The F2P “Magic” Formula
Here is the magic formula to turn water into gold!
As much as I wish that were true, no such things exists… However, I will share with you a pretty important set of terms that are crucial for understanding how to make a successful Freemium game.
In order to do so, I will compare F2P games with games that are sold using the traditional “Bricks and Mortar” approach, IE games that are sold at retail stores such as GAME. Games sold at retail are purchased en masse by distributors / shops from a publisher. For example, Sainsbury’s Supermarket may buy 500K copies of Call of Duty: Ghosts from Activision. As soon as the order is processed, Activision make money, usually earning the cost price they charge to the distributor. So if Activision charges £18 cost price and Sainsbury’s buys 500K copies then we can calculate revenue as:
Revenue = Number of Copies Sold X Cost Price
Revenue = 500K * 18
Revenue = £9m
Sainsbury’s then sell the game for more than the cost price, let’s say £24, meaning that they make a £6 mark-up on all copies they sell. Thus both Publisher and Distributor make money and the deal is fairly straightforward. There are caveats to take into account such as buyback terms, marketing and dev costs, but generally speaking the business model is something that is easy to get your head round. This means it’s fairly easy to model revenue forecasts based on previous sales records
All businesses are interested in ROI or Return on Investment. Let’s imagine that Call of Duty cost £4.5m to make (if only!) then the ROI (not taking into account costs) is 100% the original investment. Pretty damned sweet and many people will want to invest in a company that is capable of such returns, which makes share holders happy, which means more money for everyone at the company.
Free to Play games are a totally different beast, games are distributed digitally and anyone can download your game and play it. Of the total number of people that play it, it’s typical that 1% or less will actually pay any money (some games do better, but it’s rare). Of those people that do pay money, the rate of money people spend varies wildly from £0.69 all the way up to £10K a month (rare but some people do spend this amount of money). This simple series of facts already causes a lot of problems:
– The number of people that download the game is a huge unknown.
– The percentage of people that spend is an unknown.
– The amount of money a paying customer spends is unknown.
This already gives the finance team at an F2P company massive headaches. How on earth do you forecast the revenue for a game when there are such crazy unknowns!!?! Well that I won’t answer in this post, but this brings me onto the “Magic” formula that can really help.
Let’s break down the terms into each of their meanings:
LTV (180 / 360): The average Lifetime Value of a Customer, measured over 180 or 360 days. I.E. the amount of money a customer spends on average over 180 or 360 days.
eCPI: The effective (blended) Cost per Installation. I.E. The amount of money paid on average to acquire each customer that plays the game.
At it’s core, the formula is looking for two things, the amount a customer spends, and the amount it costs to acquire that user (through marketing / PR / organic downloads). So let’s take an example game, we’ll call it Match-3 Saga, and give it some fictional values.
LTV (180) = $5
eCPI = $3
Here we see that the LTV is greater (>>) than the eCPI, which is awesome! This means if I spent $1m acquiring customers, I would attain 300K users, and each customer would be worth $5 over 180 days. Thus means I make 300K * 5 = $1500K, or a cool $1.5m. In theory this would scale-up meaning that if I spent $10m acquiring customers, I would make $15m and so on. I have a 50% ROI!!!
The Tough Part
Of course, although the formula is easy to understand, making it so is not so easy. Firstly, how do we actually forecast / measure the LTV and eCPI?
It might seem counter-intuitive, but let’s start with the eCPI, as that is a lot easier to measure than LTV. In layman’s terms let’s imagine that I paid $1m and wanted to acquire $3m customers (installs). I quantify this by brokering a deal with an Ad agency such as Chartboost or PlayHaven who do a fixed CPI deal with me. They tell me (all fictional values) that if I spend $1m with them, they can guarantee 300K installs – meaning a CPI cost of $3.33. They acquire customer installs via an in-game mobile advert, a little bit like this one used by Clash of Clans:
Note that they guarantee me a CPI cost and *NOT* an eCPI cost. What’s the difference? Well if 1 million players download my game, it’s possible (probable!) that it will start climbing up the Top Free rankings. This means that people who never see adverts for my game may download it (known as an organic install). It’s also possible that through some viral functions in my game, players will attract their friends into playing the game with them, meaning that some people will download the game without me having to pay. So let’s say that I paid $1m but instead of 300K downloads, I get 700K downloads. This gives me an effective CPI (eCPI) of $1.43. It doesn’t take a rocket scientist to figure out that $1.43 is far less that $3.33, meaning that my overall ROI goes up significantly because of the cheap cost of my eCPI.
This is fairly straightforward, but in the world of F2P, there are very few constants and CPI’s (and thus eCPI’s) are no different. Whilst it may be possible to broker a deal for 300K downloads at $3.33, changing marketing conditions may mean that there is less inventory to buy at this price. If a competitor comes in with a similar product to my own, the CPI cost may go up. This means that on a month-to-month basis (if not more frequently), there are fluctuations in the CPI cost.
The number of organic installs I attain may also differ wildly depending on how popular / attractive my game is and how good the K-Factor (upcoming post on this soon!) is in my title.
This means that it’s important to review the CPI cost and eCPI cost regularly. Tolerances can be set for the value to make sure that alarm bells ring if acquiring users is too high. There is nothing worse than finding out tens of thousands of dollars per month are being spent on a game that is running at a loss!
Next up is the most complicated measurement in this formula, the Lifetime Value of a Customer. Let’s say that 700K people download and install my game. My aim is to find out as an average what each of those 700K customers is worth to the bottom-line of game performance. We have a set of problems to try to solve in order to do this:
– How many players spend? (Spending Percentage)
– How much does each paying player spend? (Average Revenue per Paying User)
– How many days does each player stay in the game? (Retention Rate)
– How often do players spend money?
– How many other players come into the game as a result of this player playing the game? (K-Factor)
When trying to forecast game performance, the truth is that it is VERY hard to predict all of these values. If you already have a successful game, it’s a lot easier as you can use real-life data as a benchmark. However, if you don’t, it’s very hard indeed.
The best way to succeed is to use Metrics.
F2P companies fire off events in their games to measure key metrics like these, helping them to work out a Lifetime Value prediction for their titles.
Lifetime Value generally comes down to one very important variable – Retention Rate. I.E. the amount of days a player keeps playing a game for. Players that play a game for a long period of time are more likely to spend money on it. Some players may play for over a year and still not pay a single penny, but most of the time, it’s a good assumption to make that players that play for long periods of time are the most engaged and thus the most likely to spend.
This is why it’s important to try to make games that are “sticky” and that make people want to come back and play them again and again. How do you do that? Well it’s not easy to quantify, but the simple answer is make the game FUN!
I could easily write and talk about this subject for hours on end. It’s very complicated and there are many pitfalls and hurdles to cross. I have deliberately not written about some key components to try and keep the scope of this post more manageable (and also, so there is still a need for me to be employed 😉 ). However, this is a good starting point to trying to understand how to measure success in F2P.
In general, to make a successful game, there are two “strategies” that work well:
1). Maximise Volume. If you can make a game that is capable of going viral and generating lots of organic installs, it’s easily possible to make a successful game. Candy Crush Saga is one of the best examples of this, with DAU numbers reportedly in excess of 20 Million (!) players on mobile alone. The eCPI on this game is very cheap, even though King spends a ton of money acquiring users. The overall LTV of customers on average is actually quite low for a F2P game, but if the LTV is far greater than the eCPI, a game is still a big success. And if you glance at the grossing ranks of Candy Crush, I’m sure you’ll notice how well it does.
2). Maximise LTV. The other (equally viable) way to make a successful F2P game is to maximise LTV. If on average every payer spent $50, then even if the eCPI cost was crazy high e.g. $40, a game would still be incredibly lucrative. A great example of this is Clash of Clans by Supercell. Clash of Clans does not have nearly a many DAU as Candy Crush and is never as highly ranked in the top free charts. This means that the eCPI is not as cheap. However, people who like Clash of Clans tend to REALLY like Clash of Clans and spend a lot of money in the game. Thus Supercell have had tremendous success despite not having as good an eCPI as Candy Crush Saga.
The difference between these two games is therefore that King want to try and get as many people to download and play Candy Crush period. Supercell on the other hand want to carefully find the right type of player that will become super-engaged with Clash of Clans. Both equally viable and lucrative strategies for success.
In theory this also means that one day someone might make a game that has a really high LTV and a really low eCPI. This game would make an absolute killing! However, given market trends this is very unlikely. If you look at a mass market casual game such as King’s games, they appeal to such broad audiences that it’s unlikely they can ever create a crazy high LTV game. If you think about it, there isn’t anything I can think of (physical item) that virtually everyone in the world has that also costs a lot of money. I am sure someone out there will prove me wrong, but I think it’s indicative of why no one will ever truly make a game that succeeds on both fronts.
180 / 360 days??
An obvious question when looking at LTV calculation is why I recommend measuring it over 180 / 360 days. The simple reason is that the App Store / Google Play Store platform as a whole is a bloodbath. There are over 800K apps on the App Store, meaning that to gain traction is very difficult. Even assuming a game will be successful for 6 months is in my opinion very optimistic (and dangerous!) unless you have lots of experience in the sector and a talented team of individuals working on a title.
A select few titles do manage to go over the 1-year mark, and some even go beyond that! I must give massive praise to a former employer of mine, GREE whose game Crime City has been in the top 25 grossing games in the US for over 2 years now – an absolutely phenomenal feat. However, this is a real rarity and the lesson is that if you want to forecast the success of a game, it’s better to try and find a way to get ROI as quickly as possible, than to have long term plans for world domination.