Sunday, March 15, 2015

Scaling promotion codes

In our system a backoffice user can issue a promotion code for users to redeem. Redeeming a promotion code, a user receives a discount on his next purchase or a free gift. A promotion code is only active for a limited amount of time, can only be redeemed a limited amount of times and can only be redeemed once per user.

In code these requirements translated into a promotion code aggregate which would guard three invariants.

The command handler looked something like this.

Depending on the promotion code, we would often have a bunch of users doing this simultaneously, leading to a hot aggregate, leading to concurrency exceptions.

Studying the system, we discovered that the limit on the amount of times a promotion code could be redeemed was not being used in practice. Issued promotion codes all had the limit set to 999999. Just by looking at production usage, we were able to remove an invariant, saving us some trouble.

The next invariant we looked at, is the one that avoids users redeeming a promotion code multiple times. Instead of this being part of the big promotion code aggregate, a promotion code redemption now is a separate aggregate. The promotion code aggregate now picks up a new role; the role of a factory, it decides on the creation of new life.

The promotion code redemption's identifier is a composition of the promotion code identifier and the user identifier. Thus even when the aggregate is stored as a stream, we can check in a consistent fashion whether the aggregate (or stream) already exists, avoiding users redeeming a promotion code multiple times. On creation of the stream, the repository can pass to the event store that it expects no stream to be there yet, making absolutely sure we don't redeem twice. The event store would throw an exception when it would find a stream to already exist (think unique key constraint).

In this example, we were able to remove an annoying and expensive invariant by looking at the data. Even if we had to keep supporting promotion code depletion, we might have removed this invariant and replaced it with data fed into the aggregate/factory from the read model. Ask yourself, how big is the cost of having a few more people redeem a promotion code? Teasing apart the aggregate even further, we discovered that the promotion code had a second role; a creational role. It now helps us spawning promotion code redemptions while still making sure this only happens when the promotion code is active. Each promotion code redemption is now a new short-lived aggregate, while the promotion code itself stays untouched. By checking the existence of the aggregate up front and by using the stream name to enforce uniqueness, we avoid users redeeming a promotion code more than once. This has allowed us to completely avoid contention on the promotion code, making it perform without hiccups.

Monday, February 23, 2015

Domain Language: The Playthrough Bonus

Since online gambling has been regulated in Belgium, basically each eligible license holder has complemented their land based operations with an online counterpart. Being such a small country, everyone wants to secure their market share as soon as possible. The big players have been pouring tons of money in to marketing and advertising, it's everywhere: radio, television, (online) newspapers, bus stops, billboards, sport events, airplane vouchers - you name it. While regulations for land based casinos are very strict and almost overprotective, regulations for online play are much more permissive. This makes that online casinos can be rather aggressive acquiring new customers.

You will often see online casinos hand out free registration bonuses: "You get 10 euro for free when you sign up, no strings attached!". This makes it look like casinos are just handing out free cash right? We should all know better than that though.

There are always conditions to cash out a bonus. Bonuses come in different forms and flavors and preconditions to clear them vary wildly. The Playthrough Bonus is the favorite among players by far; it's straightforward and requires zero investment.

When you receive a Playthrough Bonus, you receive an amount of bonus money, which can be converted to cash by wagering it a specific amount of times. For example; you receive a Playthrough Bonus of 10 euro, which needs to be wagered 30 times before the bonus is cleared. This means that you need to bet 300 euro (10 euro multiplied by 30) in total to clear the bonus and to receive what's left off your balance.

So is betting the bonus amount 30 times realistic, or will you always close your browser empty handed with nothing to show for on your balance? The answer depends heavily on the payout rate. This percentage represents how much of the money that goes into the casino, is returned to players. In a formula, this is the wins divided by the bets. This percentage is generally a lot higher than most people expect. Casinos aim for a payout rate between 95 and 99 percent. They want to cultivate a long term relationship with happy and social customers, not clear your bank account as soon as you open the door. Note that the payout percentage is an average, not all games are a smooth ride. Some players like big wins, and big losses, while others feel more comfortable losing small, but don't mind winning small either. Casinos also prefer a smooth ride, especially when it comes to bonuses. They might even tweak games to have less aggressive, more equally distributed wins when bonus money is in play.

Now let's look at how much money would be left on our balance when we try to clear a Playthrough Bonus of 10 euro with a playthrough of 30 and a payout percentage of 98.

I defined two records (excuse my primitive obsession). First a Bonus record that contains an amount, a balance, the total amount of bets and a playthrough. A few functions are associated with the Bonus record; they allow the bonus to be created, to bet, to win, to check if it still accepts bets and to check if the bonus has been cleared. The second record, the GameSettings, define the payout percentage and the stake of a bet.

After defining these structures, I defined a function that recursively keeps playing (bet and win) until either the bonus is cleared, or the bonus no longer accepts bets (out of money).

When we run this function we know the answer to our question. On average, we will clear the bonus with four euro left on our balance.

When we turn down the payout to be one percent lower, we only have 1 euro left on our balance. When we turn it down even more, there won't be anything left.

Given a few parameters which should be available to you (bonus amount, playthrough and even payout percentage), you can calculate how feasible it is to clear a Playthrough Bonus. Unless variance is on your side, I guess it will rarely turn out to be a lucrative grind.

Sunday, February 15, 2015

Side by side

This week marked my first year at my current employer. While that event went by rather silently, one year in, a few of my observations are finally shaping up to be cast into writing.

Where I used to work in the typical battery cage, I'm now part of a team of just four people, having the luxury of a big dedicated room to ourselves - a whole floor actually. The room is set up almost symmetrically; two desks on one side of the room and two more on the other side, with quite some space in between. Having only four people in the room makes it easy to casually throw something at the group - be it a question, a critique or a random idea.

I made good use of this perk early on, but noticed that I would too often find myself amid a Mexican Standoff. We would often get ourselves into discussions that quickly turned into a my-opinion-versus-your-opinion and would lead nowhere.

It didn't make sense how I got myself into this situation time after time, until I read somewhere how to approach petting an unfamiliar dog.
Our species have more in common than you would think. Our shared history of pack hunting has made both our species highly social and interdependent.
For example, when you approach an unfamiliar dog, you shouldn't pet him on the head since this can be very threatening. It's better to approach him from the side to rub his ears, neck or back. This behaviour is an evolutionary remnant of pack hunting; members of the pack would rub each other's shoulder constantly chasing their next meal.

It occurred to me that the cause of our unproductive discussions might be as simple as our desks being in an aggressive position, desk-to-desk or face-to-face.
Looking back at my previous jobs, I found no precedents of having discussions in this position. The horrors of the open plan had always forced me to either walk over or to find a meeting room.

But when I look at my personal relationships and discussions, I find more situations that confirm this theory. When going for drinks, most of my friends prefer a noisy and crowded bar, which force you side-by-side just to make yourself understood. Even when communicating with my girlfriend, it's not the cliché tete-a-tete dinner dates that yield the best conversations, it's taking a walk, long road trips or even cooking together.

When it came to avoiding these unproductive situations at work, I now carefully consider which things I can just throw out there, or which things require a side-by-side approach. Even when you got yourself in trouble face-to-face, you can still guide things into a more constructive direction by changing the situation.

Getting side-by-side shouldn't be too hard in a professional environment. Both pair programming and whiteboard sessions (or one of its more exotic evolutions - model storming, mob programming etc) are ingrained in most places now.

Evolution has wired our brain in a way that makes being side-by-side, preferably chasing the same goal, extremely amicable. Although we're no longer hunting for food, we still find ourselves chasing different means of prosperity and success. Just like before, it's still the case that we're at our best as a team, side-by-side, in pack.