Resource

App Monetization, Resource

top_10_resources_for_understanding_customer_lifetime_value

Customer Lifetime Value is one of the most important metrics to track for every service oriented business including free mobile apps, websites, free to play games, SAAS, music subscriptions, phone subscriptions and many others. There  is still, however, a lot of uncertainty around LTV calculations, how to use it and where to find the data to feed the formules. This post is trying to sort through the life time value maze.

Customer Lifetime Value Resource List:

1) Who Should Track LTV and Who Shouldn’t

Published: May 25, 2016

There are many resources showing how to calculate ltv but it’s really not for everyone. Some apps and websites should use other models.

 

img_33462) 6 Customer Lifetime Value Calculators

Published: Apr 26, 2016

6 calculators showing how to calculate customer lifetime value. Full explanation and links to additional resources such as spreadsheets and excel files. This is a great resource for anyone who is a beginner in LTV. Bookmark this link for future use.

3) Calculating LTV for Your First UA Campaign

Published: Jun 21, 2016

How do you calculate Life Time Value (LTV)? There are a number of formulas circulating but how do you know which is the right version for you? Here’s some tips and pointers that are specifically targeted for publishers are measuring LTV for UA campaigns.

4) 7 Analytics Platforms with Built In LTV Reporting

Published: Jun 30, 2016

Some analytics platforms offer LTV reports and also prediction of the lifetime value. This research brings together 7 platforms to consider and provides details about their LTV models and the pros and cons of each one.

5) Calculating LTV with Google Analytics

Published: Jun 8, 2016

Google Analytics for mobile apps doesn’t show LTV. These slides explains how to retrieve retention numbers and find the DAU in the Google Analytics screens. The slides show how to feed the data into an online calculator to get the LTV prediction.

5 surprising facts about customer lifetime value of mobile games6) 5 Surprising Facts about Customer Lifetime Value in Mobile Games

Published: Aug 7, 2016

LTV – life time value is a key metric many mobile game publishers follow. Here are 5 things that even some of the experts didn’t know.

 

7) Calculating LTV for a Mobile Game – Methosd for Different Stages

Published: May 9, 2016

Calculating LTV for a game in design phases is different compared to the soft launch phase which is again different from the lauch phase. This post describes the calcualtion in different phases and suggests additional resources such as CLV calculators.

8) Flurry Analytics – Calculating LTV (Slides)

Published: Jun 6, 2016

App developers who use Flurry analytics have hard time getting their LTV – user lifetime value. This presentation shows how to do it easily with a free online calculator. The first section is showing how to retrieve retention and DAU data from flurry dashboard and the second part explains how to use the calculator to ge the results.

 

9) Apple Subscription Model – LTV Formula

Published: Jul 5, 2016

Calculating LTV for apps that use the apple subscription model. This post includes a formula as well as a calculator.

 

10) Easy to use Customer Lifetime Value Spreadsheet 

Published: Sep 11, 2016

Our best LTV model brings together simplicity and accuracy. Input only 6 parameters and get d60, d90, d180 and d365 LTV results.

 

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App Monetization, Resource, Startup Tips

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Many app developers are looking to project their app revenue as they are starting out. This is obviously an important question as publishers needs to justify the development effort in their mobile apps. The answer is dependant on many parameters and quite complex to answer. However, we identified the key drivers and created the following calculator for you. Below the calculator you can find explanation of all the fields.

Mobile App Revenue Calculator

Calculator Explanation and Fields

The calculator has 4 parts:

  • Retention Inputs
  • Monetization Inputs
  • Traffic Inputs
  • Output / Results

Retention Inputs

Here you will need to input your D1, D7, D14 and D30 retention figures. If you are unclear about how to do this we highly recommend checking these guides for getting your retention in Flurry and GA. Even if you are using another analytics platform it will give you a sense of what you are looking for. In short d1 retention is how many users played your game 1 day after the first day they played. If you had 1,000 users that downloaded your game and played it in one specific day and the next day 350 of them came back to play again your D1 retention is 35%. One popular benchmark in the mobile games industry is 40%,20%,10% for D1, D7 and D30 retention – this is considered good retention and not all games get there.

Monetization Inputs

In order to calculate your app revenue, we need 2 types of monetization inputs: IAP and Ads. For In-App Purchase (IAP), the two input fields are:

  • Conversion rate to payers
  • Average Revenue Per Paying User (ARPPU)

The ARPPU is impacted greatly based on what type of app you have. Some apps and games simply sell remove ads for $1 and then the ARPPU will be $1. Strategy game apps on the other hand allow the user to build armies and castles by buying virtual currency and create a competative state that can lead users to spend hundreds of dollars in the app.

On the Ad side of things, you will need to enter the following fields:

  • Opt-in ratio to rewarded video
  • Number of rewarded videos you expect your user to see in a typical day
  • Number of interstitials you expect users to watch in a typical day
  • Number of banners per day

Note that most apps don’t have all 3 at the same time. If your app doesn’t have one of these ad types, simply put 0 (zero). The opt-in ratio to rewarded video is a tricky one if you haven’t started out yet. Consider these values:

  • 10% if you are hiding it inside the virtual goods store
  • 20% if you are prompting users in a specific situations as they run out of a resource
  • 40-60% if you are going to measure and optimize on this parameter and have multiple prompts on a daily basis

If your app have interstitial videos as opposed to rewarded videos, just treat them as regular interstitials.

Traffic Inputs

Another critical set of data for calculating the app revenue is how many users you will have. You will need to enter the expected number of downloads per day and the traffic mix between Tier 1 (US, UK, CA, AU, DE, FR, NO, FI, SE) and Tier 2 countries. If you are unsure about the values for these fields or other fields in the calculator you can also check out our game benchmakrs post.

Ouputs/ Results

Here you will find the estimated daily app revenue alongside other results:

  • User life days – this is how many days the average user will play in your game over his entire life
  • DAU – how many users open your app on a daily basis
  • Tier1 ARPDAU – the daily revenue per active users for tier 1 countries
  • Tier2 ARPDAU – the daily app revenue per user in tier 2 countries
  • The ratio of ad revenue out of the total

 

 

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Analytics, App Monetization, Resource

ltv model

In previous blog posts I posted 6 different LTV calculators and received a lot of feedback about the LTV models. Turns out game publishers found them super useful for calculating the LTV of their game. It was great to hear the positive feedback which also led to a lot of conversations about how people are calculating their LTV. Here are some of the learnings I can share.

Specific LTV model is always better than generic one

All our LTV calculators can’t be nearly as accurate as the ones you can build in-house. If you have the money to hire a data sceintist or at least contract one to build a formula for you after you have gethered some data, you will end up with a more accurate model. The reason is simple, in predictive modeling, the more signals you have the more accurate the model will be. All our calculators use retention and arpdau because they need to be widely applicable. However, there are a lot more signals you can feed to a specific model: tutorial completion, level progress, soft currency engagement, challenges completed, … Factoring such signals would give you a better prediction model. Our generic calculators’ main purpose is to get you started, give you a framework to think about LTV prediction and help you do some basic modeling if you are on a budget.

Simplified spreadsheet modeling

Our original spreadsheet model was taking in 31 points of data. However, after talking with readers I learned that most of you only track 4 retention data points and 1 arpdau point. This is why I created a version that is simpler on the input side. Another feedback I received is that you want more outputs: Day 60, Day 90, Day 180 and Day 365 LTV. Here is the new calculator based on all that feedback.

Inputs:

  • Day1 retention
  • Day7 retention
  • Day14 retention
  • Day30 retention
  • ARPDAU

Outputs:

  • Day60 LTV
  • Day90 LTV
  • Day180 LTV
  • Day365 LTV

Method:

This spreadsheet is the same one from the retention modeling we presented in this post but with a few tweaks.

The actual spreadsheet

 

If you want to measure the ads LTV in addition to IAP LTV you should check out SOOMLA Traceback – Ad LTV as a Service.

Learn More

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Resource

image

One of the most effective tools in business is using back of the envelope calculations using rules of thumb or benchmarks. This method is highly useful when trying to quickly evaluate opportunities before committing resources for in-depth research. In Mobile games, there are already established benchmarks for many KPIs you would need when trying to calculate things on an envelope. We collected 33 of these in this post. Save this link for the right time.

Retention and Engagement

  1. 2d retention – 40% is on the high side of the spectrum
  2. 7d retention – 20% is on the high side
  3. 30d retention – 10% is on the high side
  4. MAU DAU ratio – poor ratio is 1:10, really addictive games get 1:3 – 33% of their users play every day
  5. Session length in mobile games – 7.5 minutes is a good overall benchmark but some genres like card and board are getting between 10 and 15 minutes.
  6. Time spent per day – According to flurry the average user spent 33 minutes per day in mobile games during Q2/15. This stat is down from 52 in Q1 that year.

Marketing and User Acquisition

  1. Marketing spend from total revenue – If we look at public companies we can find these ratios in their income statements:
    • Zynga: 22%
    • Glu:20%
    • King:18%
    • In smaller companies we can expect the ratio to be closer to 30%
  2. CPI in tier 1 countries – high $10 (for strategy), low $2 (for casual games)
  3. Download boost when getting featured – games saw an average boost of 130% in H2/2015 according to a research by App Annie
  4. Top charts download boost – for games 100% boost (an additional organic install for every paid one)
  5. First week ROI on UA – For an app with 40%,20%,10% the first week contribution is 12%. For apps with worse retention, this number needs to be closer to 20%
  6. Top-10 threshold: Apple’s top free chart – 72,000/day, Apple’s top grossing chart – $47,000
  7. Top-25 threshold: Apple’s top free chart – 32,000/day, Apple’s top grossing chart – $23,000
  8. Top-50 threshold: Apple’s top free chart – 23,000/day, Apple’s top grossing chart – $12,000, Google’s top grossing – $6,600
  9. CTR – for banners we have seen reports of 0.25% to 0.75%, for intersitials it can go up to 5% and even 10% but a lot of those are accidental clicks.
  10. Install Rate – According to Branchmetrics – click-to-install rate is 11.9% on iOS and 13.5% on Android. US rates are lower – only 6%. The report also shows the install rate by channel.

Game Monetization

  1. ARPDAU in tier 1 countries – the lowest we have seen is $0.005 for apps with only banner ads and the highest report is for $1 for a hard-core strategy game targeting Japan. Glu sees $0.08 globally while Kabam, A Thinking Ape, PerBlue and Dena higher levels between $0.4 and $1 for hardcore titles.
  2. ARPDAU from ads alone in tier 1 countries – the lowest we have seen is $0.005 but with Rewarded video you can get all the way to $0.09 according to some reports.
  3. LTV in tier 1 countries (IAP+Ads) – The range here is quite high. Hard-core titles can reach $20 LTV (for all users – not just payers). The good casino games can get to $10. The bottom side of the range can be quite low if the game has no monetization it can be $0.
  4. LTV in tier 1 countries (Ads Only) – The lowest we have seen using TRACEBACK is $0.1 and the highest we have seen is $1.5
  5. Rewarded Video CPMs in tier 1 countries – we have seen reports of CPM going up to $60 in some genres. The numbers can go as low as $15 for the first impression and will go down for games that expose their users to too many
  6. Video CPMs in tier 1 countries – $8 to $15 in most games but if you have too many video ads it will decline below that
  7. Interstitial CPM in tier 1 countries – $5 to $10 eCPM
  8. Banner CPM in tier 1 countries – $1 to $3 eCPM
  9. Conversion to payers – 1.5% conversion is typical on a monthly basis and 0.3% on a daily basis.
  10. Top 10% revenue contribution – The top 10% of payers typically contribute 50% of the revenue in games with consumables or currency
  11. LTV of paying users (Total ARPPU) – In hard-core strategy games the average is about $500, in casino it’s usually $200-$300, in Match-3 it can get to $150 but $50 to $100 is more typical.
  12. Ad revenue proportion – In hard-core strategy games – 0%, mid-core strategy games and simulation games get 10%-15% of their revenue from ads, Casino games can see up to 50% of their revenue from ads, card and board games typically see 25%-30% ad revenue and more casual genres typically go above 50%

Market Research

  1. Calculating MAU from Ratings on Google Play:
    • Take the Ratings count from Google Play
    • Divide by the number of years the game was live
    • Multiply by 10 to get MAU Estimate (actual MAU might be 30% higher or lower)
  2. Calculating MAU from ratings on Google Play
    • Take the minimum number of installs from Google Play
    • Divide by the number of years the game was live
    • Divide by 2 to get an estimated MAU (Actual MAU might be 30% higher or lower)
  3. Number of apps per user – Android users have 95 apps on average
  4. New apps installed per month – The average user installs 1 app per month
  5. Total revenue in Mobile games in 2015 – $34B according to AppAnnie

 

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Announcement, Resource

app nanny is a free tool for app research

Today we are proud to continue the tradition of making free and open source tools with the launch of App Nanny. App Nanny is a unique tool made for mobile industry insiders who need to research apps quickly using Google or the App Stores. The tool simply surfaces key information about the app inside the search results so you don’t have to go back and forth in your browser in order to find interesting apps.

App Nanny enhances your app research experience

App nanny adds more information in cards when you search for apps The new tool is a Chrome extension which means that you install it with one click and after that App Nanny works behind the scenes and slightly modifies your app research experience. There are 2 main differences you will notice:

  • App cards will appear in your search results on Google
  • More information will appear in app thumbnails in Google Play and The App Store

What information App Nanny provides

The extension brings information from the app main page into your search results and thumbnails. The information is selected to help you identify the apps that you were looking for:app nanny adds information snippets when searching in google for cool apps

  • Main image (in Google search results)
  • Download count (in Google play)
  • Last update date
  • App publisher
  • Genre
  • Bundle ID

App Nanny saves you time while researching apps

Let’s focus on an example to see why App Nanny is great. Say you are researching for a blog post called “Top 10 Match 3 Games” you would need to search Google or the app stores and track mainly the name of the game, the image and the game popularity but you would also want to see if the game is recently updated. Let’s say that you would need to screen 200 candidates to find the top 10. It means you need to open 200 app pages and scroll down each one to find the relevant information. With App Nanny on the other hand – you get this info directly in the search results so you can save valuable time.

Improve your ASO with App Nanny

Another cool way to use App Nanny is to find out which terms are popular and the competition level. Searching Google Play for the keyword “banana” and the word “dash” allows you to quickly see that there are a lot more dashing apps and that they have a lot more downloads if you combine them. You can also see apps that have not being updated for sometime. These usually present an opportunity.

Hope you also find it cool and useful like we do. Feel free to give it a shot and give us any feedback that will help us improve it.

 

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App Monetization, Resource

image

There is a lot to be learned from the success of others and this is why case studies can be really effective if they are done well. However, it’s not always easy to find good case studies that don’t have a strong bias and are not too sales oriented. Here are 3 case studies I think any game publisher should read especially as ads are becoming a critical component in the app monetization mix.

Adding rewarded video in IAP heavy games – Next games

Unity did a very good case study with Next Games. The games themselves are high production quality games and one of them is also based on strong IP – The Walking Dead is an award winning TV series by AMC. With this kind of investment you can imagine that the games monetize mainly with IAP. However, Next games made a strategic decision to have rewarded video designed carefully into the game. In Compass Point West – they would have a wagon coming into the screen and offering players an incentive to watch a video. The players loved the wagon and the result is that Next game are seeing an ARPDAU of $0.06 from ads alone without any negative impact on IAP revenue. From an LTV perspective this translates to a full $1 of Ad LTV. So if their IAP LTV is $3, The combined LTV would be $4. This is critical for companies who do paid marketing and trying to constantly get the CPI below the LTV.

Take away points:

  • Video ads that are thoughtfully designed into the game work better.
  • Ads can yield $0.06 ARPDAU and $1 Ad LTV without hurting IAP revenue.
  • For companies who relay on paid marketing an extra $1 in LTV is critical for being ROI positive

Ad supported clicker games can do effective user acquisition

The next case study is also from Unity but it covers a very different type of game. FuturePlay creates clicker games that are relaying mostly on ads. 70%-75% according to Jami’s statement in a Panel from Casual Connect Amsterdam. Here the challenge was different – creating enough monetization to rise above the neccessary bar for paid marketing. Futureplay integrated video ads into the core loop of the game and was able to get as much as 80% opt-in ratio. More over, the combined ARPDAU they reached was $0.15. So roughly 10 cents from ads and 5 cents from IAP on a daily basis. With good retention KPIs such as 40%, 20% and 10% for d1/d7/d30, these $0.15 translates into $2.23 in LTV according to this calculator. This LTV is high enough to allow FuturePlay to do paid user acquisition. So they are an advertiser and a publisher at the same time.

Take away points:

  • Clicker games are a good platform for high paying rewarded videos
  • By integrating rewarded videos well you can reach 80% opt-in ratio
  • Even if ads make the majority of your revenue you can still have LTV as high as $2 and acquire users through paid channels

To read the full case study – click here

Even games with almost no IAP can have ROI positive UA campaigns

The last case study is about Gram Games. The company had phanomenal success with their game 1010 and are pioneers in the new trend of companies who are both a publisher and an advertiser. The case study points out that Gram was able to acquire users at scale with a reported CPI of $1 in US and grow to 20M users world wide. The relatively low CPI is possible for casual titles with wide appeal and a familiar gameplay. To reach an LTV higher than $1 in US, Gram games are relaying mostly on ads as a monetization strategy. The gameplay they created retains users for a very long time and 14% of their users stay after the first month. In other words, their retention is 40% better than 40/20/10 which is considered a very good retention. This means that even with a $0.05 ARPDAU they can get to $1 LTV. While having LTV = CPI is not profitable on it’s own, games like 1010! typically get an organic boost when acquiring users through paid channels.

Take away points:

  • Games with excellent retention can get over $1 LTV from ads only.
  • If your game has wide appeal and super casual gameplay you can buy users at $1 CPI
  • Super casual games with mass appeal often get an organic boost on their media spend

 

If your company has over 15% ad revenue and is marketing the game through paid channels you need powerful ad traceback tools like SOOMLA TRACEBACK.

Learn More

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Research, Resource

global gaming investor map shows investments in gaming companies by investors all around the world

While I was working on raising a round for SOOMLA I came across a post on local media that showed a map of all the Israeli angel investors. This map was based on a croudsourced spreadsheet that was first initiated by Eden Schochat at Aleph.vc. I thought that it would be really nice if someone made a resource like that for gaming investors.

Why did I create the Global Gaming Investor Map

Gaming investment is a polarizing topic – some investors love gaming and some hate it. There are very few investors that are in between. From this reason, just knowing what investors invest in gaming is super valuable. Beyond that, investors rely on their network for intros so knowing the investments of each investor allows gettting an intro through a portfolio company which is considered a strong intro. The map also shows what investors often invest together and pinpoint hubs of connections that could be key people to know.

the gaming investor map itself contains so much information that it can't be presented as an image and requires a special tool to be useful

A few notes about the map

The map above contains a lot of investors, venture firms, partners, companies and executives but it’s not complete. Surely I missed a many data points. I also know it has duplicates so it’s not perfect. The colors have the following meaning:

  • Green – VC that invests in gaming
  • Blue – Games company
  • Grey – Everything else which is mostly Executives, Partners, Angels and non-gaming companies.

To view the map you need to use mindmup.com or the mobile app.

Note that the map is given with full edit permissions – please don’t use it in ways that will make me regret it. Respect others and help build this resource futher.

 

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App Monetization, Research, Resource

the top 6 mobile ad mediation platforms compared and reviewed in great detail. The image includes the logos of Ironsource, Mopub, Fyber, Appodeal, Heyzap and AdmobFollowing the success of our recent posts comparing ad-networks, offer wall providers and push notification platforms I’m happy to provide you this research about the leading mediation platforms. We reviewed many candidates and only included platforms with demonstrated market traction and selected to include only platforms that have at least one thing that is unique and great about them.

I highly recommend reading this list alongside our post about the difference between ad-mediation, SSP and ad-server.

We reviewed each of the different providers from a few aspects:

  • Do they mediate on the client side, server side or both
  • Platform and Game Engine support
  • Ad format specialization – video, banner or interstitials
  • Monetization technique – do they charge a fee or place their own ads in return for a free service
  • Reporting user interface – can you understand what needs to be done for optimization
  • Ad network support – how many ad networks from the top 20 they support and are there any big providers missing
  • Special features worth mentioning

We ended up with two lists: one for video mediation and one for banner and interstitial mediation. Here are the top 3 in each category.

Video Oriented Banner Oriented
Fyber Admob
Heyzap Appodeal
Ironsource ( formerly Supersonic) Mopub

 

If your app is monetizing through ads you should get better tools to track your ad-revenue. Check out SOOMLA Traceback – Ad LTV as a Service.

Learn More

 

the logo of fyber, an ad mediation platform for mobile apps with a focus on mobile games and rewarded video

Fyber

Fyber took a strategic decision to put gaming publishers at the focus of the company. Their mediation platform definitely deserves a premium spot in the top 6 list. They focus mostly on SDK level mediation and support every meaningful video ad provider with the exception of Supersonic / Ironsource. Their list for banners and interstitials on the SDK side is a bit shorter but they can source these ads by making the inventory available through their SSP platform. Fyber’s hodling company RNTS recently bought Heyzap and Inneractive but so far they seem to be keeping the brands and the platforms separate.

Fyber’s monetization technique is to make the inventory available to their ad-network. This is the most popular method today but it creates a conflict of interest for the mediation providers who can’t maintain neutrality

Fyber’s reporting interface is easy to use and include important KPIs and metrics. It includes information about active users that is important for publishers to track impression frequency but it fails to track the opt-in ratio and doesn’t provide a good way to track the waterfall optimization. The ability to view performance by segment is also lacking.

Their Unique Advantage: Best coverage for video networks and best coverage for top 20 ad-networks

Platform support: iOS, Android, Unity, Adobe

Ad networks supported out of top 20: 13

Total ad networks supported: 16

the logo image of mediation provider heyzap, the company was recently bought by RNTS who are also the owner of fyber

Heyzap (Acquired by RNTS/Fyber)

Until recently Heyzap was an independant provider with no ad-network affiliation but since the begining of the year they are in the same family as Fyber and Inneractive and they are all held by RNTS. Their video network coverage is excelent and is done mostly on the client side through SDK adapters. They also have a nice support of interstitial and banner providers.

Fyber monetization technique is to place ads from their own ad-network which is mostly coming from placing the inventory for RTB. They also added demand from Fyber as a default setting in waterfall.

Heyzap’s reporting dashboard is very graphic and includes good visualization of the waterfall configuration alongside the historic eCPM and fill rates. It’s a bit lacking on the metrics and doesn’t include any data on unique users so it’s impossible to analyze ad frequency, opt-in and segments.

Their Unique Advantage: Waterfall visualization and interface simplicity

Platform support: iOS, Android, Unity, Adobe, Cordova, Buildbox

Ad networks supported out of top 20: 9

Total ad networks supported: 12

Ironsource (formerly Supersonic)ironsource mediation platform came to the company via the acquisition of supersonic. The platform is focus on rewarded video and doing well especially in the gaming sector

Supersonic mediation started as a rewarded video platform but since the acquisition by Ironsource the company have added interstitial and banner support. However, their focus still remains on mediating video through SDK adapters and the only provider not supported on that front is Fyber (and vice versa).

Like Fyber, the mediation technique here is also by placing ads from both Supersonic and Ironsource own demand sources.

The reporting interface is not as shiny as others but still effective. It includes 2 important metrics not supplied in some of the other platforms:

  • The number of active users – this allows to optimize the ad frequency
  • The number of “engaged users” – these are users who engaged with the rewarded video (opted in)

Another cool feature is that the management section indicates the historic eCPM of each ad-network and makes it easy to make waterfall management decisions. The platform is still missing a good visualization that includes fill rate alongside eCPM and the priority that the algorithm gave the ad-networks. Another miss is the lack of breakdown to segments in the reporting dashboard.

Their Unique Advantage: Reporting per user and indication of historic eCPM in auto-pilot mode

Platform support: iOS, Android, Unity, Adobe

Ad networks supported out of top 20: 12

Total ad networks supported: 13

admob by google is a popular ad mediation platform with great network coverage

Admob by Google

Like the ad-network, Admob’s mediation is better for banners and interstitials and not as good for rewarded video. Their coverage on the video side is lacking Mediabrix and Tapjoy but for banners and interstitials they have the best coverage for both SDK based integrations as well as S2S.

Their monetization method is to place their on ads in the bidding mix. These ads are coming from advertisers on Admob and from Adsense as well so their backfill sometimes includes text ads that might look very random in the context of your app.

Their reporting interface is not good. Google’s line of visually boring reports is a topic on it’s own but on top of that there are some serious challenges in getting the information you will need to see in order to understand what actions to take. The only hope is that Firebase is going to fix all that but we will have to wait and see.

Their Unique Advantage: The widest ad-network coverage

Platform support: iOS, Android, WP7

Ad networks supported out of top 20: 12

Total ad networks supported: 43

AppodealAppodeal are an up and coming mediation player with nice features and great features for small developers

Appodeal is a fast growing startup who already made a name for itself in the mediation space. The company doesn’t have an attached ad-network so can maintain unbiased position and focus on helping the publishers. It support all ad-formats and covers all the important players for banners, interstitials and native ads. On the video side they are missing Fyber, Mediabrix and Supersonic Ads.

One of the unique features about Appodeal is the ability to create custom segments and apply a different logic in this segment. For example, you can decide that females will see less ads or that people with older devices will not get video ads. Another important feature that is not available in all other platforms is the ability to define house ads for cross promotion or direct campaigns. There are also some great features for small developers like auto-registration and advanced payment.

The way Appodeal makes money is by brokering your backfill inventory. This means that when there is no fill from the ad-networks you selected, Appodeal will allow place the inventory on an exchange and allow other networks to bid on it. From this revenue, Appodeal will take their commission.

The reporting interface of Appodeal is simple and effective but it’s lacking on a few aspects. The ability to see the number of clicks is an important feature that other platforms don’t have. However, there is no visibility to the actual waterfall configuration that was set up in a specific day. The ability to track impressions per user and to monitor opt-in ratios for rewarded ads is also missing.

Their Unique AdvantageSegmentation feature and other advanced capabilities

Platform support: iOS, Android, Unity, Adobe, Cocos2d-x, Cordova, Marmalade, tvOS

Ad networks supported out of top 20: 11 through SDK and 2 more through S2S

Total ad networks supported: 25

Mopubmopub mediation and SSP platform provides a combination of ad network optimization alongside access to RTB markets

Mopub are combining an SSP with mediation in the same SDK. The company was acquired by Twitter in 2013 so adding your SDK allows you to receive ads from Twitter advertisers like Facebook Audience Networks gives you exposure to FB advertisers. The platform focus is on banners and interstitials more than on rewarded video. On the video networks they are missing: Applovin, Fyber, Mediabrix and Supersonic and on the banner and interstitial side they are missing Flurry.

Mopub monetization method is to bundle their SSP along side the ad mediation so they get access to the inventory and can get their cut through the ads they are placing.

The dashboard offered for managing the ad-networks is good overall and makes all the main functions easily accessible. The reporting is pretty good but lacking a few features to understand what’s happening on a user level.

Their Unique Advantage: Best access to RTB ads

Platform support: iOS, Android

Ad networks supported out of top 20: 10 through SDK and 1 more through S2S

Total ad networks supported: 11 through SDK and 9 more through S2S

 

These are the top 6 but there are plenty of other platforms out there so feel free to explore and try others. One platform that was pretty close to getting included is Ampiri by Glyspa we recommend checking it out as well.

 

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App Monetization, Resource

mobile ad networks logos including: Flurry, Fyber, Vungle, Mopub, AdColony, Revmob, Chartboost, Inmobi, Tapjoy, Millenial, Supersonic, UnityAds, Inneractive, Startapp and Applovin

A few months ago we did a post called top 20 mobile ad networks that became very popular. This post describes each network in words which is very useful. However, we recently realized that app publishers need a better tool for comparing ad networks to each other.

We collected the main features of 18 mobile ad networks into the google doc linked here. There are 5 Spreadsheets: Payout/Revenue, Mediation Support, Reporting API details, ad formats and General information.

Below are the details of each section.

Mobile Ad Networks Payout/Revenue

This section contains details about what you will be getting paid for: the business model of each ad network, the payment terms, payout methods and thresholds. We recommend also reading – 5 secrets of Mobile Ad Networks to gain further insight about this section.

  • Payment Model – this field indicates the commercial commitment made by the ad-networks – what are they actually paying for. Rev-share means that the mobile ad-networks pay a percentage of what they are making. It also means that you are only getting paid if they made any money regardless of the amount of ads you showed your users. Some ad networks indicate the share of the revenue they are paying. For example – if the table indicates 70% it means that the ad-network will be keeping $0.30 of every dollar paid by the advertisers after their deductions (read about deductions below)
  • Campaign Types – this indicates how the mobile ad networks get paid. Since the payment model is mostly rev-share based you need to understand how your ad-provider makes money to understand what you are getting paid for.
    • CPI – the advertiser is paying only after the user downloaded, installed and opened his app
    • CPC – the advertiser is paying when the user clicks
    • CPM – the advertiser is paying when the user sees the ad
    • CPCV – the advertiser is paying when the user finished watching the video ad
  • Minimum Payout – this field indicates the threshold you need to pass in order to get paid. Unpaid balances roll over to the next month.
  • Payment Term – mobile ad-networks don’t pay you immediately but rather wait a certain period of up to 2 months to pay. NET 30 for example means that revenue that was made during March is paid on May 1st – 30 days after the end of the month.
  • Revenue Deductions – when an advertising company promises to pay a percentage of the revenue they mostly refer to “net revenue”. This means that after calculating how much revenue the ad-network made from the impressions related to your site they start deducting certain costs up to 40% of the revenue. “Sole Discretion” means that the ad network may apply a fixed deduction of x%. Let’s assume it’s 20% as an example this means that if your rev-share is 70% and the ad-network made $1, they may first deduct $0.2 to cover their costs and then the $0.8 is shared so you actually get $0.56 (70% of $0.8) for every dollar made. “Consistent” means that the ad-network is providing the exact amount they are deducting. “Limited” means that the provider is only deducting in certain categories that are provided in the notes below the table
  • Links – for each ad network you will find a link to the publisher terms as well as to the payment FAQ page

Mediation Support

This section provides a table of which mobile ad networks supports which ad mediation platform. a cell in the table indicates that the ad-network in the left column of the selected row is supported by the mediation platform on the top row of the selected column. Each cell can have the following values:

  • SDK – this means that the both the mediation SDK and the ad-network SDK needs to be integrated and the mediation will also have an adapter to go along with each ad-network. This method id more popular compared to the alternative.
  • S2S – this means that the mediation provider will pull the ads from the ad-networks servers and present them in your app. This method has limitations especially with video ads and advanced formats.
  • Self – this means that the mediation provider is also the ad-network

Reporting API

This spreadsheet provides the details about the information available for automated reporting. This is important for companies who try to get further insight into their revenue using their internal BI tools. Here are more details about some of the fields:

  • Timezone – this indicates the timezone of the report and is especially important when trying to reconcile discrepancies
  • Data Update Lag – most mobile ad networks don’t make the data available in real time. This fields indicates how long the data is delayed and what’s the update interval
  • Time Granularity – indicates whether the API allows to get the data fields per hour or just per day
  • Other Dimensions – country, app, zone, user, traffic source, etc – a “yes” in this field means that the data can be queried for this dimension. For example, if the provider has a “no” in the “user” column it means that you can’t get the ad revenue or number of clicks per user.
  • Data Fields – these are the fields you can get back in the response. For example a “no” in the “installs” column means that the ad-network will not provide the number of installs

Ad Formats

This section indicates which ad formats are offered by each mobile ad network. For example a “yes” in “video” column means that the network offers video ads.

General Information

In this section you can find general information about the companies: How long they have been in business, where is the headquarters located, what platforms are supported and also links to their website and other useful pages.

Contribution Guidelines

We are interested in contributions for the spreadsheet. If you want to help us evolve this shared resource and keep it updated you will receive multiple karma points and likely to live a long life. Here is how you do it:

  • Clone the spreadsheet to your own google drive
  • Make the edits you want to make – add relevant references in the comments
  • Share the cloned spreadsheet with yaniv@soom.la – make sure you give edit permissions as it allows me to see revision history
  • I’ll notify you about the progress in email back to the email associated with your google drive. If you want to be notified to another email please provide it in the note when you make the sharing request.

 

If your company uses multiple ad-networks it’s important to know the ad revenue per user. Check out SOOMLA Traceback – Ad LTV as a Service.

Learn More

 

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