In the last 5 years, resale has completely disrupted the retail industry. In North America the resale market is expected to grow 8 times faster than the overall apparel market in the coming years. Globally, it is expected to grow 127% by 2026.

In 2022, 74% of consumers have shopped or are open to shopping for second-hand apparel.

Brands such as Levi’s, The North Face or Patagonia have all created their own resale corner on their website, distributing authenticated used clothes alongside brand-new ones.

If consumers are willing to wear used clothes, why won’t they buy pre-owned travel reservations?

Before jumping into speculations, let’s face it: a travel resale experience only makes sense for non-flexible reservations. Why will a customer sell its reservations if he can simply cancel it and get a reimbursement?

Non-flexible reservations play a key role in travel distribution optimization. By discounting reservations, travel operators such as hotels, airlines or railway companies decide to trade profitability for certainty of revenue. And it works well.

But non-flex bookings also have disadvantages.

Let’s take the example of an airline company. For a Paris-New-York flight, you can either book a flexible ticket for $900 or choose a non-flexible one for $800.

If the company succeeds in its overall forecast for that flight, it maximizes its revenue. However, if the demand for this flight turns out to be higher than expected, granting a discount for low-flex bookings is then an error, retrospectively.

The same applies to hotels, railway, ferries, etc.

But profitability is not the only problem. If a customer with a non-flex ticket cannot travel anymore, he does not have any incentive to notify the company. The result is simple: no-show.

Now let’s say that the same customer is willing to get compensation. He will call the company’s customer service multiple times and do its best to convince the agent.

If the company agrees to give him compensation, some money will be lost as the customer will be granted flexible benefits for free. If the company does not accept, its relationship with the customer will be negatively impacted.

To sum it up: non-flexible reservations could limit both profitability and customer satisfaction, but travel companies do not have any alternative now.

Let’s make it clear. A resale scheme can finally offer a viable solution to the various disadvantages of non-flexible reservations.

Not only it can, but it does. This is exactly what Ouigo is doing with remarkable success, using Fairlyne’s platform.

1. A resale experience can deepen customer relationships
   Going back to our previous example: instead of doing a no-show the customer can simply go to the airline website or app and register its ticket into the resale scheme.
   If a new customer is willing to buy back its ticket, the former customer will then receive a voucher. This is called the consignment model.
   Instead of having numerous and complicated calls with a dissatisfied customer, the airline company can now offer its customers a fair and seamless solution for their pain points. The relationship is healthier, and the booking experience is far better.
2. Resale can increase the operators’ margin
   We have seen how the consignment model works. Let’s focus on how it can create an additional margin. The mechanism is dead-simple: yield management. Now, all travel operators use revenue management systems. To make it simple, for an airline reservation the prices will go up until the departure date.
   In fact, a resale experience coupled with yield management is highly profitable. Customer A bought its ticket for $800, 30 days before departure. Now, customer B wants to buy it only 10 days before departure. The price for this ticket is now $1200.
   If the swap occurs, the airline company will give a $400 compensation (if the company chose to compensate at 50%) to customer A and receive $1200 from customer B, for the same ticket!
   The airline now enjoys its $2000 cash-flow for a single ticket and has managed to generate a $700 margin.
3. Resale gives access to valuable and multiple data
   Data is becoming the fuel of today’s economy, and the travel industry is one of the most advanced in this domain. By implementing a resale scheme, travel companies will gather valuable data that they did not track before.
   For instance, by allowing customers to register on a waiting list when a date is fully booked, a travel company can finally know what the unsatisfied demand for this day was and adjust its offer in the future.
   On the seller’s part, a travel company will also better understand the no-show reality of its non-flexible reservations: when do customers want to cancel? How many are there?
   These are only a few examples of data. Resale schemes tend to be also extremely useful to help product teams gather data to enhance the whole booking experience.

The question we asked ourselves: “why is the resale model currently not leveraged in the travel industry?” When digging into this question, it seemed to us increasingly awkward.

Implementing a resale scheme in the fashion industry is far from simple. Brands must organize their supply chain, manage their stocks, or even develop authentication processes. Of course, all these operations come at a cost, sometimes particularly high.

But above all, the fashion industry does not use yield management! Meaning that the profitability of brands’ resale corners only come from commissions on purchases.

Travel distribution has been disrupted many times in the past decades. From OTA to asset share models, new usages have challenged the way travel operators commercialize their offers, sometimes giving away an important part of their margin to third-party distributors.

With the new resale revolution coming, travel brands have at their disposal an incredibly efficient tool to reinforce their direct distribution and get their customers to love them even more.

With Fairlyne, we give you all the capabilities to do this on your direct channel. We have one philosophy: your terms, your brand, your customers, your data.