Author

Raised in the Kibbutz and reborn in the city, Yaniv is a certified entre-parent-neur. When he’s not busy doing SEO, content marketing, administration, QA, fund raising, customer support… [stop to breathe], you can find Yaniv snowboarding down the slopes of France and hiking with his kids. Yaniv holds a B.Sc. in Computer Science and Management from Tel Aviv University. He is also an avid blogger and a speaker at industry events. Before SOOMLA, Yaniv co-founded EyeView and INTENTClick.

App Monetization, Tips and Advice

How Gazeus saved 66% of their budget by measuring ads

At SOOMLA we are always advocating being more data driven when it comes to mobile app monetization. This way we are happy whenever we see a publisher stepping up their data game and starting to measure their monetization. In an earlier post we showed how Kongregate doubled their traffic by measuring ads and in this post we will see how Gazeus saved 66% of their budget.

About Gazeus

If you don’t know Gazeus I highly recommend watching the video below. The presentation is given by Paula Neves, CMO @ Gazeus.

 

 

Here are a few key points to know about Gazeus:

  • Owner of the Jogatina brand that is known from web/PC games
  • 40+ Titles
  • 9M MAU in mobile
  • 99% of mobile revenue coming from Ads
  • Strongest Geos – US, Canada

Measuring Ads – Critical and Challenging Problem

Since 99% of the revenue is coming from Ads, says Paula: “LTVs are lower and UA has to be spot on”. She then explains that they had ROI calculations only at the app level as a whole but not per campaign. On the product side, they didn’t have sufficient feedback loop for product to know if the features they are making are good. For these reasons, ad measurement is critical for Gazeus. In the video, Paula explains that her background is in the eCommerce domain where she took LTV for granted but when she came to Gazeus, she discovered that an entire infrastructure has to be created just to receive an answer for this question. This root cause of that is, of course, lack of user level data from the ad-networks.
 

CASE STUDY ON ADVERTISERS CHURN & eCPM

 

The outcome – 66% of marketing budget saved without sacrificing growth

Skipping to the bottom line quickly. Paula explained that the ability to measure ads allowed them to be much more focused in their UA efforts. In one example she gave, having the granular ad revenue per user data allowed them to chart the LTV curve for each cohort. By comparing the curves of iPad vs. iPhone users coming from different campaigns they were able to save a big portion of their ineffective marketing spending. The bottom line is that they were able to spend as little as 1/3 of what they were spending and still get the same revenue growth.

Gazeus ad measurement infrastructure and SOOMLA

In the middle part of the video, Paula explains how they built their ad measurement infrastructure. They had to collect API level data from each one of the ad-networks. For each one, different types of fields and dimensions are provided so normalizing that and the timezones is another challenge altogether. From the client side, they had to set up an event to be fired every time an ad is served. The server than allocates the average eCPM of the previous day for the relevant country and ad-format for each impression and multiplies by the number of impressions to generate user level revenue data.

Of course, a publisher doesn’t have to go through all this in order to get user level ad revenue. They can simply work with SOOMLA to get the data through API, directly into Amazon or via SOOMLA Dashboard. For Gazeus, they decided to go with their own solution since they use a few unique networks in Brazil that SOOMLA doesn’t support as Paula explains but for most publishers it’s not an issue. Here is a table to help you evaluate both options.

Build In-house Using SOOMLA
Initial Effort Up to 6 man months 1 week
Calculation Method Average eCPM Method* True eCPM Method**
Ad Network Support Tailored The 25 Most Popular Networks
Maintenance Internal resources Outsource to SOOMLA
Extra features N/A Advertiser identification, ad whale lookalikes, postbacks
Cost (for 5M MAU) Increase in hosting bill can reach $2,000 $2,500 to $3,500

*Average eCPM Method

  • In this method, the ad LTV system queries the API of each ad-network to retrieve the average eCPM of the previous day for each country and ad-format.
  • At the same time, the client side of the app reports to the ad LTV system each time an impression is shown to a user.
  • The ad LTV system calculates the revenue for the user by multiplying the number of impressions the user made in each ad-format by the average eCPM of that ad-format/country in that day and than dividing by 1,000. Than it sums the results for each ad-format for that user.
  • The process is repeated each day and data is aggregated on a user level basis and on a cohort basis.

Putting it in a formula – this would be the calculation of the revenue for user x (Imps is short for impressions here):

**True eCPM Method

  • In this method, the ad LTV system queries the API of each ad-network to retrieve the average eCPM of the previous day for each country and ad-format in addition to other dimensions that are available.
  • At the same time, the client side of the app reports to the ad LTV system multiple events for each impression: impression event, clicks, installs, ad interactions, advertiser identity, business model, bid levels.
  • The ad LTV system leverages advanced algorithms to deduct the true eCPM of each impression based on the data collected from the client side as well as the averages reported through the APIs. It then calculates the revenue for each user by summing up the contributions of each impression he viewed.
  • The process is repeated each day and data is aggregated on a user level basis and on a cohort basis.

The formula below shows the revenue calculation for user x where ‘n’ is the number of impressions he made in that day.

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Analytics, App Monetization, Tips and Advice

10 Mistakes that will keep your ad revenue low

Most of the companies I talk with are interested in increasing their ad revenues. For many, increasing ad revenue is critical as they need to be profitable on their UA activities. Despite that, I see many mistakes companies are making that prevent them from improving on this front. Here are the top 10.

No new SDK policy

Some companies seem to have decisions made from the engineering to the business and not the other way around. It’s true that there are many SDK companies knocking on the door at any given time and many of them promise more than they deliver. However, not adding any new SDKs is like saying – our strategy is to not change anything. In a dynamic space such as the mobile app market – this is a big mistake.

How to fix it:

Establish a process for vetting new vendors based on business potential, risk and costs and make sure you include alternative cost as part of that equation. This will help you re-gain the confidance of the engineering team that you are not just making random requests.

No ads for payers

In 2018 mobile app publishers will make more revenue from advertising than from IAP and publishers needs to start thinking about ads as a main source and not a secondary one. In 2016, SOOMLA revealed the existence of ad-whales. These users can contribute $30 or $50 or $100 in your app – more than some of your payers contribute.

How to fix it:

It’s time to design monetization patterns where ads and IAP complement each other. Think about a user that just purchase a bag of coins maybe he can get 25% extra coins for watching a video right after the purchase. There are many other options to experiment with just make sure you measure the impact accurately.

Not measuring your ad monetization

You can’t manage what you can’t measure” said Peter Drucker in a famous quote. In other words, the path to improvement goes through measurement and the domain of app monetization is not different. Ad revenue has been lacking proper measurement tools but the situation is quickly changing and monetization measurement is becoming a neccessity for any company who takes their ad revenue seriously.

How to fix it:

Implement a monetization measurement system that allows you to get granular data about how your users interact with ads in your app. As Jeff Gurian from Kongregate said: “Ads count so count your ads

Banning competitor ads

The debate whether or not to show competitor ads in your app has been going on for years. Some companies simply block any app that seems competitive while others enjoy the high eCPMs that competitors could be generating. A recent study by SOOMLA revealed that ads showing competitors might not be the ones that take your users away and each app needs to be evaluated on a case by case basis before deciding to blacklist.

How to fix it:

There are several SDK providers that can give you insight into who is advertising in your app. Implementing such an SDK in your app will enable a more data driven approach to the decision whether or not to advertise a specific app or block it.

One size fits all

When it comes to ads, not all the users are created equal. For example, some users may respond better to rewarded videos while others yield more revenue from banners and native ads. Serving the same ad experience to all the users is a great way to keep your revenues low.

How to fix it:

Track the yield of each user from each ad-type (for example – by using SOOMLA) and use the data to segment them into groups. You can then build more tailored ad experiences that will improve your ad arpdau.

Introducing rewarded videos late

While it’s clear that most ad formats have a negative impact on retention and payer conversion it’s also clear already that rewarded videos do not have such impact. Since 80% of your users are likely to not survive the first week, delaying ads for 7 days will surely have a negative impact on revenue.

How to fix it:

Introduce rewarded videos as early as possible and even include them in the tutorial. If you want to be a bit more cautious, you can do this only for users who are not likely to pay.

 

FREE REPORT – VIDEO ADS RETENTION IMPACT

 

Incentives that don’t add up

In many apps and more specifically in games, the users are rewarded for watching videos. The rewards can range from an extra life to coins or pretty much any upgrade that the game has to offer. Some games have invested time and effort to carefully design the reward opportunities into the game but in other cases the reward for watching videos is in-game currency in small amounts that don’t allow the player to buy anything of value. Offering incentives with little value will discourage users from watching ads.

How to fix it:

First, you should measure opt-in on a cohort basis to see if your users lose interest in the rewards over time. If you detect such an issue you can consult this post for ideas how to improve the incentives – Top 7 Incentives for Video Ads in Mobile Games

Not managing the ad networks

Ad networks are an important part of your monetization but their interests are not always aligned with yours. Typically, for each $1 you are making, the ad-networks are also making a $1. This means that there is a lot of opportunity for the publishers who can closely monitor and negotiate the prices up. Without doing this, your ad monetization not be optimal and might decline over time.

How to fix it:

First, you need a way to track ad revenue per impression sequence so you can manage the waterfall. Additionally, you may also want to get visibility into the campaigns the ad-networks are bringing you. If you don’t have those, you can still negotiate with the ad-networks but it will be harder. To successfully negotiate – remember that your leverage will  be the share in the impressions they are getting as well as their position in the waterfall. In return, you will want to get guarantees for eCPM and fill rates.

Focusing your UA only on payers

If you ask most marketing teams what users are they trying to get for the app they might answer “payers” or “high value players” but in both cases they mean payers actually. What this means is that the monetization manager is trying to monetize with ads users who were supposed to be payers. This strategy is far from ideal. If you are not giving the UA team a task to bring ad whales don’t be surprised that your users don’t do well with ads.

How to fix it:

Step 1 is to figure out who the ad whales are. Once you do that, you can start sending postbacks for ad whales so ad networks can send you more of these high value players. At the same time, you can have the marketing team profile the ad whales and learn more about them so they look for the right media to reach this audience. Finally, targeting lookalikes of the ad whales on FB ads manager has brought great results for some of our customers.

Not doing direct deals

Do you know how many ad-tech middle-mans are between you and the advertiser placing ads in your app? You don’t. It could be 1 or 2 or 5 or 10. One way to know for sure is having no middle-mans. Not doing direct deals means you are leaving money on the table but what’s more important is that you don’t even know how much revenue you are missing out on which means you have very little leverage when you negotiate with ad-networks.

How to fix it:

You should start by getting visibility into who is advertising in your app. This will give you a priority list of who you should be approaching. Getting to the right contact in these companies is not very hard but if you get stuck, shoot me an email to yaniv [at] soom [dot] la and I will try to connect you. Also knowing the eCPM you are getting from each advertiser through the ad-networks could prove useful.

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Analytics, Announcement, Industry News

New Loot Box Regulations - What It Means for Mobile Games

About 3 weeks ago on December 21st, Apple added a small term to it’s T&C for app publishers.

Apps offering “loot boxes” or other mechanisms that provide randomized virtual items for purchase must disclose the odds of receiving each type of item to customers prior to purchase.

Most of you probably missed it during the holiday season as did I but a few major publications caught the change and reported it quickly. Here is the report in PocketGamer and in The Verge. This change might be a response to an increasing interest of some of the regulators in the loot boxes concept. It started with Starwars Battlefront 2 criticism on reddit when a response by EA became the most downvoted comment on reddit ever. The “loot box” monetization strategy along side the game appeal to kids caused a few regulators to take notice. Most notabely, the State of Hawaii announced they will work on legistlation to ban loot boxes and Belgian officials said they would like loot boxes banned as it’s a form of gambling.

The top 25 grossing games were not effected

One might think that the change made by Apple will make a big impact on game publishers given how popular loot boxes are. In reality, however, none of the top 25 grossing games made any changes. The reason, is that none of them are selling loot boxes as in-app purchases. While loot boxes are popular, they are commonly sold for virtual currency which can be bought for cash. If you look at the top 25 grossing apps, the items that are listed in the app store for purchase are packs of: quartzes, diamonds, crystals, gold, coins, gems. The only game we could find that will have to make a change is Hearthstone.

What about in-game loot boxes

Apple didn’t entirely ban loot boxes that can be purchased inside the game with in-game currency. The regulators however might decide to address this type of loot box as well. There are many game elements that are randomized, therefore the question arises of where the distinction will take place. It’s one thing to ban something that is purchasable, but if any randomized game element is banned, pandora’s box will open. My guess is that regulators will focus on purchasable items and games that are made for kids.

 

CASE STUDY ON ADVERTISERS CHURN & eCPM

 

If gambling with VC is illegal than what about social casino

The comment by Belgian officials was that loot boxes are a form of gambling and therefore should be banned. What is a bit odd is that there are more obvious forms of gambling that are not banned yet – the social casino apps. Either these officials have a double standard when it comes to mobile games or they haven’t opened the top grossing charts recently.

The clear winner is rewarded video

Aside from kids and their parents who might get to keep more money in their wallets, the companies who provide monetization via ads and rewarded videos will probably benefit from these regulations if they happen. Ad based monetization models are becoming more popular in the mobile game industry and the fact that Apple is adding limitations on in-app purchases pushes more game developers in towards ads.

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Analytics, App Monetization, Game Design, Tips and Advice

4 Proven Tips for Improving Opt-In Rate - Based on Data

If you have been following the SOOMLA blog, attending mobile game conferences or keeping up with the latest mobile monetization trends in some other ways you should already know the following important fact. Improving Opt-in to rewarded videos usually results in an increase of the same proportion in your total ad revenue. This is why many companies that use rewarded videos have been focusing on the opt-in parameter and have been trying to optimize it.

While getting the basic opt-in ratio is easy, there are a few advanced methods for finding hidden opportunities around opt-in rates.

1 – Look at daily opt-in vs. monthly opt-in

Typically, app companies focus on the monthly opt-in – this is the ratio that is normally available by platforms such as Ironsource mediation and what most will allow you to analyze if you send them the impression events. The monthly opt-in, however, only tells part of the story and in many cases we have seen that the daily opt-in can be significantly lower. What that means is that there are users who opt-in to the videos some of the days while not watching videos on other days. Fixing this can usually yield 20-25% more in ad revenue and the way to do it is by taking a close look at your incentives. Will the users need the incentive on a daily basis? If not, try to figure out an incentive that the users will need more regularly.

Definitions
Monthly opt-in – the number of unique users who watched at least one video in a given month out of your total MAU.
Daily opt-in – the number of unique users who watched at least one video in a given day out of your total DAU. The daily opt-in has to be averaged across multiple days to smooth out the fluctuations.

2 – Analyze opt-in for cohorts

Cohort analysis is hardly a new trick for marketers but when it comes to monetization managers it actually is. Comparing the opt-in rate for new users vs. existing users can lead to some pretty interesting insights based on our experience. This might requires some help from your BI team (or simply using SOOMLA’s dashboard) but the hidden opportunity should justify the effort as we have seen up to 2x differences between the two segments. If opt-in is high for new users and declining for long-term users it could be a sign that your incentives are not meaningful enough for your users. In other words users are willing to watch videos but they soon realize that what they are getting in return doesn’t get them very far so they stop. In other situations, the opt-in for new users is low. This could indicate an awareness and training problem. Making your users aware of the option to watch videos early on can fix the problem.

3 – Differentiate users from different traffic sources

One of the interesting patterns we have seen is that users from different traffic sources behave differently when it comes to opt-in ratio. Users who came from paid channels and specifically from video ads often present a higher opt-in ratio compared to organic users. To improve the opt-in ratio for organic users, consider adding some more guidance to highlight the opportunity of watching videos for in-game rewards.

4 – Treat your ad whales to nice Incentives

In recent research we showed that the top 20% of the users contribute 80% of the ad revenue. These so called Ad Whales are the most important segment from an ad revenue perspective. You should focus a lot of your attention to make sure the opt-in rate for this group is as high as it can be. These users typically contribute more than $0.99 and sometimes up to $100. This means that they are as good as payers and you can offer them in-game items that are normally reserved for an actual purchase. However, since you want users of this group to watch a video daily it’s better not to offer them a perpetual item. Some examples of incentives you can give for ad whales:

  • A tank that is normally worth $100 – watch a video to use for a single day
  • Shortening a waiting time that normally costs up to $1
  • 10x coin boost for a short period instead of 2x

Identifying the ad whales is possible by attributing the ad revenue accurately to the user level. The only way to do this accurately today is with SOOMLA Traceback.

We’ve put out a series of posts on the wide topic of Opt-In rates and the importance of them. Feel free to check them out:

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Game Design, Tips and Advice

Is it time to end Match 3 Game tutorials?

If you downloaded a match 3 game recently you might have noticed that the first few levels are guiding you how to play the game. I would make a guess that if you are reading this blog you have already played several match 3 games already and the tutorial is not really relevant for you. The question is how frequent is this situation and if there is a better why.

Match 3 – a popular genre

Match 3 games are a popular genre on mobile – no doubt about that. A Google site search on the play store returns over 1M results for the search “Site:play.google.com “match-3”.

image-5

It’s probably the genre with the most number of apps out of the narrow genres (as opposed to a wide genre such as “Strategy”).

If we look at the number of players: Candy crush alone has over 2.7 billion downloads – this is close to the number of app capable devices out there and there are many more apps who are not that far behind.

It’s not a new genre either. Match 3 games has been around for at least 15 years. They have been with us through web games, Facebook games and mobile games.

image-6

A new user in a match 3 games is not new to the genre

What all these stats mean is that if your company publishes a match 3 game it’s likely that the majority of the new users you are getting is already familiar with the genre. Your UA teams are targeting users who liked other match 3 games on Facebook, Google is targeting your ads to users who searched match 3 in the past and other networks are trying to achieve the same result to send you relevant users. Users who know how to play match 3.

The tutorial is redundant for experienced users

image-4

Showing a tutorial to a user who never played match 3 could be the difference between him staying or leaving. However, the same tutorial for an experienced user is not effective. In fact, it might have the opposite effect – causing the user to leave as he is not challenged enough. Consider the tutorial in the image shown on the right side – it basically says “match 3 items” and might evoke the reaction “Well Duh!! It’s a match 3 game”.

Detecting experienced users automatically

Game publishers who want to offer an adaptive tutorial experience face a new challenge – how to detect which users are experienced match 3 players vs. not. Here are a few ideas how to detect this:

  • Acquisition channel – normally your UA efforts will be targeted at match 3 fans so you can just treat all paid traffic as experienced players. Alternatively, separate campaigns that are directly targeted to match 3 fans vs. broader campaigns. Using deeplinking you can invoke different flows inside the app. 
  • For the android version of your app, you can potentially check what other apps are installed on the device to determine if the user is already familiar with the genre. While Google will not allow you to send the app list to your server, checking locally and adapting the game experience is in the benefit of the app publisher as well as the user.
  • Prompting the user and asking him if he knows the genre is another way to go. If you think asking the user questions is annoying you should think again. Going through 7 levels of learning the game is far more annoying.
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Analytics, App Monetization, Industry Forecasts, Industry News

7 App Monetization Predictions for 2018

As SOOMLA is the 1st company to focus on monetization measurement for mobile apps it only make sense that we will take the lead on predicting some of the trends that will control app monetization in 2018. These predictions are based on our data as well as on observing the market trends in 2017. However, predicting the future is a tricky business so take these with a grain of salt. Here we go – counting 7.

1 – Let the ad whale hunting begin

In 2017 SOOMLA exposed the existence of ad whales – a group of users who contribute over 80% of the app ad revenue and can sometimes make $100 for the app publisher by watching and interacting with ads. In 2018 more and more app companies will invest resources into understanding who the ad whales are, how they behave, what are the best channels to bring more of them and how to adapt the app for this segment. Basically, the same practices app companies applied for the top spenders will be used for the users who generate the big advertising dollars.

2 – Publishers will seek tighter control on ‘rich’ interstitial ad content

2017 introduced a lot of innovation around ad-formats that can be delivered through interstitial containers: Playable ads, interactive videos, dynamic end cards and what not. Publishers who integrated interstitial ads expecting a short ad break in the app flow ended up with an experience they didn’t sign up for. The fact that a longer ad experience with an invisible ‘x’ button has a toll on retention intuitive but SOOMLA also validated that with data and will publish a report about it in Q1/18. In 2017 some publishers started pushing back on these formats and we expect more publishers will want to control these ad experiences in 2018.

3 – More publishers that are also advertisers

In 2016 there were very few ad driven app companies that could afford paid UA campaigns. In 2017 this number grew and in 2018 it will grow even more. Following the footsteps of SOOMLA, more providers are offering tools that give visibility into Ad LTV. In turn, more publishers are aware of where they stand and what CPI levels they can bid. See the post about the steady increase of CPIs and how they are here to stay.

4 – Header bidding will start but adoption will be slower than expected

Header bidding was discussed in many conferences in 2017. The idea is simple and highly beneficial to publishers and some ad providers have launched earlier versions of this model. In 2018, some publishers will test out this model but it will not go into mass adoption just yet. There are too many loose ends at the moment and no sufficient coverage from ad providers. Furthermore, it appears that the some of the leading players are happy to receive bids from others but no so happy to provide the bid out. FB, Google, Mopub, Appodeal and Ironsource are each trying to become the company who will run the auction so they refuse to give a bid out. This means each that each one of them insists on exclusivity which will be a big turnoff for publishers.

5 – Better control over ad experience and creative

Publishers needs ways to control the ad experience as part of the overall app experience. In 2017, SOOMLA and SafeDK started providing solutions in this area. We expect more solutions will become available, more publishers will start using these and ad providers will also start adding more functionality to control ad experience.

6 – More apps will advertise competitors in 2018

Advertising competitors was a big no-no for many app publishers who were concerned their users will churn away and move to the competitor app. In 2018 there are already tools that allows monitoring the eCPM and churn caused by specific advertiser. This means app publishers will be able to apply a data driven approach to this question that was decided with gut instincts until recently. Based on the data we have seen – more publishers will feel comfortable with advertising competitors as a result.

7 – Ads will surpass IAP for mobile game monetization

2017 ended up with a tie between the different monetization models for games. Some studies claimed IAP revenue was still bigger while others showed ad revenue as the winning monetization model. In 2018, there will be no question any more and the clear monetization winner will be ad revenue. Part of the reason for that is the emergence of data tools to measure ad monetization. This makes more publishers feel comfortable with building games that relay heavily on ad revenue.

That’s it – 7 predictions for the new year. Write them down and check if we were right in 12 months.

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App Monetization, Tips and Advice, Video

Top 7 incentives using video ads in your app!

Rewarded videos have been proving to be a highly effective format that balances retention with monetization and typically turn eCPMs of over $20 in the US. However, unlike other ad formats, they require the game designer to build incentives that can be handed to the users when he watches videos. Check out our previous post that talks about mastering the Opt-In ratio to boost rewarded video ad revenue. The general rules of thumb on where to implement rewarded videos are:

  • Designing the incentives from the beginning is easier than adding them after
  • The more evolved the meta game is, the more opportunities for videos there are

Here you can find the most popular incentives to entice users to watch videos:

1. Lives or “save me” option

This is a familiar incentive that allows the player to cheat death. It it widely used in Match-3 games where the meta game typically dictates that a player may only fail 5 times before he runs out of lives at which point he typically has to wait for his lives to replenish. Another version of this incentives appears in action/arcade games where a violent death of the character typically ends the player’s session and an option to keep the session going makes a strong incentive for the user to watch videos.

2. Time related incentives

Warping the game time can be a compelling incentive for the player. In some games, the player is only given a limited time to complete a mission or a screen and is offered to watch a video to gain more time. In other situations, the player wishes to avoid a long wait and is willing to trade that wait for watching a video. A perfect example is upgrading a piece of equipment which takes 2 hours, but if you watch a video ad, it upgrades immediately.

3. In game currency

This one is simple and quite obvious. A bag of gold in exchange for watching a video is one of the oldest offers out there. It’s not the most effective incentive but it’s widely applicable and typically doesn’t require any special hooks to be put in the game for it.

 

FREE REPORT – VIDEO ADS RETENTION IMPACT

 

4. Earnings doubler

The coin doubler is known as a paid item that players can buy. However, a limited time doubler may be offered as an incentive to players who are willing to spend 30 seconds watching a video ad. This type of incentive is popular in idle clicker games and runner games among other genres. There are 2 variations of this incentive:

  • Pre-session – allowing the user to start a session knowing his earnings will be doubled
  • Post-session – popping the question to the user in the session summary screen

5. Re-dealing of a randomly assigned element

In many cases a player get dealt a hand of cards, in other games he opens a pack of collectables and sometimes it’s quests, missions or even songs that the game randomly selects for the player. If a player doesn’t like his options, he can change them in exchange for watching a video.

6. Renting items

Some items in the game can be priced very high and not many users can afford them. Giving them away for a video watch can reduced the perceived value of such items. The compromise is to rent such items for a limited period of time. If an item costs $50 and you expect the users to use it for 30 days renting it for 15 minutes for a video view is maintaining the balance and unlikely to hurt your conversion to payers.

7. The daily spin

Many games offer a daily spin or surprise box as part of their meta game. It’s a great way to make players feel welcomed and keep them in the game. This daily spin often ends with a near miss experience and users are likely to watch a video ad if one is offered in return for an extra spin.

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Analytics, Announcement, Industry News, Tips and Advice

GDPR 101 - How to avoid the €20M fine for your mobile app

Some of our customers started asking us about GDPR. To those of you who haven’t heard about it, GDPR is the new European privacy regulation that will take affect on 25th of May 2018. The new set of rules is causing many companies to lose sleep also due to the recent Disney lawsuit and the lawsuit against Kiloo, maker of Subway Surfer. The first suit includes not just the company itself but also tech providers such as Kochava, Upsight and Unity.

This means that while the app companies are on the front, the technology companies behind them should also learn GDPR carefully. In the rest of the post, I’ll try to describe some of the key differences and explain what actions companies should consider. So lets jump into what’s new with the GDRP:

The price tag difference

One of the new aspects of GDPR is that it names a price for non-compliance – fines can reach up to €20M Or 4% of annual gross revenues – the greatest of the two. What this means for app companies is that they have a strong business case to invest money and effort in complying. For tech companies, it means that the level of liability will be pushed up. If tech companies were able to get a way with capping their liability at a $0.5M or $1M dollar, that will no longer be acceptable by the app companies.

US companies also on the hook

Another key difference is that GDPR makes it clear that as long as companies have users in EU, the rules apply to them regardless of their location. For US companies, this is a major difference as privacy rules in the US are less restrictive.

Everything is personal

One thing that the GDPR makes very clear is that all device identifiers including IDFA (Apple devices’ ID for advertising), GAID (Google’s advertising ID) and IP address are now considered personal data and any data stored with it in the same record should also be considered personal. This have been a gray area a few years ago but was getting less and less gray in recent years. With GDPR there is zero doubt about this. For app companies and, advertising companies and analytics companies this means that all data becomes personal and should be treated as such.

Encrypting and protecting and documenting data transactions

Another requirement that GDPR makes more clear is the need to encrypt and protect personal data as well as document any transaction in which encryption was not possible. This is not a new requirement but since all data is considered personal now it becomes a requirement for each company and each piece of data. Here is an example of one process that is likely to change for App companies and has already affected some of the tech providers. In the past, companies used Facebook’s highly effective lookalike modeling service by creating custom audiences based on divide identifiers. The practice of exporting a CSV file from you analytics or attribution platform, storing it in your personal computer and uploading it to Facebook is now considered a non-encrypted transaction that has to be documented. Not many app companies will want to cumbersome their process with the documentation requirement and so some of the attribution companies have responded with audience builder tools that make this transaction encrypted.

 

REPORT – ADVERTISERS EFFECT ON CHURN & eCPM

 

Is your data coming to US for business or pleasure

Another area that app companies and tech companies serving them should be aware of is the transfer of information outside the EU and specifically to US. This has been a key topic for previous legislation but the requirements became stricter with GDPR. This topic is known as cross border transfer. In a nut shell, EU knows that US is more liberal when it comes to privacy and specifically in the Federal’s government ability to force companies hand in providing private data. One example of the FBI power over companies was last year when Apple confronted the FBI and refused to help them crack an iPhone. While Apple stood up to the FBI, very few companies will risk disobeying a court order.

To adapt to the new regulations, companies can no longer rely on gaining the user consent for transferring their data. This practice is required but not sufficient anymore. Instead companies should do one of the following:

  • Keep data about EU users in Europe and comply all tech providers to do so
  • Make sure all providers are part of the Privacy Shield initiative
  • Execute model clauses to document each data export from EU to US

Keeping data in EU

This may sound easier than it is. If you are an app company, you are probably using at least a dozen services to help you monetize users, analyze them and improve your app. Most likely, you also have homegrown analytics tech that reads and writes data to a database stored by a cloud provider. Keeping the data in EU means you need to go to your cloud provider and each one of the other tech provider and make sure they also keep the data in EU. In turn, the tech providers will have to go to their tech providers and cloud providers and do the same. While the major cloud providers: AWS, Google and Azure have data centers in Europe it’s unlikely to ensure 100% of the data staying in EU given the number of providers involved especially when the app is serving ads.

Privacy Shield

This is essentially a certification that companies can get if they do store their data in the US. Being listed in the Privacy Shield list of certified companies is an alternative requirement to keeping data in EU. It means that tech providers who don’t keep EU user data in EU can get a Privacy Shield certification and help the app companies comply with GDPR. In the list below, you can find popular SDK providers that already obtained Privacy Shield certifications and the ones who didn’t. The extensive list can be found here – https://www.privacyshield.gov/list . Note that:

  • Providers that store data in EU don’t need the Privacy Shield (e.g. Adjust)
  • Providers can give an EU model clause document to app companies as an alternative to Privacy Shield and still comply with GDPR.

SOOMLA is already in compliance with the regulations and has started a process to obtain a Privacy Shield certification. Ask us about the current status by emailing – privacy@soom.la.

EU Model Clause

As mentioned before, providers who don’t keep their data in EU and don’t have a privacy shield certification can still help app companies comply with GDPR by providing an EU model clause document explaining exactly how and what personal data flows from EU to US.

The right to be forgotten

Another key requirement by GDPR is that every user has the right to be forgotten. This means that a user can request an app publisher to delete all his data including data about him that is stored by 3rd party providers.

What you should ask from your providers

While there are a few changes app developers might have to implement in how they handle their users’ data most of the work will probably be with ensuring their providers’ compliance and more specifically their advertising related ones. The decision to treat IDFA, GAID and IP addresses as personal data puts all the advertising industry in the spotlight as most of it was operating under the assumption that IDFA will not be considered personal data.

Here is quick compliance checklist for your providers.

  • Do you protect and  encrypt any record that contains IDFA or IP address?
  • Can lists of IDFAs or IP addresses be exported? Do you send such lists over email?
  • Do you keep the data in EU or US? If in US – are certified under privacy shield? Can you provide model clause explaining all data transactions?
  • Forgetting users – Make sure you know all instances of the user record (log, backup, main DB, …) and what’s the mechanism to delete.

Providers Not Certified with Privacy Shield [updated Nov-2017]

  • Appodeal
  • Chartboost
  • Ironsource
  • Fyber
  • Adjust (But already has a stricter certification)
  • Heyzap
  • Lifestreet
  • Media Brix
  • AOL / Millenial
  • Tapjoy
  • Vungle
  • Upsight/Fuse
  • Unity / Unity Analytics / Unity ads

Providers Certified with Privacy Shield

  • Google – including Cloud, Admob, Analytics and Firebase services
  • Amazon – including AWS and Amazon Ads
  • Microsoft – including Azure
  • Applovin
  • Adcolony
  • Appsflyer
  • AppAnnie
  • Mixpanel
  • Facebook
  • Kochava
  • Amplitude
  • TUNE
  • Mopub

 

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Analytics, App Monetization, Tips and Advice

3 reasons to track 1st Impression eCPM and not average eCPM

App Publishers who monetize with ads often face the need to compare between ad-networks. Which one offers stronger monetization? Is the network declining in strength? Who should i put first in the waterfall? The common practice today is to look at the average eCPM but actually looking at the 1st impression eCPM is a much better approach. Here are 3 reasons for that.

Networks put their best campaign first

Each ad network has internal optimizations mechanisms in place. Some have algorithmic approach that try to predict the eCPM of each potential ad given who is the user and all the data they have about him. Others have more simplistic priority lists. Either way, when the network sees the user for the 1st time in a given day, it will try to put the best ad for that user. In later impressions, they have to circulate in other ads, their 2nd best, 3rd best and so on.

Average eCPM is a self fullfilling prophesy

Average eCPM on the other hand is influenced by many parameters other then the network’s stregth. In situations where the average eCPM is used to determine the priority between the networks it acts as a self fullfilling prophesy. To understand this, let’s look at the two ends of the priority list:
The Network with First Priority – This network gets more 1st impressions than any other network as long as it has fill for them. This drives the average up. At the same time, the network also wants to stay at the top and knowing that the publisher is looking at the average eCPM it is likely to set a price floor that will eliminate the low eCPM campaigns. This will also drive the average eCPM up.
The Network with the Low Priority – This network is getting less 1st impressions so their average will be lower. Even if the network landed a major campaign it will not get a lot of exposure and will not be able to drive the eCPM up. At the same time, the low priority network can’t shut down the low eCPM campaigns as that will completely choke the delivery for their advertisers and will cause a new bag of issues for the network.

 

FREE REPORT – VIDEO ADS RETENTION IMPACT

 

Changes in 1st impression eCPMs are clear triggers for action

Tracking different parameters is a good practice but tracking becomes much more powerful when it’s connected to actions. When you track the average eCPM and you see a drop in that paremeter for one of the ad-networks there could be a few potential explanations. For example, if that network is getting a high percentage of later impressions it would bring down the average. The 1st impression eCPM is less influenced by how you are using the demand source and is a better indicator of the quality of the demand. A drop in the 1st impression eCPM can be caused by the ad-network losing an important advertiser or by them changing the rev-share on their end. Either way, it’s a good reason to look for new partners to take the lead.

Tracking 1st impression eCPM – Easier than ever

The reason why more company focus on average eCPM rather than 1st impression eCPM is that this is the information the ad-networks are making available on their dashboards. Publishers that use SOOMLA, however, have easy access to reports about the 1st impression eCPM over time and the 1st impression eCPM of every single campaign by each ad-network in addition to the average eCPM.

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App Monetization, Tips and Advice

Hiring a ROI Monetization Manage, a full ROI formula and explanation

Many companies ask themselves these days if they should be hiring a Monetization Manager now or wait until it’s volume is larger. In this post we will try to provide a simple framework for thinking about this question.

Ads first games vs. IAP first games

There are two types of companies to consider for this question. Before you continue, you should ask yourself which type of company are you. The framework for evaluating the merits of hiring a monetization manager differs a bit between the two types of companies. Here is the profile for each one:

Ad first games – These are typically smaller companies. If you are an ad supported company and still debating the monetization manager question it’s unlikely that you have more than 15 employees. These companies tend to have a mix of at least 3 ad formats from this list: banners, native, interstitials, video and rewarded video.

IAP first games – These are typically more established companies who already do well with IAP and treat ads as a secondary channel. The ad formats in use here are mostly rewarded videos and sometimes offer walls.

The basic formula

There are 2 conditions to be met before you hire a monetization manager:

  • The ROI condition
  • The focus condition

The ROI condition

[monthly ad revenue] x [improvement opportunity ratio] x [risk factor] > [monetization manager full cost]

Where:

  • Monthly ad revenue – how much your app is making every month from advertising
  • Improvement opportunity ratio – Estimation of how much you can improve
  • Risk factor – the chance of that improvement actually happening
  • Monetization manager full cost – Salary + social benefits + taxes + direct overhead increase + cost of tech tools + cost of projects he will drive

The focus condition

The focus condition is looking at the same formula but instead of justifying the direct cost, you are estimating the opporunity cost. The focus condition is more relevant if you are projecting that the monetization manager will be driving many requirements to R&D and BI departments. We will see how to evaluate how much effort the monetization manager will require in the paragraphs below.
The way to think of opportunity cost is usually top down. Let’s say that the goal of the company is to double in revenue within 12 months. This means that each quarter you are looking to get 20% growth. Most companies can’t contain more than 2 focuses each quarter and some say 1 is enough. This means that if the monetization manager and all the tasks associated with him will not generate 10% increase it’s not meeting the focus condition. The formula will look as follows:

[improvement opportunity ratio] x [risk factor] > [Required quarterly improvement] / [Quarterly initiatives count allowed]

Estimating the improvement ratio

For IAP first games

  • Improving opt-in ratio for rewarded videos – high product and R&D effort – can double or triple ad revenue when combined with A/B testing.
  • Adding more demand partners – medium product and R&D effort – the improvement in ad revenue can be up to 50% depending on current status (see full explanation below)
  • Applying CPM price floors and cutting fixed CPM deals – no R&D effort – up to 15% improvement
  • Blocking low eCPM advertisers and optimizing volume for high eCPM ones – no R&D effort – up to 15% improvement
  • Setting different ad strategies for different segments – low R&D effort – up to 30% improvement
  • Acquiring users who respond better to ads – no R&D effort – up to 50% improvement

For Ads first games

  • Optimizing the frequency and mix of ad-formats – medium R&D effort – can improve ad revenue up to 50%
  • Adding more demand partners – medium R&D effort unless done as S2S – the improvement in ad revenue can be up to 50% depending on current status (see full explanation below)
  • Applying CPM price floors and cutting fixed CPM deals – no R&D effort – up to 25% improvement
  • Blocking low eCPM advertisers and optimizing volume for high eCPM ones – no R&D effort – up to 15% improvement
  • Setting different ad strategies for different segments – mid R&D effort – up to 30% improvement
  • Acquiring users who respond better to ads – no R&D effort – up to 50% improvement

 

FREE REPORT – VIDEO ADS RETENTION IMPACT

 

How much your ad revenue can improve by adding demand partners

The improvement ratio per ad-format is driven by how strong your demand and fill rates are currently. We included a basic formula that we found helpful but you should do a better job assessing this by looking at specific countries and diversified demand. We also recommend Jonathan Raveh’s post on this subject. Here is a simple formula to start with:

(2x[number of ad-networks serving banners]+1)x[banners revenue ratio from total]/2x[number of ad-networks serving banners]-1

Estimating the cost of the monetization manager

$8K/month or $96K per year is a nice salary for a monetization manager in US. The taxes and benefits in US can come to 25% to 40% on top of the salary. Office space and immediate overhead per employee can be around $500 based on WeWork rates. In addition, we should add the average license cost of SOOMLA ($3,000) since having a monetization manager and not giving him the right tools to optimize would be moot. The total comes to $13,500 – $15,000.

Estimating the risk

The risk ratio is slightly harder to estimate. You should think of all the things that can go wrong and try to assign probabilities. Here are some items to consider:

  • Bad hiring can set you back
  • If you can’t afford a SOOMLA license your risk will be higher
    • The monetization manager will not be able to a/b test the ad revenue so optimizations might have a negative impact
    • His ability to set the right price floors will be limited
    • He will not be able to analyze and optimize on a campaign level
    • Segmentation will not be possible for him
    • The users that are being acquired by the UA team will not be a good fit for ads
  • IAP first apps monetize mostly with rewarded video where negotiating eCPM price floors with ad-networks is only possible for high volume apps.

Example – finding the ad revenue threshold for hiring

Let’s look at one example of using the formula. We can estimate that the total opportunity to improve is 60%, the risk factor is 50% and the total cost of the monetization manager will be $15,000.

[monthly ad revenue] x 60% x 50% > $15,000

To satisfy this condition we need an ad revenue of at least $50K / month or $600K annually. The numbers we choose are reasonable so if you have this level of ad revenue and you are not hiring a monetization manager you are probably leaving money on the table. Of course, if you have $1M/month from IAP and only $50K in ad revenue, you might have bigger fish to fry first. This is where the focus condition comes in to play. Make sure you evaluate both before you make the decision.

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