products and pricing information.

This allows it to find key products that bring people to its site and price them in a manner that brings in a sale but also reinforces the customers view of Amazon as the best value marketplace. Meanwhile it looks for price inelastic goods and maintains margins on these to make up for low margins or even losses on other products.

Amazon does this through regular pricing adjustments that sometimes are made on an hourly basis depending on demand.  

It was also one of the first to move into the realm of personalized offers. The user is confronted with suggestions related to what they have purchased and what they are currently looking at. These suggestions are dynamically put together based on various factors such as past purchases the user has made, as well purchases that others have made with a similar interest profile.

The core lesson here is to think about how pricing can impact long-term loyalty and price aggressively to draw in first-time customers. 

Although more segmented pricing has potential rewards, it also does not come without risks. Tinder, the popular social match-maker and a fast-growing player in the platform economy has applied a pricing practice that may have been correct from a data perspective but came unstuck against legislation and consumer rights.

As with all pricing, it is a case of supply and demand, with older consumers more willing to pay for the service and were thus being charged more for their Tinder Plus and Tinder Gold services. Older consumers are operating from a smaller pool of potential partners, frequently have higher earnings or wealth and are less common on the Tinder app, making finding a partner harder, thus meaning it makes more sense from a user perspective to pay to level the playing field and improve their probability of generating successful matches.

However, Tinder ran afoul of ethics and the law with their strategy, settling a class action lawsuit for USD17.3 million in January 2019 through the California lawcourts.  

It will be paramount for travel companies to ensure that their pricing practices are based on segmentation using context and behavior, and on supply and demand, as opposed to factors which can be legally challenging due to being discriminatory.

To find out more, download the Dynamic and Personalized Pricing report for free now and receive:

• Detailed analysis from a report written by a pricing expert and consultant.
• A breakdown of modern pricing practice in travel to help you get to grips with the current environment and how it is changing.
• Key rules to create your own advanced pricing regime.
• Real-world examples of advanced pricing practices from Airbnb, Amazon and more.
• How to integrate dynamic pricing into increasingly complex distribution networks.

Why dynamic pricing will transform travel distribution

Smarter pricing structures will allow travel brands to create more relevant prices for their customers, boosting revenue and loyalty finds a new report.

Pricing within the travel industry is evolving to match consumers and what they are willing to pay far more accurately as a result of a better understanding of impacting variables and more ability to deploy granular prices across distribution networks. The upshot of this, according to a new report, is that travel brands can continuously adjust their pricing to suit their customers and thus maximize the revenue they get for each route or room. To explore the step change in capabilities and how they can be implemented, you can download the Dynamic and Personalized Pricing report completely for free here now.

Currently, most revenue management systems (and revenue managers) take into account things such as historical demand curves, events and conferences, seasonal factors and overall route capacity, etc. However, with the changing ability of systems to factor in a greater depth of information in very short timeframes and from an almost unlimited number of sources, the calculation of demand is starting to change.

Firstly, brands can bring in more information surrounding the destination and target market. For example, for a short leisure trip, a system could factor in the weather at different locations and use that as a component of the algorithm to calculate anticipated demand. Then there are customer personas that are growing increasingly detailed and only really limited by the amount of available data.

This is allowing micro-segmentation and fundamentally changing the way offers are created to the point where each individual could receive a different offer when considering all the possible combinations.

With micro-segmentation, the industry is moving away from the simplistic leisure versus business traveller divide and the other common segmentations that have been used to date. The idea is to apply a finer grained mesh – perhaps with dozens or even hundreds of micro-segments as opposed to five or ten. With this systematic approach, applying factors such as willingness to pay and demand-based factors to individual offers provides considerable price-point differentiation.

The fundamental processes can also be applied to ancillaries, in what is termed complete offer creation that creates the next level of differentiation. Complete offer creation involves bundling additional products that are probabilistically calculated to be desired by the consumer. In the case of the airlines, this could mean an offer in which the travel, wireless connectivity, a checked bag and a warm meal is included in the overall offer price. If the brand can add value to the customer’s request by addressing an additional need or desire, and the offer is within the consumer’s willingness to pay, an expanded offer can not only generate additional immediate revenue but also a higher level of customer satisfaction and potentially additional follow-on revenues.

This creates a huge range of possible combinations that means, effectively, pricing is coming down to the individual. The value created from this investment into more complex and granular pricing is leaps in revenue through maximizing the pricing level in each demand period and minimizing the amount of inventory left unused.

To find out more, download the Dynamic and Personalized Pricing report for free now and receive:

• Detailed analysis from a report written by a pricing expert and consultant.
• A breakdown of modern pricing practice in travel to help you get to grips with the current environment and how it is changing.
• Key rules to create your own advanced pricing regime.
• Real-world examples of advanced pricing practices from Airbnb, Amazon and more.
• How to integrate dynamic pricing into increasingly complex distribution networks.

Measuring and making the most of consumer data

Travel brands are sitting on huge value in their databases but are yet to unlock its full potential, which will be game changing

Virtually every consumer-facing travel brand is capturing critical data constantly from their site visitors but many are struggling to maximise its value says EyeforTravel and Datumize’s new Understanding Customer Behaviour Through Demand-Based Analytics white paper. This is because of the reams of information that are being constantly created across multiple channels and the need to be always on and live. These factors often prevent travel companies from getting down to the key metrics that matter and being able to fully extract and study them.

“Travel companies normally only have access to converted sales and aren’t able to track all the requests that customers are making though channels,” explains Datumize’s head of marketing Carlota Feliu.

“Some of them they can track, for example, through their own website. But the vast majority they are not capable of tracking this data with the technologies they are using. Everything that you want to do in demand forecasting starts with good data and good knowledge of your customers – without this, you won’t be able to understand demand, predict it, or increase it,” says Feliu.

She points to several key areas where brands can start to interrogate their data:

Inventory: Do you have the right offer at the right price in each area?

Availability: Do you have the stock available to action all requests, and in the right price range?

Experience: Are all software links in the chain performing as they should for a quick, smooth booking?

Vueling Airlines, a Spanish, low-cost provider, has around five million search queries a day, 50% of which come directly from customers and 50% from online travel agencies and other tour operators. But since its business goal is to answer all enquiries for a flight in a second or less, it was struggling to store and make use of all this demand data.

Jonathan Guerrero Corcho, innovation manager, explains that a Datumize solution – which monitors everything without adding any code to the main process or slowing anything down – means that the business can now understand more which kinds of routes and dates are most in-demand, with negligible noticeable effects to end users.

“We can see if a route is being asked for more times than we are operating on for those days and we can not only adjust the current schedule but we can adjust the next schedule,” he says. “We can say ‘this route is better to operate on Tuesday than Monday, as the numbers are saying that this route is more requested on Tuesday.’”

This kind of learning is particularly important for a business that does not operate the same flights each day, but a limited number of times a week.

For more case studies of brands that have driven performance gains from better utilisation of data, download the free white paper now.Demand-based analytics promise a step-change in travel brands’ capabilities, unlocking huge insights that will allow brands to better target consumers, build superior products and adjust faster to changing patterns. To understand how to unlock the value contained in demand-based data, download the Understanding Customer Behaviour Through Demand-Based Analytics white paper now! It includes:

• Real-world examples and case studies
• Industry survey data
• Data-based techniques and areas of focus that can improve business performance immediately
• Expert insight.

This white paper features insights from:

• Europcar
• IHG
• The Travel Corporation
• Thomas Cook Hotels & Resorts
• Vueling
• W2M.

Click here to download your copy of the white paper for free!

How simple measurements can make a big difference to travel brands’ performance

Travel brands can make huge leaps in performance through relatively simple measurements and metrics finds new white paper

Rigorously monitoring even the most basic of demand-based data can make a critical difference to overall performance says EyeforTravel and Datumize’s new Understanding Customer Behaviour Through Demand-Based Analytics white paper, which is available to download now. The paper finds tracking own-site searches, business-to-business requests, drop-outs across the funnel and service availability can result in major uplifts to bookings.

“All companies know what they sell – but they don’t know what they don’t sell,” says Josep Maria Gomis, Travel Solutions Architect, at Datumize. He suggests that travel brands can grab uplifts in conversions quickly by monitoring simple elements such as geographies for where requests are received. “When we deployed our solution with one of our clients five years ago, for example, we found that the first region they received requests for was Spain.” The sales director knew this already, and he was also blasé about the discovery that the second most common type of request was for inventory in France. But the fourth region – to his astonishment – was China. “He said – ‘you are wrong – we are not selling in China!’” says Gomis. “And we said, ‘you are not selling because you don’t have a product, but this is the fourth most popular market for which you receive requests. You should have a product for them! We consider this a lost sale.’ And after a month they started offering products for China. Profits went up.”

Another way of finding these lost sales and improving business performance quickly through monitoring requests is looking at the languages used: “One of our customers discovered that people were looking for products on its Polish webpage but typing in queries in the German language,” says Datumize founder Nacho Lafuente. “This might seem like a stupid case but it’s tens of thousands of euros that you are not converting. If you are looking for ‘Crete’, a Greek island, on a Polish page, then the result is not found.” Analysing requests can find that some customers are not finding products that you have available because of a language gap. Not every destination is the same in every language, which leaves an obvious measurement metric to judge whether the offering matches what your clients are searching for.

Demand-based analytics create opportunities to match a brand’s product with the true picture of what customers want and are looking for.  

Measuring relatively simple metrics, such as those above, also gives brands an opportunity to search for patterns and critically when anomalies occur in those patterns. For Spanish tour operator W2M, which receives 250 million availability requests per day, finding the mismatches has been a key driver of business performance. W2M has set up some automatic alarms to flag up higher-than-expected error ratios, so the IT team can respond immediately. “We went from a 10% level of error to under 5%,” says Ernesto Sigg Rodríguez, head of clients and supplier performance. “I would say that represents between 5% and 10% growth in terms of sales,” which has made major difference to his business where margins are very slim.

Making dynamic changes and working across a business to implement them requires constant inputs, says Lafuente. “When you are dealing with a highly competitive business such as travel, margins are so low that they need to squeeze [every] euro,” he says. “It’s not only about having a general understanding or perception of how things are going. You need to photograph every single minute and have alarms for things if they break certain thresholds.”

Demand-based analytics promise a step-change in travel brands’ capabilities, unlocking huge insights that will allow brands to better target consumers, build superior products and adjust faster to changing patterns. To understand how to unlock the value contained in demand-based data, download the Understanding Customer Behaviour Through Demand-Based Analytics white paper now! It includes:

• Real-world examples and case studies
• Industry survey data
• Data-based techniques and areas of focus that can improve business performance immediately
• Expert insight.

This white paper features insights from:

• Europcar
• IHG
• The Travel Corporation
• Thomas Cook Hotels & Resorts
• Vueling
• W2M.

Click here to download your copy of the white paper for free!

Why demand-based data matters

Demand-based analytics promise a step-change in travel brands’ capabilities, unlocking huge insights that will allow brands to better target consumers, build superior products and adjust faster to changing patterns says new research

Demand-based data is increasingly important and can allow travel brands to become both more agile in the short-term and better prepared for long-term trends according to the new Understanding Customer Behaviour Through Demand-Based Analytics white paper from EyeforTravel and Datumize, which is free to download now. Looking at ongoing demand patterns will arm travel brands with a wide-range of capabilities, such as more responsive marketing, better-adjusted pricing, more personalised products, superior forecasting capabilities and increased planning capabilities.

This kind of data is of utmost importance to a youth brand like Contiki, part of The Travel Corporation’s agglomeration of 30 international brands. Raj Dhawan, senior executive, technology at The Travel Corporation, explains that understanding and forecasting demand is critical to keeping Contiki’s catalogue of offerings appealing and up-to-date.

“The one area that we look at regularly is search terms on our website – the cities and countries where people are searching,” he explains. “That may result in us culling some trips and destinations or increasing our inventory on those destinations.

“There are areas and destinations that are hot in the market versus those that are not, and every year that changes a bit. Based on that, our product changes to some extent, with variations that could appeal to the audience that we have.”

Building on this monitoring, the business is experimenting with a machine learning pilot to give these learnings a concrete and immediate use: Depending on patterns of searches, for example for a particular area or cost bracket, Contiki customers will see a website personalised for their type of customer.

“When people search for certain terms, the website is curated based on this,” says Dhawan. “That’s something we are piloting, and that uses machine learning and the search product on the website.”

This is just one example of the insights from brands featured in the white paper. Download the full research now to get more from industry leaders, including Europcar, IHG, Thomas Cook Hotels & Resorts, Vueling and W2M.

Demand-based analytics promise a step-change in travel brands’ capabilities, unlocking huge insights that will allow brands to better target consumers, build superior products and adjust faster to changing patterns. To understand how to unlock the value contained in demand-based data, download the Understanding Customer Behaviour Through Demand-Based Analytics white paper now! It includes:

• Real-world examples and case studies
• Industry survey data
• Data-based techniques and areas of focus that can improve business performance immediately
• Expert insight.

This white paper features insights from:

• Europcar
• IHG
• The Travel Corporation
• Thomas Cook Hotels & Resorts
• Vueling
• W2M.

Click here to download your copy of the white paper for free!

Are travel companies ready for the digital revolution?

Travel companies are struggling to transform themselves for the digital age, with digital transformation, technological and data siloes and internal data quality their top three internal challenges

According to the World Economic Forum, digitisation in the aviation, travel and tourism industries is expected to create up to USD305 billion in value through increased profitability up to 2025. This should make digitisation a key priority for the travel industry, however, achieving a strong platform to do so is proving difficult for travel brands. This is one of the findings from the new Understanding Customer Behaviour Through Demand-Based Analytics white paper from EyeforTravel and Datumize, which is free to download now.

In a major survey of the industry featured in the white paper, travel suppliers (accommodation, car hire, cruise, ground transport, airlines & tour operators) said that their greatest internal issue is digital transformation (34.4% of respondents). This is followed by technological alignment (30.5%) and the perennial concern of data siloes and internal data quality (29%), both of which are critical to achieving a digital brand fit for the 21^st Century.  

“Our data and the industry interviews conducted for this white paper suggests that a significant proportion of the travel industry is struggling to construct the necessary infrastructure to create strong digital brands,” said Alex Hadwick, Head of Research for EyeforTravel. “Stringent data practices increasingly underpin the modern travel sector, which is emphasised by our finding that the most important trend for travel suppliers right now is GDPR and cyber security, followed by big data and analytics. There is huge value to be unlocked but brands need to get the basics right first by complying with regulations, creating secure, structured and accessible databases and measuring the right metrics.”

The research recommends that brands move data into the cloud and focus on getting a picture of total demand. This is the approach of hotel giant IHG: “Before we had a big data platform, we weren’t able to store and analyze our availability requests,” said Jeff Garber, vice president of revenue management systems at IHG during the EyeforTravel 2018 Digital Data Europe conference. “We had a lot of information about reservations, and customers that had made reservations. As we bring more data into that big data platform, we can really understand the choice model. Our next step is merchandising and being smarter about what people aren’t buying so that we can reduce the clutter we are showing to them.”

Demand-based analytics promise a step-change in travel brands’ capabilities, unlocking huge insights that will allow brands to better target consumers, build superior products and adjust faster to changing patterns. To understand how to unlock the value contained in demand-based data, download the Understanding Customer Behavior Through Demand-Based Analytics white paper now! It includes:

• Real-world examples and case studies
• Industry survey data
• Data-based techniques and areas of focus that can improve business performance immediately
• Expert insight.

This white paper features insights from:

• Europcar
• IHG
• The Travel Corporation
• Thomas Cook Hotels & Resorts
• Vueling
• W2M.

Click here to download your copy of the white paper for free!

Hotels are losing out on metasearch

Hotels need to improve their competitive performance and monitoring of metasearch channels finds new research. 

Hotels aren’t bidding enough on metasearch sites or monitoring the space effectively, affecting their bottom lines and brand loyalty, says EyeforTravel and Fornova’s new The State of Hospitality Distribution: Metasearch white paper, which is free to download now.

Data from the white paper drawn from nearly 10 million searches on meta engines in 2018 reveals that just 34% of bids monitored featured a direct link posted by a hotel.

Across March, April, and May 2018, less than a third of the shops made by data partner Fornova on meta sites had a direct hotel option being displayed. This rate reached a low of 18% in March 2018 and rose to a high of 28% of shops made in May. Ranking for hotels was also low on the sites monitored, with hotels’ bids coming in at the sixth-ranked option on average in May 2018.

This is allowing OTAs to dominate the space, one which is increasingly crucial for attracting consumers. More than 90% of consumers report using meta sites for price comparison when booking accommodation but the vast majority of bids and outbound traffic from these hugely popular sites, including Google, TripAdvisor, and trivago are benefitting Online Travel Agencies (OTAs) finds the white paper.

Furthermore, hotels are being undercut by both their contracted OTA partners and by third parties working without agreements. The research finds that contracted OTAs are undercutting by an average of 5-6% on meta sites and by an even higher 10-11% by non-contracted OTAs. This means the consumer, who is largely driven by value, is frequently seeing better rates than hotels direct bids, meaning wasted spend and lost data and brand loyalty. When the consumer is searching 14 days or less out from their stay, the research found that they would see a lower bid the majority of the time from multiple actors.

This is a battle for hotels as the average hotel usually falls short of the labour and technological resources to do so. Furthermore, as Fornova CEO Dori Stein points out, there’s no way for a hotel’s revenue or e-commerce manager to know what meta engines are showing their guests in different countries because of the varying IP addresses. “Unless the hotel has a way to monitor its top inbound source markets, it’s a losing battle,” he added.

Chatchai Pongprapat, assistant vice president, revenue management  at Dusit International appreciates the issue, “There is crossover between all of the different players on various channels and that makes it very hard to maintain rate integrity,” he said. The company’s solution has been to partner with Fornova, which polices the rates and helps Pongprapat to maintain rate integrity and partner behaviour.

More effective monitoring and activity on metasearch sites can have a very real effect on the bottom line: “We felt we weren’t featured very visibly as their models evolved and so we hired a third party that could constantly monitor our meta campaigns and make them effective programs,” said Preferred Hotels & Resorts, Global Vice President, Revenue Optimization, Rhett Hirko. Meta-driven bookings jumped 30% after Preferred began working with a third-party partner to manage meta campaigns. They determine the best ROI from each individual meta site based on the budget Preferred dedicates to the channel, as well as meta sites’ performance for Preferred based on click-through volumes. Hirko noted that in terms of how cost effective the move was, “it took a while to tweak the program, but we’re definitely getting good returns for our investment.”

For more on how metasearch is shaping the digital accommodation market, download the free white paper now.

This white paper, made in conjunction with Fornova, gives real-world data on hotel, wholesaler and OTA bidding strategies, alongside consumer behaviours, and meta success metrics. Use these to understand the channel, the competitive landscape and build a winning strategy!

Learn the following from this white paper:

• The state of the metasearch market.
• Market penetration rates among consumers and hotels.
• Consumer behaviours on metasearch.
• OTA bidding strategies.
• Techniques to succeed on metasearch.
• The outlook for meta.

Click here to download the white paper for free now.