On Saturday 22nd of September, 50.000 tickets went on sale for Jochem Myjer’s whopping stretch of 36 shows in the Royal Theater Carré. At 10 AM, the moment the sale started, already more than 40 thousand people were on the GUTS Tickets website, eagerly trying to get their hands on precious tickets.

Roughly 200 minutes and an intense stress test later, the tickets were all sold out. This is no major surprise, considering the marketing effort that preceded it, both by the theater, Carré and Jochem himself, as you can clearly see:

Summarized translation of the tweet above:

‘4 more days until the sale for my long stint in Carré starts! #JochemInTheBigCity #RedLightDistrict #JochemInCarré2019’

Nevertheless, the demand for these tickets was, as seems to be the case for every Jochem Myjer show, impossible to satisfy. With 40.000 people on the website before the sale was live, and a maximum of 6 tickets per person, it was obvious that not everyone was going to be able to get their ticket. It’s never fun to disappoint, and the messenger (i.e. the ticketing company) often gets shot by those who miss out. This is fine, we are tough and have a strong support system of psychiatrists on stand-by at the office.

Jochem’s manager, Robert-Jan Veen gave an interview following the sale. When asked about the speed of the sale; he said the huge demand for tickets “exceeded all expectations” and unfortunately lots of people missed out, “simply because there was too much demand.”

The success and speed of the sale was picked up by pretty much every major news outlet in the country:

This publicity is great, and having a happy artist, venue and management were of course at the top of our priority list. Also, let’s not forget that more than 50.000 people will be happily experiencing Jochem Myjer perform in Carré, without having to worry about their tickets being fake or having to pay unfair prices.

At the same time, there were plenty of learnings to be learned — thankfully.

“Not all tickets are the same.” — Captain Obvious

The types of variable tickets and orders created some unforeseen troubles. To give you an impression, even though the tickets sold were all for the same theater and thus the exact same floor-plan, there were still more than 1100 ticket types for sale. This included differences in sections, seat types, but also champagne and food options. Such a variety leads to tricky calculations, because the system is constantly checking whether the selected options for every person on the site are still available. These situations are tricky to test for extensively, as you never know which kinds of combinations will occur.

While this is carefully thought out and built in, you only truly see how this plays out in the system once thousands of people start clicking. During the sale, we noticed that the certain components of the ticketing application were having a harder time to keep up than expected. (We are not yet sure whether this was due to the ticket types, but we are looking into the possibility.) In order to handle the demand, we scaled up our processing power immediately. To monitor the effect of the scaling we first had to slow things down for a bit. You can compare the construction of the ticketing system to that of a car. There are many different parts that have to function independently to make it all work. During this sale, most parts were running smoothly, while some less so. As with a car, it’s tricky to figure out what exactly is running sub-optimally when you are going full speed ahead, so you have to slow it down a bit or pull over.

The types of variable tickets and orders created some unforeseen troubles. To give you an impression, even though the tickets sold were all for the same theater and thus the exact same floor-plan, there were still more than 1100 ticket types for sale. This included differences in sections, seat types, but also champagne and food options. Such a variety leads to tricky calculations, because the system is constantly checking whether the selected options for every person on the site are still available. These situations are tricky to test for extensively, as you never know which kinds of combinations will occur. While this is carefully thought out and built in, you only truly see how this plays out in the system once thousands of people start clicking. During the sale, we noticed that the certain components of the ticketing application were having a harder time to keep up than expected. (We are not yet sure whether this was due to the ticket types, but we are looking into the possibility.) In order to handle the demand, we scaled up our processing power immediately. To monitor the effect of the scaling we first had to slow things down for a bit. You can compare the construction of the ticketing system to that of a car. During this sale, most parts were running smoothly, while some less so. As with a car, it’s tricky to figure out what exactly is running sub-optimally when you are going full speed ahead, so you have to slow it down a bit or pull over. The dynamic time shown in the waiting line unnecessarily scared a lot of people

When the system was facing peak pressure and we pulled back the throttle in order to support the high demand, the algorithms that determine the remaining waiting time did their job — a little too well. That means that some people saw their estimated waiting time rise from, say, 20 minutes to something in the realm of 500+ minutes, leading to a moment of understandable yet avoidable panic. This in turn led to lots of new support tickets and tweet-storms, ranging from friendly inquiries whether everything was going okay, to usage of swear words we had never heard of, to people offering to supply us with more server capacity (very funny, we’re good). The waiting line here actually did exactly what it should have done; it ensured that the back-end could process the number of requests in a controlled way. What can be better is the way that this information is communicated to the person in line, as to avoid creating a false sense of alarm.

If you look close enough, you can sort of tell on which day the sale occurred.

People make mistakes

With an insanely popular artist like Jochem Myjer, there is a very real sense of urgency when ordering the tickets. It’s no surprise that things can go wrong. For example: some people filled in the wrong phone number upon registering, and were then greeted with errors when they tried to buy the tickets and typed in their (correct) phone number. Even though this is a human error on the customers side, these people had trouble finding out where things had gone wrong and may have thought they were duped by an error in the system, only to give up buying their tickets. These instances provided us with valuable insights into how users can get themselves ‘stuck’ in the process and where we need to put in place extra guard rails to prevent them from slipping through the cracks.

With an insanely popular artist like Jochem Myjer, there is a very real sense of urgency when ordering the tickets. It’s no surprise that things can go wrong. For example: some people filled in the wrong phone number upon registering, and were then greeted with errors when they tried to buy the tickets and typed in their (correct) phone number. Even though this is a human error on the customers side, these people had trouble finding out where things had gone wrong and may have thought they were duped by an error in the system, only to give up buying their tickets. These instances provided us with valuable insights into how users can get themselves ‘stuck’ in the process and where we need to put in place extra guard rails to prevent them from slipping through the cracks. New issues require new responses

Scaling means learning means failing. Every new level brings with it new challenges. These new challenges require quicker and stronger responses on multiple fronts: tech, customer support, communication, etcetera.

This is very much the case for this sale; learnings all around.

Scaling means learning means failing. Every new level brings with it new challenges. These new challenges require quicker and stronger responses on multiple fronts: tech, customer support, communication, etcetera. This is very much the case for this sale; learnings all around. Scalpers gonna scalp — (or at least try to)

We were expecting the public announcements for a sale of this size with a ‘new and safe’ way of selling tickets to come across sounding as a challenge for those that like to make money reselling tickets. We have indeed noticed a couple efforts of people trying to sell sim-cards with purchased tickets on them for a mark-up. These tickets have all easily been flagged and will be made invalid.