App Monetization

Analytics, Announcement, App Monetization, Resource, Tech Resources

Header image - the SOOMLA ads and churn case study is out for Q4 2017, full of insights

We are excited to announce our industry first “Q1 2018: Monetization Benchmarks” report today. This is one of the many industry data reports that we will continue to publish providing important insights related to monetization through ad revenue. This report gives an in-depth comparison of eCPMs for 1st impressions and overall and providing a ranking of monetization providers in the mobile industry.

You are welcome to download the report through this link.

Here are the quick take-aways from the report:

  • Advertisers and monetization providers are clearly paying a premium for first impressions. The premium can be as high as 100% of the average eCPM, sometimes higher
  • Monetization providers and advertisers have different bidding strategies when it comes to first impressions. Some are more aggressive while others seem indifferent to the impression sequence
  • Games tend to have a bigger focus on getting the 1st impression in comparison to non-gaming advertisers who appear to be indifferent to whether or not they are shown 1st.
  • There are a few advertisers who repeatedly show up in the top 10 across different ad formats and platforms. They are able to do that by having a clear data advantage. When negotiating prices for 1st impression – make sure you have enough data.


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Analytics, App Monetization, Game Design

Playable Ads 101 - Best Practices and Top Providers

One of the hot trends in the last 6 months in mobile game marketing has been playable ads. MZ, also known as Machine Zone, was an early adopter with Game of War and Mobile Strike but many ad-networks are offering them now, more advertisers have discovered their effectiveness and players are getting used to them.

Playables of different kinds

The first playable ads started as HTML5 ads served through MRAID protocol. However, following their success, more formats have evolved. The video ad networks started moving in and have evolved two formats.

  • Interactive video end cards – This format starts as a regular video that plays for 15 or 30 seconds and once the video is over it is replaced with an HTML5 playable experience.
  • Interactive videos – These videos are broken down into 3 or 4 parts and the user has to take a simple action like clicking a button in order to continue.

Serving playables in the publisher game

While the experience from the advertiser is quite similar, on the publisher side there are two main ways to get playables in the app. There are playable ads that get served through standard containers such as interstitial. Today, if the publisher implements Admob or Mopub SDK he is likely to get some playable ads unless he blocks them. With some providers and specifically with Admob, there is no way to block them. The same thing goes for the rewarded video container – most of the video ad networks are now serving the playable ads described in the previous section when the publisher calls a rewarded video ad. On top of these there are also companies who serve playable experiences through a dedicated SDK.

The dedicated SDK approach has some pros and cons. On one side it leads to an improved ad experience for the advertiser. From the publisher’s perspective it means better control and can lead to a more expectable user experience. However, it does requires the publisher to integrate another SDK which is always fun :).

Designing playable experiences inside the game

In terms of game design, publishers have 2 main choices. The first one is to integrate playable ads in standard containers such as interstitials and rewarded videos. This is the default option and unless blocked by the publisher most ad networks will hijack standard containers and serve playables in them.

The main problem with this experience is that it’s not expected by the user. A user might sign up for watching a rewarded video in return for some in-game incentive but than get a playable ad instead. Even worse, an interstitial container might contain a playable ad at the end of a regular play session where user expects a much shorter interruption if any. Based on the data SOOMLA collects, this hijacking has a high toll on user churn. Finally, the practice of injecting a playable ad experience into a regular container creates an unfair competition in your waterfall.

As explained by this analysis made by Kongregate the playable ads generate higher eCPM for the publisher so networks that serves high amount of playable ads are more likely to produce higher eCPM rates and win the first impression. The alternative is to introduce a specific inventory for playable. A publisher can design a special button with a game controller icon and offer increased rewards for users who are willing to try a new game. This creates an opt-in experience for the playable ad rather than an hijacked one.




Who makes the playable ads

Ads are traditionally made on the advertiser side of things but with playable ads the advertising company take a very active role. This is a typical step in the evolution of an ad-formats where newer formats are produced by the ad-network or ad agency and as the market get used to the format the advertising companies take on the production task. Today most of the playable ads are produced by the provider rather than by the advertiser with only a handful of advertisers producing their own playables.

How playable ads might evolve in the future

Today, there are 2 main challenges with playable ads. One is that they don’t accurately reflect the game play of the advertised app – this can lead to lower conversion rates. On the publisher side – users find them to be repetitive – one might have to play the same 2 moves over and over again every time the ad pops up. This might be some of the reason why playable ads tend to churn more users. One evolution that we might see in the market are ads that remember the state of the user and offer progression from one ad view to another. This can be a much better user experience on the publisher side and potentially more qualified installs for the advertiser.

Winning Playable Ad Experiences

  • Applovin – Word Cookies
  • Chartboost – Bubble Island
  • Ironsource – Lords Mobile
  • CrossInstall – Solitaire

Top providers offering Playable Ads

Today most of the top rewarded video providers are offering playables:

  • Ironsource 
  • Applovin
  • Chartboost 
  • Vungle  
  • Inmobi / Aerserv
  • Adcolony
  • Apponboard
  • Cossinstall
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Analytics, App Monetization, Tips and Advice

Finally a Data Based Formula for deciding which advertisers to block

One of the oldest debates in the short history of in-app ads have been what advertisers should be blacklisted by publishers. Many companies have already started using SOOMLA to gain valuable data in support of such decisions as shown in this case study. However, we’ve noticed recently that many publishers face a problem, even when they have the data.

The problem – how do you weigh ad revenue vs. churn from ads

Even when companies have the full data of the eCPM rates paid by each advertiser along side the churn rates, it’s not always enough to reach a complete decision. What’s needed is a formula to weight the pros and cons. In other words, companies want to know what eCPM lift justifies a 1% lift in churn.
For example, let’s consider two advertisers:

  • Billionare Casino with eCPM of $17.54 and ad resulted churn 5.2% (from users who clicked the ad, how many haven’t returned)
  • WGT Golf with eCPM of $27.27 and ad resulted churn of 18.5%

Who do you think is better? Does the eCPM increase justify the additional churn?

The analysis – revenue lost vs. revenue made

To answer the question, it’s not enough to look at the basic parameters. The basic analysis that needs to be made is how much revenue was lost vs. how much revenue was made. To determine this, we have to first put a value on a lost user. A good place to start is the overall LTV of a user. If the ad is presented to the user in the first days of activity than the overall LTV of the user is pretty close to the value. For users who have been in the game for some time, the value of a lost user would be the future LTV from that point on. It’s important to note that the number could be higher due to users already having an emotional investment in the game but it can also be lower if the game doesn’t have a lot of depth. Right now, we will assume the value for all lost users is the overall LTV. Now that we figured out how much a user is worth we can multiply it by the number of users lost to determine the amount of potential revenue lost. This factors in the churn ratio but also the CTR as the churn ratio is calculated from the clicks. The revenue that was made is given directly by SOOMLA in the advertiser analysis screen.
Going back to our example – the value of a lot user was determined at $1.28:

  • Billionare Casino – generated a total of $623 and while their churn was only 5.2%, the number of users churned was 1,509 so potential revenue loss was $1,931 and the net revenue was a loss of $1,308
  • WGT Golf – generated a total of $1,573 and only churned 188 users which are worth $240. Net revenue made was $1,333

As you can see, comparison becomes much easier this way. One has a negative impact and the other has a positive one.




Comparing 2 advertisers with positive net revenue by using nCPM

The analysis above does help weed out advertisers with negative contribution, however publishers also wants to be able to compare between advertisers and give more priority to the ones with higher eCPM and low churn. In many cases, there is a need to compare the net revenue of each advertiser on a quantity of 1,000 impressions to determine who the impressions should be given to. This ratio can be called the nCPM / nRPM (net revenue per mile) as opposed to eCPM / eRPM (revenue per mile).
So back to our example:

  • WGT Golf – generated a net revenue of $1,333 on 57.7K impressions which makes his nCPM $23.1

Improving the formula

One way to improve this analysis is to have a better understanding of the lost revenue. Some games don’t have the depth to keep users retained for a long time so the loss might be lower while for other games. Also, some of the games only expose users to ads once they predict the potential for IAP revenue is very low. If they are successful in such prediction, the revenue loss from churning such user would be much lower.

Better way to prioritize advertisers

nCPM is a better way to prioritize advertisers than eCPM. However, the tools available to publishers for optimizing are limited to blacklisting. In reality, the task of prioritizing advertisers for the publisher mostly falls on the shoulders of the ad-networks. The ad providers have an algorithm that tries to predicts the eCPM of each ad. In an ideal world, there will be a way for a publisher to add a “toll rate” for each advertiser rather than just blacklisting them. This will allow the ad-networks to prioritize based on nCPM instead of eCPM.

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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.



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.




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, App Monetization, Tech Resources, Tips and Advice

A Look Into Social Point's F2P Rewarded Video Ads Strategy With Sharon Biggar

CLARIFICATION: Social Point are not a customer of SOOMLA at the moment

Video ads have been taking the mobile industry by storm as the new business model and with that, comes an abundance of questions as to how to optimize and what are their effects on users. Depending if you are a monetization manager or a product manager, your KPIs may vary, however the ultimate goal is the same: A successful app that maximizes it’s potential.

In a recent panel at GIAF (Games Industry Analytics Forum), Sharon Biggar, Chief Analytics Officer at Social Point led a captivating talk on their personal journey through a series of tests with their users on the effects of video ads and their various formats. The official title was “Video Advertising Strategy in F2P Mobile Gaming”. The video runs for about 25 mins, so if you have the time, give it a watch. Here are the topics covered:

Social Point sought to answer 3 main questions internally before coming to any conclusions regarding their F2P video advertising strategy and I’ll give a break down for each one.

What design options exist for video ads in F2P games?

Generally speaking, there are 4 main ways to integrate video ads into F2P games. Each one has it’s pluses and minuses and are used in different ways. Sharon broke them down into two main categories:

  • Pull Advertising – Pull referring to giving the user the choice to “pull” the video towards them, thus initiating the video ad.
  • Push Advertising – Push referring to forcing the user to watch the entirety of the video in order to continue.

Method 1 – Pull – Gain Currency

Rewarded Video Ads Pull 1 - Gain Currency

I’m sure we are all familiar with this method as its possibly the most prevalent in mobile games. While there are usually daily limits to prevent abuse, the general idea is a user can request to watch a video in return for a reward in forms of gold coins, gems or some other form of in game currency.

Method 2 – Pull – Double Rewards

Rewarded Video Ads Pull 2 - Double Rewards

These rewarded videos tend to appear in two forms as well. One being before initiating a level, the player can watch a video to double the effect bonuses received (gold, gems, experience) upon completing a level. Alternatively, the player is given the option once they’ve completed the level to double their rewards. Generally speaking there are no daily limits on these as they are based upon a user’s direct engagement with the app. Why limit your user’s engagement right?

Method 3 – Pull – Speed Up

Rewarded Video Ads Pull 3 - Speed Up

I’ve encountered (and used) these countless times. Sometimes they come in forms of using in game currency, but specifically here we are talking about watching a video ad in order to speed up an upgrade or improvement. Why wait 5 hours for an upgrade when you can watch a 30 second video to complete the upgrade immediately. Overall it’s a win – win and keeps user’s active.

Method 4 – Push – Forced Video

Rewarded Video Ads Push 4 - Forced Video

An intrusive and often causes some heat from users, due to it’s method, these video interstitials take over the full screen, and force the user to watch / interact with the ad. Some show a countdown before the X appears, others will appear after a few seconds. No reward / incentive is given to the user aside from waiting it out to allow them to continue to play.

Most Requested Video Ad Type

Looking specifically at their game “Dragon City”, in October, they took note of “pull” types of video ads and found some interesting things. *Note: “Dragon Cinema” refers to the gain currency type of rewarded video.

Video Ad Types and Engagement

  • Double Rewards was the most requested type of video ad
  • Interestingly enough that the “Speed Up” type of video ad was less used considering the time spent waiting vs. time spent watching the ad

Do Video Ads Increase Churn?

I think this is one of the most discussed topics right now in the industry. Before I dive into Social Point’s specific study, make sure you check out SOOMLA’s recent report on Lotum and their study on the effect on advertising direct competitors as well. It goes a bit more in depth into the effects on eCPM, churn and has surprising results. We’ve also published a series of blog posts on rewarded video ads which you can find here.

Touching upon Social Point’s study, they found that pulled video ads on similar cohorts (users that played 7 days and that had 14 sessions) had some interesting results. The users that did in fact engage with video ads within the first 7 days, churned significantly less than those who did not watch any video ads. Clearly indicating that for Social Point, video ads were NOT causing an increase in user churn.

Social Point's Results on Do Video Ads Increase Churn




What About Push Video Ads?

Social Point ran an A/B test where they allowed a control group to see 0 video ads and the second group that saw skippable video ads. There was a clear decrease in retention once forced (push) video ads were displayed. More interestingly, as pointed out by Sharon, is the minor difference between 1 and 3 skippable video ads displayed effect on retention.

Do Push Video Ads Increase Churn?

Do Video Ads Cannibalise IAP Revenue?

Social Point ran an A/B test intending to test the theory that video ads cannibalize the in-app purchase revenue. The results were rather surprising as they did in fact find that the video ads resulted in an 8% decrease in IAP revenue in the control group, however when looking at the overall revenue, the ad revenue resulted in an overall 5% increase in total revenue despite the drop in in-app purchases.

Do Video Ads Canniblize In-App Revenue?





The tests ran were under the condition that users could watch up to 4 video ads a day, as was the limit set at Social Point. However due to an intentional development change, users were able to watch up to 8 per day. Therefore the results changed a bit.

They quickly found that 39% of their payers (users who were doing IAPs), were watching up to 8 videos resulting in a significant drop in IAP revenue, and even further, the ad revenue was not off setting the drop in IAP revenue and cannibalising the revenue.

Too many rewarded videos results in drop in revenue


  • ”PULL” video ads have no impact on churn
  • ”PUSH” video ads have a small negative impact on churn
  • Video ads DO canniablise IAP revenue
  • IAP + AD revenue can be greater than IAP alone
  • Be careful – don’t allow Payers to watch too many ads

There were two great questions raised by the audience members which really touch upon the importance of analyzing advertisers, churn, eCPM as key drivers.

  • Q1: In the place where you raised the cap on video ads, did you see a drop in the eCPM and was that what impacted the video games short fall in the IAP?
  • A: Yes exactly. As soon as you go to a higher number of video ads, the players are less likely to convert on those video ads.
  • Q2: It is possible to optimize your ad stack to make up for the drop in eCPM?
  • A: Possibly, one of the challenges we’ve had is quite often the mediation platforms don’t have enough inventory.

To close, SOOMLA provides a series of tools helping monetizers, marketers and even product managers analyze critical KPIs on their app’s performance.


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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.

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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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.




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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App Monetization, Research

SOOMLA Webinar # 1 Lotum Case Study on ads and churn

This week we ran our very first webinar at SOOMLA, in an effort to give a bit more visibility and break down to our recent data report on Lotum. The report’s main focus was on the effects of advertising direct competitors on churn and eCPM. Thanks to our very own Yaniv Nizan who took some time to break down the report.

Here is the recording of the webinar! You can find the data report here as well as the full transcript of the webinar below the video.

Start Webinar Transcript

Ben – Hey everyone and welcome to SOOMLA first Webinar, I am Ben Lerner the Director of Marketing and I am joined by our very own CEO, Yaniv Nizan.

Yaniv – Hey, happy to be here, super excited and welcome everyone.

Ben – I’m going to give everyone a very quick intro, these webinars are something we plant o do a monthly basis. There is a lot of great content on our blog including previous reports, but we’re hoping this will help make things a bit more accessible. Today we’re going to be discussing our case study on LOTUM. LOTUM is one of our customers who used Traceback to help gain some really interesting insights. One of which was that specific advertisers resulted in a 3x churn rate, but I think more importantly in all that, it wasn’t quite who they expected.

Before we get into that, Yaniv why don’t explain a bit about SOOMLA and what the Traceback platform is.

Yaniv – Sure, so SOOMLA is an ad measurement platform, and more specifically, we help app publishers measure their monetization. To give you an example, today app publishers don’t know who is advertising in their app, it could a competitor, it could be another app that is taking their users.

Ben – Ahh yes, the infamous black box of advertising that everybody talks about. I’m sure we’ll get more into that, but for now let’s jump straight into the study itself. To give a quick brief on LOTUM, they have a casual word puzzle game called “4 Pics 1 Word” which is available in 8 languages and considered to be one of the top word games in the industry. Yaniv, want to take it from here?

Yaniv – Sounds good, so the context of this report is that we realized that many app developers who used ads, faced the same issue of whether or not to advertise direct competitors.

Ben – Oh yeah absolutely. I personally follow a lot of Indie developer forums being a big gamer myself, and I consistently see issue being raised whenever ad monetization discussion begins.

Yaniv – Yea so the problem is that most app publishers follow their gut feelings when it comes to this. They don’t have any real data to back it up.

Ben – Yea I have seen time and time again – the big warning sign the the skull and crossbones saying – “Don’t allow direct competitors to advertise, they will steal all your users and disappear.”

Yaniv – This sow here Traceback comes in to help Lotus break things down. We can jump into page 3 of the report, and what you can see here is the top 8 advertisers that LOTUM had in the US in the period we measured this. For the purpose of this report we defined Churn as users who clicked on an ad inside the game, but didn’t come back to the game within a 7 day window after clicking on the ad. So if the user did not come back, they are considered to be a churned users. So what you can see here, some of the games like Game of War for example, has 3x more churn. So when Game of War is being advertised in LOTUM app, users that clicked on that are 3x more likely to not come back.

Ben – Really? Okay so seems kind of crazy the nobody has analyzed this until today. Just a question though, what are the actual numbers we are talking about here? Are we talking about churning in the thousands of users, hundreds of users? All I am seeing here are graphical displays.

Yaniv – Yea so this report doesn’t show the exact numbers. Obviously this is confidential information that LOTUM preferred to keep to themselves and we totally respect that for our customers. To give you a range where this could be, typically if we look across all of our customers the churn rate caused by advertisers comes between 3% up to 25% caused by specific advertisers.

Ben – So to fully grasp what you’re talking about, your saying that the potential range is not 3x but closer to 8x. Whats the biggest range you’ve ever seen in a single game?

Yaniv – Yea so 8x is across all the games that we are seeing and I’m saying games, but its also broader than that, as we also have non gaming apps as well. But in a single app or game, we’ve seen a difference of up to 4.5x churn rate between the lowest and highest churning advertiser.

Ben – Wow, but correct me if I’m wrong, isn’t Game of War not a direct competitor to 4 Pics 1 Word?

Yaniv – Yea and this is the part that also surprised us a bit and also Lotum. So Game of War isn’t even a word game and Lotum’s app is. These games are very difference in nature and still this is the advertiser that was taking away the most churn. So when we say this, we wanted to look specifically about whats happening with direct competitors vs non and take the opportunity to dig a little deeper.

Ben – So its literally going completely opposite to whats the industry standard right now.

Yaniv – So as I mentioned before we had a drill down about this specifically. If you look at pages 6 and 7, this is the area where we focused on that. So we looked at all the advertisers and classified them into groups. We didn’t just look at the top eight, but many more. The groups were: Non Games, Other Games and Direct Competitors. For each one of these advertisers we measured two parameters: The churn rate of advertisers in this group and eCPM.

Ben – So thats very interesting and I imagine this means that there is no negative implications for advertising direct competitors. Is it safe to assume that competitors will be paying more to advertise in the app?

Yaniv – Yea so great question, so if you look at page 7, this is what I was saying before. We also measured the eCPM of each one of these groups and what we have seen quite consistently is that direct competitors do pay more to be placed in the app. But as you mentioned before a lot of time there is no negative impact.

Ben – Great so I think these case studies are great but I think a lot of our users would love to see how this has all been possible. Do you think we can spare a few minutes and jump into the Traceback platform itself?

Yaniv – Absolutely, so let’s jump into Traceback. For the sake of this section, we’ll use our demo app called Muffin Rush, which contains a bunch of sample data. So the data is based on one of our live apps, but we masked everything to protect the confidential data of course.

Ben – Yea of course, makes sense. Sow act does it look like once I login, what am I going to start seeing, what data am I going to start seeing? Go for it.

Yaniv – Cool so now that I clicked on the app, I’m int he overview screen once I logged in. This shows you aggregated data and allows you to follow the trends for the app.

Ben – Okay but I see there are some deeper drill down screens. Which one should we be focusing on? I’m thinking the section most most relevant is one that we are looking at advertisers themselves. Can you breakdown what we are looking at?

Yaniv – Yea so on the top menu you can see all the different breakdown screens. One for segmenting and AB testing, another to analyze how ads impact your marketing activity, another how to optimize your waterfall. But as you me toned, the most interesting one for this discussion is the advertiser screen.

Ben – I see you already have the US country filter selected and the interstitial ad types.

Yaniv – Yea so obviously it makes sense to compare advertisers using the same ad format and country, otherwise you’ll be comparing apples to oranges and you don’t want to do that. I can also select different date ranges and change the filters as well.

Ben – Great os it looks pretty intuitive. Each row represents a specific advertiser. Under each one you’re seeing whats the eCPM, whats the total revenue, how many ads were shown etc.

Yaniv – Yea so you can slo control the columns via the three dots on the right to control which columns are being displayed.

Ben – Are there any further drill downs we can go from here?

Yaniv – Yea so if I click on word crossy for example, I get a more specific drill down to them. So this advertiser is coming to my app both through Facebook Ad Network as well as AdMob and actually I can see here that both are paying different eCPMs for this advertiser.

Ben – Well this looks great and I’m sure it has some incredible applications for anybody that knows how to break through all of this data. Tying back to the report itself, LOTUM had asked you guys to produce this report for them, but is this something you do for all of your customers.

Yaniv – Right so we obviously understand that the amount of data can be overwhelming and not everyone has the time to really analyze everything and this is why we assign a dedicated customer success manager who’s job it is to help the customer identify areas where they can improve. This was the case with LOTUM. We gave them this report and allowed them identify different areas to improve.

Ben – Great Yaniv, I wanted to thank you for taking the time to break down the report and more importantly, showing us the the results of Lotus are indeed possible for others given the insights.

Yaniv – Yea was my pleasure and hopefully we’ll run more of these soon with other key features,

Ben – Absolutely. Shout out to everyone for attending. We’ll be posting the recording of the webinar and some of the questions we’ve received throughout. See you all next time for another SOOMLA session. Thanks guys!

End Webinar Transcript

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SOOMLA - An In-app Purchase Store and Virtual Goods Economy Solution for Mobile Game Developers of Free to Play Games