CPI – The Business of Social Games and Casino

Five Steps to Reduce Churn

I have wrote and spoken several times recently about how increasing user acquisition costs are impacting the social game industry, particularly social casino, and some strategies to offset and even capitalize on this trend. One of the best ways to combat this problem is to focus your resources on reducing churn rather than acquiring new users. As the cost of acquiring a user increases, the cost of replacing that user also increases. While companies devote ever larger budgets and build bigger teams for user acquisition, they fail to devote comparable resources to retaining the players they already have. Moreover, in the social casino space, players often play 3-5 apps, so the less they play your title, the more they are playing a competitor‘s slot.

I recently came across a blog post, “How to reduce Churn by building a bulletproof retention process” by Andrew Tate, that lays out five ways that you can reduce churn. Tate starts with the example of Burbn, a Foursquare clone that had a huge churn issue. Using analytics, the team saw that users found it too complicated and were using the app to post pictures rather than check in. So they modified the app based on this data to reduce churn and renamed it Instagram. Let’s just say it worked out okay for the Burbn team. This example shows how a focus on reducing churn can be the difference between failure and billions.

Focus on the small gains

The first step to combating churn is to take a lot of small steps rather than looking for the magic formula. One change or feature is not going to improve retention 50 percent. If you can reduce churn a few percent every build, you eventually will get negative churn rather than seeing your game lose all its users and revenue. Thus, it is more critical to build a process that always is working to reduce churn rather than fire off a churn reducing feature and then go on to your next KPI (key performance indicator).

Define goals

To create the process discussed above, you first need to set goals. As with all goals, they need to be measurable and clearly defined as well as time based. Reducing churn is not a goal, but reducing churn by 50 percent in three months is a goal. Then you should break this goal into sub-goals, with Tate suggesting

Reduce short-term churn by 20 percent
Reduce medium-term churn by 20 percent
Reduce long-term churn by 10 percent

With goals in place, you can track your progress as you create individual AB tests and set an end-point for the process. This technique aligns the entire team on a visible and understandable goal. Continue reading “Five Steps to Reduce Churn”

Dawn of a new era of in-game advertising

Last week I wrote about the rising cost of paid user acquisition. this week I want to dive deeper into how advertising can help mitigate this issue. Ironically, my former employer, Zynga, made a creative move recently in this direction. Zynga announced SponsoredPLAY, an in-game advertising product where sponsors offer special content or levels that enhance rather than detract from gameplay. I do not know enough about the offering to comment on it directly but it shows how game companies need to think to thrive in the coming age of higher cost per installs.

Why advertising is the natural hedge

Last week I discussed the fundamentals of the paid user acquisition space and why it pointed to dramatically higher CPIs (cost per installs) in the near future. There are several options to cope with this situation but one of the strongest is to increase advertising revenue in your game. Once advertising becomes a significant component of your revenue mix, any increase your CPIs due to higher advertising rates should also generate additional ad revenue on the other side of the equation. The more CPIs increase, the more your ad revenue increases.

Advertising 2.0

Unfortunately, increasing advertising is not as easy as putting banner ads in your games. Last January I wrote how consumers are much savvier now and expect their communications with companies to be as smart and sophisticated as they are. The same holds true for advertising.

For advertising to work in 2015 and beyond, it must achieve certain functions that most ads do not

Targeted: The advertising should be relevant to the customer. A 50-year-old man should not see an ad for a Miley Cyrus concert.
Contextual: The advertising should fit naturally with the overall game experience. You should not be playing Game of War and all of a sudden see an advertisement with pink fluffy unicorns dancing on rainbows.
Beneficial: Rather than having the advertising annoy the player, enhance their experience. Use it to deliver benefits that they would not normally receive.
Segment: You do not have to show ads to everyone. You may only want to show ads to non-spenders. If the ads are truly beneficial, you may actually want to show them more frequently to spenders. The important thing is to create as small clusters as possible and then create an advertising strategy that optimizes the value for that cluster (IAP [in-app purchases], subscription, advertisements).
Multiple formats: You should not limit your advertising strategy to one type of advertising, just as you would not limit your in-app purchases to only allowing players to buy chickens. Different types of ads will work in different parts of your game and some types will be more relevant to certain users. Use the full arsenal of advertising to optimize your player’s experience and the revenue they generate.
Flexibility: The digital marketing world is still in its infancy. Rather than have a laser focus on one ad unit or strategy, keep abreast of developments in the industry and continually evolve your strategy as best practices evolve.

Continue reading “Dawn of a new era of in-game advertising”

Why your game’s metrics mean nothing

From the beginning of time (or at least 2009), companies have been basing decisions on game metrics, investors have used performance metrics to base investment decisions and outside analysts have used game metrics to estimate the health of a company. Unfortunately, all of these applications of metrics are deeply flawed and often mislead the decision-makers, investors and analysts (sometimes intentionally, sometimes not).

The charts below from Appsflyer show the critical flaw in looking at a game’s metrics:

Retention performance on Android by source:

It all depends on the source

The first lesson from these charts is that performance depends largely on the source of users. Although these charts show retention metrics, I am certain monetization and virality performance shows similar behavior. Thus, your performance metrics are incredibly biased by the source of traffic and metrics for your game overall only reflect the quality of the various user sources.

As an example, assume your Bingo game has D7 (Day 7) retention of 20% and an ARPDAU (average revenue per daily active user) of $0.25. Your main competitor’s game had D7 retention of 10% and an ARPDAU of $0.15. Based on this information, you may decide to cancel other projects and focus on this game. As a corporate development expert, you may aggressively try to acquire this company. The problem, however, is that the competitive game may be three years old and the company is using a very weak user acquisition channel that does not have a high cost because they have gotten all potential users from the better channels. Conversely, you may have acquired users through a Facebook mobile ad campaign targeting high-value Bingo players. Thus, your new users are of much higher quality than those from competitive Bingo game.

Even if your game is significantly worse, its metrics would look better at this stage. If you decide to focus on this game, the new users you bring in end up performing much worse than when you made the decision. This deterioration is not due to the game getting worse; it’s just based on a different set of users. If you end up acquiring the company for $100 million, you will then find out that as you try to grow it, you have trouble getting new profitable users.

Trends can be misleading

Trends one of are the most powerful analytics tools in your arsenal, as they show how your product or game is performing over time and if it is improving or deteriorating. Looking at the Appsflyer charts, however, it’s easy to see that that trends can largely be created by changes in the user mix. As the user acquisition team changes the mix of players, the new mix could create upward trends even if the game has not improved or deteriorated. The changes in behavior will be caused by the changes in user mix.

The only metric that counts

I have written many times about customer lifetime value (LTV), and the variance in metrics by source shows the central importance of focusing on the lifetime value to CPI (cost-per-install) equation. To summarize, LTV is how much profit a new player will generate for you in total and is a function of retention, monetization and virality. As long as your LTV is higher than the cost of acquiring that customer (CPI for paid user acquisition on mobile or web), you want to continue acquiring players.

Given the variance in performance by source that the AppsFlyer charts show, the LTV by source will also have huge variance. Thus, the goal is to have an LTV higher than the cost of user for that source. The LTV on a global scale is not important, it is finding pockets where LTV is greater than CPI and then acquiring against those targets. Any target KPIs (key performance indicators) outside of LTV being greater than CPI are worthless because this last equation will determine the success of your game. Anything else can be manipulated (e.g., buying users from certain sources who generate your “goals”). As long as LTV exceeds CPI for a source, you can acquire users from that source and grow your game. Once there are no sources where the LTV for that source are higher than the CPI (even if overall LTV is higher than many sources but not higher by source), you cannot buy users and the game will stop growing and start withering.

What it means

The high variance in performance of players by source has several important implications:

You must track performance of users on a cohort/source basis. Only by comparing similar users can you understand how your game is performing.
The sophistication of your user acquisition/growth team is critical. Managing CPIs is meaningless if it is not tied to the performance of the users; you need growth experts who can get you users with the highest yield (delta between LTV and CPI). You also may otherwise miss opportunities where your metrics may not appear to support buying expensive traffic, but that traffic will perform so well that it is a good value.
Holistic game metrics (sometimes referred to as vanity metrics) are meaningless or even misleading. You need to focus on keeping LTV higher than CPI for your sources of traffic.

The critical point is not to focus on vanity metrics that can be manipulated and are not actionable. Instead, focus on the performance of your product for specific cohorts of customers.

Key takeaways

There is an extremely high variance in performance of users based on the source of the users. Thus, it is misleading to look at overall metrics as they are largely a result of your user sources.
You must track performance of users on a cohort/source basis. Only by comparing similar users can you understand how your game is performing.
It is critical to build a strong growth or user acquisition team. Managing CPIs is meaningless if it is not tied to the performance of the users, you need growth experts who can get you users with the highest yield (delta between LTV and CPI).

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