Analytics, App Monetization, Tips and Advice

Monthly vs. Daily Opt-in for Rewarded Video

Daily vs Monthly Opt In Rate - How to improve them and what value they can bring!

One of the charts we always recommend our customers to look at is the comparison between Monthly Opt-In and Daily Opt-In. This chart generated some of the more impactful insights and customers that acted on these insights ended up having nice revenue lift.

What is daily and monthly opt-in for rewarded video

Since rewarded videos are not forced on users there are users who watch them vs. users who don’t. The ratio between the number of users who watch videos and the total number of users who were active in the same time period.

We already discussed opt-in ratio in other posts including this one. This post however concentrates on one important aspect – the ratio can be measured on different time periods. When measured on monthly basis it will be the number of users watching at least one video ad in that month divided by the MAU.

At the same time, we can also look at the daily ratio. In this case we will be looking at the ratio between the number of users watching video ads in a give day and the daily active users, the DAU. In order to get a more reliable result, this ratio needs to be measured across multiple days and then aggregated to a single ratio using weighted average.

Monthly opt-in is always equal or higher than the daily opt-in

When comparing the monthly rate to the averaged daily rate over the month, the monthly opt-in will be at least the same number as the daily rate. To understand this let’s consider a very simple scenario with an app that only has two users. Both users were active in all the days in a given month. In all the even days, the first day user #1 watched a video and in all the odd days user #2 watched a video. Both the DAU and MAU will be 2. When we look at the monthly opt-in both users are watching videos so 2/2 = 100% opt-in. When we look at the daily opt-in however, in each of the days only 1 users watched a video so 1/2 = 50% in each day.

Why should you care about this

When thinking about opportunities to improve revenue, it usually comes down to how much more revenue can be generated compared to the cost of the additional effort. To address these for the opportunity at hand – we will need to make some assumptions. The 1st assumption is that optimizing opt-in rate trnaslates directly into the same proportion of revenue lift. This is something we have noticed pretty much in every app we are monitoring and was also reported by Ketchapp games in this talk. The 2nd assumption is that every users who watched a video in one day in a month and came to play in a 2nd day of that month can be convinced to watch a video again. There are a few reasons for that:

  • This user already showed that he interested in getting ahead in the game
  • The user is willing to watch videos
  • In apps that only allow some users (the ones less likely to pay) to watch video if a user already watched means he is in the right group

If these are true then the potential revenue lift in this opportunity is the precentage difference between the monthly opt-in and the daily opt-in multiplied by the daily revenue.

To put this into an example, an app that makes $200K monthly revenue from rewarded video ads and it’s Monthly opt-in is 50% while the Daily is 40% will be able to make $50K more per month by focusing on this opportunity.

Create a habbit with the right incentives, segmentation and popups

There are a few methods we can use to improve the daily opt-in to the monthly level. The most important step is to track this ratio to see which method creates an impact as we experiment. If you have the right setup for a/b testing this will allow you to get results more quickly.

Method 1 – Incentives and daily bonuses needs to work together

  • In many cases, users start a game with some coin balance and watching a video might increase that coin balance to a level that allows them to buy something meaningful with the coins. The second time the user comes into the game he will not have that initial coin balance so watching 5 or 10 videos to accumulate enough coins will seem less appealing. Bottom line – to improve daily opt-in, the daily bonuses needs to be designed along side the incentives for videos to amount to something meaningful together.

Method 2 – Simple pop-up for a segmented group

  • Sometimes, users needs to be reminded. If your platform allows you to pop up an in-game message to a segment of users you can target users who already watched a video in previous sessions with a prompt suggesting they should do so again.

Method 3 – Selling Insurance

  • People tend to buy insurance every time they fly abroad. However, if the insurance company will allow them to only buy the insurance when they need it, less people will end up buying insurance. Similarly, allowing a user to “save himself” by watching a video is less effective than allowing a user to obtain a “save yourself once” credit in return for watching a video at the beginning of a session.

So in terms of effort estimation, the effort might amount to a few days of studio work to set up such tests, a few hours here and there of testing and analysis. All in all I would be surprised if the efforts on this will exceed $10K in labor costs. This means that the return time will be 1 week for the numbers mentioned above so pretty good investment.

Feel free to share:
Analytics, App Monetization, Game Design

Inside SOOMLA: Advertiser Breakdown

Inside SOOMLA: A sneak peak into our Advertiser Breakdown screen.  One of the many unique and invaluable features within SOOMLA

In this installation of “Inside SOOMLA”, we’re going to show off our “Advertiser Breakdown” screen. In a nutshell, the entire purpose of this feature is to provide publishers with invaluable data about who is advertising in their app. Whether you want to understand which advertisers are paying out the highest eCPM, make direct deals, or see which advertisers are causing churn – this the place to get it all.

Ultimately, the ad experience is a double edged sword. On one end, ads can provide a significant boost to revenue and counter in-app purchase cannibalization by being properly monitored. On the other end, if not controlled, ads can ruin a user’s experience in the app and send them running for the uninstall button.

There are a few related posts to this – so I recommend checking them out for some context:

  1. 10 Mistakes That Will Keep Your Ad Revenue Low
  2. Data Based Formula – Which Advertisers to Block
  3. Q4 2017 Ads and Churn Case Study

There are several use cases that we’ve seen throughout the market for this data, so let’s take a look:

Case 1 – Advertiser Blocking Compliance

Ad-networks sometimes provide the ability for publishers to block specific advertisers. There are several reasons why publishers tend to do so:

  1. Publishers suspect that their direct competitors are causing churn (despite SOOMLA’s report on advertiser churn).
  2. Certain advertisers are deemed inappropriate for the target audiences of some apps.

These are valid reasons to want to block advertisers, however how does a publisher know that the ad-network is complying with their request. This can easily be tracked by drilling down into the specific ad networks and seeing all of the advertisers it pushes through via the campaigns.

CASE STUDY ON OPT-IN RATES & SOOMLA INSIGHTS

Case 2 – Comparing Ad Networks

More often than not, multiple ad networks are running the same campaigns, however not necessarily paying out the same eCPMs the the publishers. By drilling down into each specific advertiser, publishers can see understand which ad networks are offering what terms for one advertiser allowing you to compare ad networks to each other.

Publishers can begin to maximize their revenue potential on the per impression level like never before.

Case 3 – Doing Direct Deals

You’ve set up a deal to get ads in your app. Great. But do you know how many middle men there are between you and the advertiser? It could be 1, but it also could be 10. Each consecutive step in the process, someone is taking a cut, meaning publishers are leaving money on the table.

By knowing who is advertising in your app, you can build a priority list of advertisers you should approach and attempt to close direct deals with. Even if you don’t choose to close a direct deal, knowing the eCPMs of the advertisers through the ad-networks is still useful to establish benchmarks.

Conclusion

The Advertiser Breakdown analysis is another unique feature to SOOMLA that bring value to publishers who can utilize the data. Our quarterly Monetization and Insights reports can help make sense of all the data, providing some actionable insights. Check out our recent case study with Applife where our report insights boosted their rewarded video revenue by 94%.

In case you missed the previous “Inside SOOMLA” on Waterfall Analysis – be sure to check it out!

Feel free to share:
Announcement, Industry News, Tips and Advice

Hyper Casual Games – Thoughts about Voodoo and Gram Deals

Hyper Casual Games - Thoughts about Voodoo and Gram Deals with SOOMLA's CEO, Yaniv Nizan

Towards the end of May, the mobile game industry received news about 2 mega deals in 2 consecutive days. First it was Voodoo that announced a funding of $200M with an estimated valuation of over $500M. Then, the day after, Gram Games announced it’s acquisition by Zynga for a sum of $250M with additional sums to be paid against future results. Not surprisingly, these two companies share a similar philosophy and have been focused on games that monetize via ad revenue. Also, not surprisingly both, apply advanced measurement and optimization techniques for their ad monetization.

The new type of games that have been dominating the app stores since the beginning of 2017 is often called hyper casual games. The term first appeared in a series of articles written by Johannes Heinze from Applovin and published in the Applovin blog and in Pocketgamer. While the games have been visible on the app stores, the companies responsible for them often went undetected by press and analysts and remained an industry secret. One good example of these companies not getting detected is that both companies as well as Outfit7 (bought for $1B) were not included in AppAnnie’s top 52 publishers list.

Also, interesting to note is that these new direction of innovation is coming mainly from Europe. In addition to these 2 companies we can also add Ketchapp games, Outfit7, Tabtale as well many other smaller companies in Europe who are embracing ad driven models alongside a data driven approach and are dominating the hyper casual genres. From the US, companies such as Zynga starts to understand the potential and are compensating by acquiring such studios. Specifically for Zynga, the acquisition of Gram seems to be part of a strategy as the company also bought Harpen and paid Peak games $100M for their casual card game studio.

SOOMLA blog also picked up on the trend as early as 2016 when we noticed $300M going into companies that pioneered ad driven games. And then in March 2017 immediately after Harpen’s acquisition by Zynga, we identified Voodoo and Gram as strong potential for bigger deals in the future. Here are some additional companies who specialize in ad driven games that we recommend following.

  • Tabtale
  • Mobilityware
  • Etermax
  • Gazeus
  • Kwalee
  • Ilyon
Feel free to share:
Analytics, App Monetization, Marketing

Inside SOOMLA: Ad Waterfall Analysis

Inside SOOMLA's Ad Waterfall Analysis - an invaluable took for publishers to optimize their eCPM

As a marketer for SOOMLA, I’m often disconnected from the customers / potential clients themselves. Much of my time goes towards content writing, web design, SEO, conferences and the tons of other micro tasks that arise. However lately I’ve found myself sneaking into some of the demos our sales team gives to potential clients because.. well, it’s amazing to see.

Each customer has their own current setup, pain points, ad revenue, integrations, in-app purchases, ad types but one thing I have consistently seen is the reaction from some of the capabilities that SOOMLA brings to the table. This is why I started the “Inside SOOMLA” series to show off a bit, but also to give a sneak peak into our system for those who have yet to sign up and request a demo (which you can do here… shameless plug).

One of the most common scenarios that we see are app publishers leaving money on the table. There are a number of ways that this can occur, however specifically let’s look at the “Ad Waterfall”.

What is an Ad Waterfall?

Also referred to as daisy-chaining, simply put, the ad waterfall works as a prioritized series of ad networks or exchanges arranged from top to bottom in order of performance set by the publisher. The performance tends to be based upon the network’s history of payouts (eCPM), their fill rate, latency delays when serving ads and many more other potential reasons.

To gain some context on what makes the ad waterfall so important, we recently published a monetization benchmarks report which specifically looked at the importance of first impressions. TL;DR – Advertisers payout exorbitant eCPMs for first impressions as they understand their importance.

Q1 2018 MONETIZATION BENCHMARKS

Waterfall Analysis Screen

The entire purpose of this feature within SOOMLA is to give publishers the ability to make more data-driven decisions rather than biased ones. Publishers often times have a strong biased towards one ad-network since they see a higher eCPM coming from that network however this has been shown to be misleading. The position of the ad network in the waterfall often dictates the higher eCPMs and not necessarily the caliber of the ad network.

There are however other key features of this screen. By giving publishers the ability to visualize the data, they can make data-driven decisions towards changing up their ad-network mix, as well as helping to leverage this information for more beneficial discussions / negotiations with the ad networks. How is this all achieved you ask? Here goes…

Feature 1 – Ad Networks per Impression

This particular section shows full details about what is happening throughout the first ten impressions broken down by ad-network. Publishers see the number of impressions, the total revenue generated by that impression and the current eCPM, all broken down by the impression # in the ad waterfall.
Inside SOOMLA's Ad Waterfall - Ad Networks per Impression

Feature 2 – eCPM Decay Chart

What publisher wouldn’t like to know if they are achieving the optimal eCPM and not leaving money on the table? Thanks to this feature, publishers are now able to see just that. For the first ten impressions, publishers are displayed the “Actual eCPM” (the average across all selected ad-networks) while the “Optimal eCPM” represents the maximal eCPM attainable for the given impression by one of the ad-networks. For a more in-depth explanation about eCPM Decay, check out one of our posts on it.

Inside SOOMLA's Ad Waterfall - eCPM Decay

Feature 3 – Ad Network Comparison

This section visualizes for the publisher which ad-networks serve at which impression and how many ads they server daily. Furthermore, you can see exactly the eCPM paid by each ad-network for each impression count.

This is an invaluable tool in conjunction with the eCPM Decay feature as it allows you to break down why certain ad networks, while having higher eCPMs, are not displaying more ads as I’m sure publishers would like them to be. Low fill rate or bad choices vis a vis the mediation are often the culprits here.
Inside SOOMLA's Ad Waterfall - Ad Networks Comparison

Conclusion

Our Ad Waterfall analysis feature is unique to SOOMLA and one has one of two effects on potential clients of ours: 1) They are amazed and want to see a direct business case via their data, or 2) The stream of questions comes, asking how we achieve this, is the data credible and so on.

If you have any of these questions, or want to see a far more in-depth demo of SOOMLA (not just the Ad Waterfall feature), reach out and we’ll get one set.

Feel free to share:
Analytics, App Monetization, Game Design

How Applife’s Rewarded Video Revenue Jumped By 94% In 100 Days With SOOMLA’s Insight Reports

Case Study with Applife and SOOMLA's Insight and Monetization Reports

One of the great benefits afforded to our clients, is our tailored Insight and Monetization Reports that we produce for them on a quarterly basis. Just like it sounds, we have dedicated customer success managers that use mobile industry benchmarks and powerful analysis tools to make sure our customers can convert their data into actionable insights.

Our Insight and Monetization Reports have been beneficial to our clients and for Applife it was no different. Here you can find a copy of a sample Monetization Report.

Applife, has been a customer of ours for a little over 4 months at this point. They have several apps, however the one we took a look at is “Parking Escape”. Parking Escape is a casual sliding block puzzle game. The goal of this game is to get the blue car out of a six-by-six grid full of automobiles by moving the other vehicles out of its way. The game contains 6 difficulty levels with thousands of puzzles to be solved.

Our analysis noticed a severe drop off in users’ opt in rate to rewarded videos after the first week of and immediately noticed a strong opportunity to boost Applife’s rewarded video revenue. Get the full report and case study below, seeing how Applife was able to boost their rewarded video by revenue by 94% within 100 days of using SOOMLA.

CASE STUDY ON REWARDED VIDEO REVENUE & SOOMLA INSIGHTS

Here are some related articles that can help:

  1. Measuring and Improving Opt-In Ratio with SOOMLA TRACEBACK
  2. 4 Proven Tips for Improving Opt-In Rate – Based on Data
Feel free to share:
Analytics, App Monetization, Game Design

Japan eCPM Benchmarks Series – Top Advertisers Comparison

Japan eCPM Benchmarks Series - Top Advertisers Comparison

We’re back for another installation of Japan’s eCPM Benchmark Series! In the 3rd (and final) part, we’ll be looking to compare the performance of advertisers who serve interstitials and rewarded videos in Japan. In order to be as concise as possible, we’ll be looking into the top 10 performing advertisers in each category. In case you missed the previous parts, can find part part 1 and part 2 here.

For each ad type, we will look into advertisers who were first impression focused, as well as those who maintained a low amount of first impressions. Furthermore, we looked at the top performing advertisers, broken down by iOS and Android in terms of first impression volume and eCPM.

Why 1st Impressions

By focusing on 1st impression monetization, we are able to provide a better measure of the strength of different monetization channels. More importantly, it allows us the compare between advertisers on a more level playing field.

Ad networks will be able to see which advertisers are buying aggressively for each format and platform, while publishers can gain some insights on which advertisers are a potential fit for direct deals.

Note: As a base filter, we looked at apps with a minimum of 5,000 first impressions for the date range selected.

Interstitials – 1st Impression Lovers / Non-Lovers

The chart below shows advertisers that served a higher ratio of first impressions in the day compared to the total impressions.
SOOMLA's Japan Breakdown - Interstitial 1st Impression Lovers

To show the contrary, the chart below displays advertisers that have a lowest ratio of 1st impressions to the total impressions. These advertisers have not adopted a strategy focused on the importance of the 1st impression.
SOOMLA's Japan Breakdown - Interstitial 1st Impression Non-Lovers

While these charts might not be indicative of anything in this context, the next few charts showing the eCPMs can help give insights about advertiser specific strategy.

Top Advertisers for Interstitials – iOS

The chart below ranks the top 10 advertisers who placed ads in other apps via different channels. The comparison of these advertisers is based on 2 dimensions – 1st impression eCPM and 1st impression volume.
SOOMLA's Japan Breakdown - Interstitial Top Advertisers iOS

We can see that Kurashiru, Homescape and Wooden Block Puzzle are the only 3 advertisers that are performing above average (green line) for both 1st impression volume and eCPM. Another interesting note is that Fill has a very high eCPM payout in comparison to the other advertisers despite having a fairly lower volume of impressions.

SOOMLA's Japan Breakdown - Interstitial Top Advertisers Android

For Android, we can see that only Hidden City – Mystery of Shadows maintains an above average 1st impressions volume and eCPM in comparison to other advertisers.

Q1 2018 MONETIZATION BENCHMARKS

Rewarded Videos – 1st Impression Lovers / Non-Lovers

The chart below shows advertisers that served a higher ratio of first impressions in the day compared to the total impressions.
SOOMLA's Japan Breakdown - Rewarded Videos 1st Impression Lovers

Yes, 96% and 91%. I saw it as well and was positive there was an error in my data, however after triple checking, the data was in fact accurate. Both of those apps are ENTIRELY focused on 1st impressions.

To show the contrary, the chart below displays advertisers that have a lowest ratio of 1st impressions to the total impressions. These advertisers have not adopted a strategy focused on the importance of the 1st impression.
SOOMLA's Japan Breakdown - Rewarded Videos 1st Impression Non-Lovers

Top Advertisers for Rewarded Videos – iOS

The chart below ranks the top 10 advertisers who placed ads in other apps via different channels. The comparison of these advertisers is based on 2 dimensions – 1st impression eCPM and 1st impression volume.
SOOMLA's Japan Breakdown - Rewarded Videos Top Advertisers iOS

For this case, we can see that no apps are performing above average for both 1st impression volume and eCPMs. However we do see that Hidden City is dominating the 1st impression volume, while Matchington Mansion and Seeker’s Notes maintains very high 1st impression eCPM payouts.

SOOMLA's Japan Breakdown - Rewarded Videos Top Advertisers Android

For Android, we can see an almost mirroring of iOS. There are no apps that are performing above average for both 1st impression volume and eCPMs. Hidden City however has appeared on the high end of 1st impression volume for both iOS and Android.

Conclusion

This concludes our first eCPM Benchmark Series who’s sole focus has been on Japan. In our next series, we will be looking at India and how the growing gaming market is now one-tenth of all global gamers.

In the spirit of being big in Japan, enjoy the closing song!

Feel free to share:
Announcement, Events, Marketing

MAU Vegas 2018 Ultimate Attendee List

We've got the ultimate spreadsheet containing 998 companies and 1862 attendee who are attending MAU Grow in Vegas this year.  Want to take a peak?

MAU Grow is in a few days and we’re excited to be attending. Based in Vegas, MAU Grow is considered to be the world’s leading mobile acquisition and retention summit of the year, attracting some of the top mobile brands for a full two days. The conference is packed with networking events and keynote speakers from some of the world’s top marketing talent. You can find the full brochure / overview here if you want to take a look.

Who is coming?

The number one issue with most conferences is combing through the hundreds (in this case thousands) of people attending and finding ways to reach out the them.
I’ve done the hard work for you! In the spreadsheet below you can find a list of 998 companies and 1862 attendees that are going to be at MAU Grow this year in Vegas. To make it even easier for you, I’ve added the name, title and company for each attendee.

Downloading, Copying and Editing this Spreadsheet

Here is a direct link to the spreadsheet.

You can download this Spreadsheet or copy to your own Google Drive from the file menu once you open it. Please do not use the “Request Access” option as we will not approve those.

If your company is not in there and you want to add yourself to the list, simply email us to scottie [at] soomla [dot] com. We will be happy to add you.

Of course, SOOMLA will be there too so if you want to meet – drop us a line to scottie [at] soomla [dot] com.

How to connect with other companies

MAU Grow does offer an internal networking app, however it is only available for those who have applied, been approved and bought a ticket to attend the official event. For those of you who are not officially attending the event, this is why the spreadsheet is even more important. To connect with some of these companies we recommend utilizing the tried and true Linkedin – simply send people connection requests and ask for a meeting

If you found this helpful at all, we’d love to hear and of course feel free to share to anyone. Also, be sure to check out our latest series on Japan eCPM Benchmarks Series! Part 1 is a broader overview of iOS vs Android and Part 2 looks at the individual ad networks and their performance / dominance.

Feel free to share:
Analytics, App Monetization, Game Design

Japan eCPM Benchmarks Series – Ad Network Performance

Japan eCPM Benchmarks Series - Ad Network Performance

In the first part of our Japan eCPM Benchmark series, we kept a fairly broad approach to getting an understanding of how the Japanese mobile gaming market is performing. Before diving in to deeper breakdowns, it was important to look at the overall differences between iOS and Android.

There were some differences, but the most significant was how Rewarded Videos and Interstitials performed at near polar opposites. For Android, Rewarded Videos were far outperforming Interstitials in terms of eCPM payouts for 1st and overall impressions. On the other hand, we saw iOS dominating Interstitials with significantly higher eCPMs. Yes this is important, but at such a high level of analysis, it’s hard to gain actionable insights. This leads us to part two!

For the second part of our Japan eCPM Benchmarks series, we’re going to take a deeper look into the how the various ad networks are performing in Japan. Because we saw such a significant difference between iOS and Android in the ad types (Rewarded Videos and Interstitials), it only makes sense to keep the breakdown going in the same direction. It’s important to keep in the back of your mind that the majority of the mobile operating system market share in Japan is held by iOS, contrary to the rest of the world where Android maintains the larger share of mobile users. There are several reason for this, as one Tech blogger from Japan mentioned – if it interests you.

The Data

The data used for this series is based upon the data used in our recent Q1 Monetization Benchmarks Report collected through the SOOMLA platform. We analyzed the activity of over 30 million users in 8 countries over the span of 3 months (October 2017 – December 2017). Together these users viewed 600M impressions showing 2,500 advertisers in close to 100 apps. The app sample consists a higher ratio of games compared to the ratio of non-games in the app stores. However, we’ve seen the same patterns regardless of app category. The ad-formats analyzed through the study are: Interstitials, video interstitials and rewarded videos.

Interstitials – Premium Paid for First Impressions

This section looks at the premium paid in eCPM rates for 1st impressions compared to the overall average for ad networks prevalent in Japan’s interstitial domain. We compared this premium across all ad-networks who serve a high volume of interstitials. We’ve indexed the average eCPM as 100% and then presented the 1st in comparison.

SOOMLA's Japan Breakdown - Interstitial iOS - 1st Impression Lift*Only ad networks with over 1,000,000 total impressions during the data period were considered.

Japan eCPM Benchmark Series - Interstitials Android 1st Impression Lift*Only ad networks with over 100,000 total impressions during the data period were considered.

First and foremost, it’s important to note the vast difference in minimum impressions for Android and iOS. The majority of interstitial ad impressions recorded are from iOS, confirming the majority of Japan’s iOS adoptance. Furthermore, after a deeper look, the data sample has a slight bias due to a large portion of the impression counts originating from a few highly successful mobile apps. Regardless of this, we can still see that iOS does maintain significantly higher payouts for 1st impressions than the average eCPMs.

Q1 2018 MONETIZATION BENCHMARKS

Interstitials – Share of Voice

Share of voice refers to the percentage of impressions each ad network displays of the total. We broke this down into 1st impressions and total impressions for ad networks displaying interstitials in Japan.

Japan eCPM Benchmark Series - Interstitials Share of Voice
See original Android – Share of VoiceSee original iOS – Share of Voice

For iOS – we can see that AdMob take a large share of both 1st impressions and total impressions. Mopub for instance has a strategy more focused on 1st impressions compared to their total impressions. For Android – taking into consideration the previous comments, we see that AdMob maintains the lion’s share.

Rewarded Videos – Premium Paid for First Impressions

This section looks at the premium paid in eCPM rates for 1st impressions compared to the overall average for ad networks prevalent in Japan’s rewarded videos domain. We compared this premium across all ad-networks who serve a high volume of rewarded videos. We’ve indexed the average eCPM as 100% and then presented the 1st in comparison.

Japan eCPM Benchmark Series - RewardedVideos iOS 1st Impression Lift*Only ad networks with over 300,000 total impressions during the data period were considered.

Japan eCPM Benchmark Series - RewardedVideos Android 1st Impression Lift*Only ad networks with over 300,000 total impressions during the data period were considered.

For iOS – we see, as expected, the majority of the ad networks have a higher first impression eCPMs compared to the total, however AdColony is the only ad network which the first impression eCPM is lower than the average. For Android – we see TapJoy with a significantly higher first impression eCPM ratio compared to the other ad networks.

Rewarded Videos – Share of Voice

Share of voice refers to the percentage of impressions each ad network displays of the total. We broke this down into 1st impressions and total impressions for ad networks displaying rewarded videos in Japan.

Japan eCPM Benchmark Series - Rewarded Videos Share of Voice
See original Android – Share of VoiceSee original iOS – Share of Voice

Across both iOS and Android, we see that Ironsource servers large portions of the 1st and total impressions that are served, only to be surpassed by Applovin in Android. It seems like Ironsource’s dominance as a mediation for rewarded videos allows it to obtain a high number of impressions without paying a premium for it. For Applovin, it’s possible that their self-serve interface for advertiser is able to generate higher demand diversity which translates into better results in later impressions.

Conclusion

This concludes part two of the Japan eCPM Benchmarks Series where we took a deeper look into the performance of ad networks for interstitials and rewarded videos. In the next part of the series, we will be looking into specific advertisers : which love being first (impression), which don’t, which have high volumes and which have high eCPMs. See you then!

In case you missed part one, you can find it here.

Feel free to share:
Analytics, App Monetization, Game Design

Japan eCPM Benchmarks Series – iOS vs Android Breakdown

Japan eCPM Benchmarks Series

We’ve received a lot of great feedback based on our recent data report, so we’ve decided to conduct further drill-downs on a country basis.

Japan is well known for its expansive gaming market that has been growing rapidly over the past few years, and according to a recent study by AppAnnie, mobile gaming revenue increased by 35% in 2017 year over year.

For the first part of our Japan eCPM Benchmarks Series, we will look breakdown on how iOS and Android are performing.

The Data

The data used for this series is based upon the data used in our recent Q1 Monetization Benchmarks Report collected through the SOOMLA platform. We analyzed the activity of over 30 million users in 8 countries over the span of 3 months (October 2017 – December 2017). Together these users viewed 600M impressions showing 2,500 advertisers in close to 100 apps. The app sample consists a higher ratio of games compared to the ratio of non-games in the app stores. However, we’ve seen the same patterns regardless of app category. The ad-formats analyzed through the study are: Interstitials, video interstitials and rewarded videos.

Q1 2018 MONETIZATION BENCHMARKS

Overall Android vs iOS

In this section we’ll keep it fairly broad and as we progress, we’ll get more in depth. For now, we will look at the high level eCPM benchmarks for Japan – how Android is performing in comparison to iOS. Similar to the main report, the aim is to show the vast differences between the eCPMs being paid out for the first impressions.

SOOMLA's Japan Breakdown - by OS

To no surprise, we do see a similar trend in Japan as we do for overall Android and iOS. iOS does tend to overall have higher payouts for eCPMs, while both maintain first impression eCPMs that are up to 1.43x higher than the average impression eCPM.

Ad Type Breakdown

The next drill down will be looking at the overall performance (in terms of eCPM payouts) of ad types in Japan. For the purpose of this section, we’ll be looking at Rewarded Videos and Interstitials (includes video ads and playable ads).

SOOMLA's Japan Breakdown - Android

SOOMLA's Japan Breakdown - iOS

Generally speaking, the comparison between Interstitials and Rewarded Videos is nearly identical at this level of breakdown, however as we can see above there is a significant difference between Android and iOS. While it’s difficult to say exactly what the reason behind this is, it’s worthwhile to understand the unique features of the Japanese mobile gaming market which can provide some insights.

Interstitials iOS have significantly higher eCPMs payouts as well as a ratio of 1st to average impression eCPM.

This is the first part in the series, so the breakdown is kept to be very high level. In the next part, we will be looking into the performance of the individual ad networks. Stay tuned!

Feel free to share:
Announcement, Events, Marketing

Ultimate GDC Spreadsheet with 715 Companies

We've got the ultimate spreadsheet containing 715 companies who are attending GDC in San Fran this year.  Want to take a peak?

GDC is next week and we can’t be more excited. The San Francisco based Game Developer Conference is the biggest event of the year for mobile game developers around the world and attracts some of the biggest names in the industry for the entire week. The conference has many satellite events, mixers, dinners and parties. The biggest satellite event is Game Connection America which is more focused on business transactions and brands itself as the “deal making summit”.

Who is coming?

With so many things going around it’s easy to get lost so we wanted to offer a quick way to know what companies and people will be there. In the spreadsheet below you can find a list of 715 companies that will be at GDC or one of the satelite event. For some of them, the spreadsheet also includes the names and titles of the attendees.

Downloading, Copying and Editing this Spreadsheet

Here is a direct link to the spreadsheet.

You can download this Spreadsheet or copy to your own Google Drive from the file menu once you open it. Please do not use the “Request Access” option as we will not approve those.

You can also download an Excel version here.

If your company is not in there and you want to add yourself to the list, simply email us to scottie [at] soomla [dot] com. We will be happy to add you.

Of course, SOOMLA will be there too so if you want to meet – drop us a line to scottie [at] soomla [dot] com.

How to connect with other companies

GDC does offer a meeting system but it’s not considered a very good one. On top of that, most of the people who are coming to the event will not actually be buying a ticket to GDC. This is why the spreadsheet is even more important. To connect with some of these companies we recommend these 3 ways:

  • Game Connection – the ticket is a bit expensive but this is the most effective way to generate meetings during GDC week.
  • GDC Meet to Match – system to arrange and request meetings to registered attendees.
  • Linkedin – simply send people connection requests and ask for a meeting

 

Feel free to share: