App Monetization

App Monetization

network of ad providers participate through multiple hops to create a never ending fill rate of ads in your mobile app

If you have been placing ads in your apps, you have already heard about fill rates and how combining ad-networks through a mediation platform can help you optimize for fill rate.

Fill Rate – the percentage of the publisher ad requests that get a positive response (fill) by the ad network

The math is simple, if you have fillrate below 100%, you are leaving money on the table. Ad-networks have a finite number of advertisers so they will eventually run out of ads to show and so combining a few networks makes sense.

Well…. things change quickly in the mobile ecosystem.

Ad-networks outsource demand

In reality, the situation is a bit different. Most ad-networks have a finite number of direct advertisers but they also make their supply available to other networks. In other words, the ad-network will respond to ad request with their own ads as long as they have them but when they run out they will simply ask other ad-networks if they have ads. If other ad-networks have ads, they will show ads from those networks. This means that the fillrate will be high even for a single ad-network. However, these has some noticable downsides.

eCPM drops when outsourcing demand

What happens when ad-networks are taking ads from other networks? Simple – they are adding more middle mens and more mouths to feed. Let’s say that today you are getting 50% of what the advertiser pays – this is a common situation even if the quoted rev-share is 70% due to ad-network deductions – the standard rev-share only applies when there is one ad-network in the middle. If the ad-network is outsourcing their demand, it means that there are multiple parties that take a share in the middle. If there are 3 hops for example, the publisher will end up getting 12.5% (50% x 50% x 50%) from what the advertiser originally paid.

Adapting to the new situation

It’s pretty hard to tell when an ad-network runs out and starts out-sourcing. However, what you can do is enforce minimal eCPM floors on all networks that you are integrating through your mediation platform. If you enforce an eCPM floor of $1 for rewarded video in US for example, you will start noticing that your fill rate is not 100% anymore on every ad-network. Play around a bit with the threshold to find the right minimum. This will allow you to limit ad-networks to direct relationships. You will also have an indication when they run out – you will see the fill rate gows down. If that happens, this means you need to integrate more ad partners to increase demand. However, you will be integrating them as direct sources and not through a middle man.

Actively tracking your eCPM decay allows you to spot the drops in eCPM that indicates the ad-network is introducing another hop. Check out SOOMLA Traceback to get a grip on your eCPM decay

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App Monetization, Game Design

Getting your users to day 365 retention is the equivalent of LTV heaven illustrated as a tropical island in calm waters.

I recently attended Pocket Gamer Connects event in Helsinki. It was super productive for us so first of all I should think the Pocket Gamer guys who set this up and the amazing gaming industry in Helsinki. Big shoot out to you all.

One of the panels I enjoyed on the conference introduced Saara from Next Games, Eric from Dodreams and Jari from Traplight. It was called LEARN HOW TO DRIVE PLAYER ENGAGEMENT FROM THE BEST IN FINNISH MOBILE GAMING. One of points raised by Eric was that it’s a great feeling to see players come back after 6 months or 1 year. In fact, it’s not just a great feeling, it also means great LTV. If you followed our 5 things you didn’t know about LTV post you already know that two thirds of the LTV is after day 30. However, games that can keep users coming back at day 365 often find that it’s much more. Losing some users between day 0 and day 30 is natural but if you can keep most of d30 users coming back month over month you will see that most of your LTV comes from those long retained users.

Specific Example:

One of the games I analyzed had 52.9%, 29%, 18% for d1,d7,d30 retention. These numbers are very good to say the least but he still lost 82% of his users. The interesting stuff is what happens after, users keeps coming back and the D365 LTV is almost 2x the D180 LTV. You can run the numbers yourself here.

Here are a few tips on how to get users to Day365:

Tip 1 – show the users something fresh every time

Updates are super important if you want to retain your long term users. Games gets boring fast but if you keep pushing update you can keep users engaged. If your updates follow a consistent schedule you are likely to have users that expect the updates and even complain when updates are delayed. A good example for that is Color Switch – this popular game has very high retention rates. One of the reasons for that is that every time you open color switch there is some new game mode waiting for you. The experience never gets old.

Tip 2 – give your users influence

Some games have ways for the users to create levels and challenge others. This is a great way to retain users and make them passionate about your game. Others don’t have native ways to do it but can still give the most loyal users ways to influence by creating special forums for them and making sure they know their opinions matter.

Tip 3 – make your game endless or close to it

Think about how many levels candy crush has – 2,620. You can play this game forever and yet they are adding new levels. The reason is that if a user ever reaches the last level he will leave for sure. Random games may not need to make new levels all the time but they need to make sure the experience doesn’t become repatitive and that there is enough content to create new variations.

 

If your company has good retention and is monetizing through ads it’s important to know the Advertising revenue per user. Check out SOOMLA Traceback – Ad LTV as a Service.

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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.

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App Monetization

An ad-network employee looks at data from thousands of impressions to calculate the game developer eCPM and payout

If you have been placing ads in your apps, you are not alone. More and more apps are doing so and even the top grossing games have reached 50% ad penetration. Figuring out how your payout is calculated, however, proves to be a very difficult task. The ad-networks report an eCPM level that along side the impression volume makes your payout as shown below:

Basic formula (that is actually wrong):

Payout = Impression volume x eCPM

In reality, the situation is a bit different. eCPM is only calculated in retrospect as the average CPM across all impressions. So the basic formula is actually

The real formula:

Payout = sum(Price for impression1, Price for impression2, ….)

eCPM = (Payout / Impression volume)x1,000

Impressions can have drastically different prices

So what the formula above means is that eCPM is an averaged number. Now, you might remember from your statistics class that average can be misleading when variance is high. Don’t remember? Here is an article to brush up on this topic. Impression payout certainly falls into the high variance category. Let’s see how high the variance is.

eCPM Variance in CPI Networks

What is a CPI network? The following networks pay mostly based on rev-share of their CPI campaigns: Unity Ads, Vungle, Chartboost, Supersonic/Ironsource, Applovin, Adcolony, Tapjoy. In these networks, the CPI variance is especially high. This is a typical distribution of the actual prices:

Price Proportion of impressions that pay this price
$0 99%
$500-$1,000 0.2%
$1,000-$2,000 0.4%
$2,000-$3,000 0.2%
$3,000-$4,000 0.2%

If this seems a bit high it’s ok. We were also surprised but the simple reason is that eCPM is 1,000x than the price of the impression. $4,000 eCPM really means that there is an impresison that paid $4. This is simply the impression that led to the install. $4 is not a very high price for an install after all, there are much higher prices.

Variance in bid levels in RTB

If you are using an SDK from Mopub, Inneractive or Smaato, it means that each impression is getting a differnet price based on an auction. The bid levels here also vary drastically. In some cases you can see bids of over $100 when a user is being retargeted and in some cases the bid levels are at $0.05 since no one is bidding on that user except for a scavanger that bids the minimum on everything and catches the leftovers.

What about Facebook Audience Network and Admob

Facebook and Admob both operate an entire eco-system. Each of them have both CPI campaigns that are paying per installs or at least optimizing per installs along side retargeting campaigns and other forms of demand. The result here is also the same – big variance in eCPMs when you look at specific impressions and one single avarage eCPM reported for all the impressions.

Why should you care about variance in eCPM

If you are basing any business decision on ROI calculation that uses the avarage eCPM, you should care about eCPM variance. Trying different App Icons and App names, new features, traffic sources, monetization setups. These are all decisions where you try to measure the ROI. If your ROI calculations uses the average eCPM to estimate ad revenue as part of that calculaitons – it’s likely that you are making the wrong decision.

If you want to know the eCPM of every single impression and make better ROI calculations you should check out SOOMLA TRACEBACK – Ad LTV as a Service

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App Monetization

Ad_Mediation_Setup_101

The use of ad mediation in mobile apps has become the mainstream in the last few years. One ad-network can’t have demand to give you good fill-rates and high CPMs for all your user segments and all the geographic locations where you have users. In addition, mediation allows you to add more ad-networks and increase demand for your ad inventory. As you might remember from “Introduction to Economics” – with fixed supply and increasing demand the price goes up. If you want to evaluate different mediation platforms check this post comparing 6 different mediation platforms.

Use placements/zones/areas for placements

Most mediation platforms has a feature called placements or zones or areas. This is designed so that if you have different areas where ads are presented in your app, you can give them names when implementing the SDK and later on refer to them from the mediation platform. This has a few benefits:

  • You will be able to see reporting for each placement separately
  • The mediation auto-pilot will optimize for each placement individually giving the optimization more precision
  • When setting up a manual waterfalls you can set specific one for each placement

Use placements for segments, testing, impression frequency and ad types

Advanced publishers often use the placements feature for other purposes to enjoy the same benefits mentioned above. Here are a few ideas:

Segments – Let’s say that you could create a segment of users who respond well to videos it would have made sense to show them only video ads. Alternatively, if you had a segment of users that don’t perform well for CPI campaigns – it would make more sense to create a waterfall for these users that gives higher pirority for brand oriented ad-networks such as Mediabrix and Hyper MX.

Testing – optimizing and trying different things is a standard practice in mobile these days. The only way to test different setups is to differentiate group A from group B by duplicating all your placements and marking them A and B repsectively.

Impression frequency – serving different placement every time an ad is presented to the same unique users can give you visibility into your eCPM decay and allow you to optimize your impression frequency.

Ad types – this one goes without saying. Differentiate your videos from interestitials.

Some of the advanced segments mentioned above requires the use of SOOMLA TRACEBACK which also allows to test different ad setups and monitor eCPM decay without jumping through hoops

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Don’t put all your eggs in the auto-pilot basket

Most mediation platforms have 3 modes:

  • Automatically allowing the mediation platform to select the best provider
  • Manually configuring the waterfall
  • Mixed – manual for the top countries and automatic for smaller ones

The automatic approach means that the mediation platform will check each of the ad networks every day to see which one provided the best eCPM and then prioritize the waterfall based on that number. The problem with the auto-pilot approach is that it is based on yesterday’s data. Moreover, in many cases the lower performing network will get switched to the top of the waterfall due to randomness in small numbers. The companies that make the most amount of ad revenue in the world often takes things into their own hands. You should at least experiment with this approach.

Disable the network that gave you the mediation

Most mediation platforms are owned by ad-networks. This creates an immediate conflict of interest. The mediation should be an unbiased, neutral 3rd party while the ad-networks compete with each other for more inventory. What is a publisher to do? Try to find a setting in your mediation platform that eliminates the owning ad-network from the auction. This way you are still enjoying a free mediation but you can be sure that it’s neutral. Important note – make sure you have a catch-all ad network or an SSP if you use this trick. Otherwise you will end up with a low fill rate.

Multiple CPM floors to force ad-network bidding

This is the most advanced trick in this post and requires you to do some prep work on the ad-networks. Basically every ad-network can apply a CPM floor. Some of them allow you to control this from their dashboard while others have the control on their side so you have to call and ask for it. What you want to do with this setting is to create 2 or 3 CPM floor levels under different App IDs or placements and then enter them into the mediation in different positions in the waterfall. Let’s see this simplified example with 2 ad-networks.

Example of a waterfall multiple CPM floors:

  • 1st priority – network A floor $20
  • 2nd priority – network B floor $20
  • 3rd priority – network A floor $15
  • 4th priority – network B floor $15
  • 5th priority – network A floor $10
  • 6th priority – network B floor $10

This means that if either ad-network has an ad that will pay more than $20 they will get to serve it. If none has it, the waterfall goes down to 3rd and 4th priority and checks if there is an ad that will pay $15 or more and so forrth. This method forces ad-networks into an auction that increases the price you get for your inventory.

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App Monetization

10-Ways-to-Improve-Optin

We already covered the emergence of rewarded video ads in mobile games and the importance of focusing on opt-in ratio to increase the number of first impressions you get.

Opt-In Ratio – the number of unique users who watch rewarded videos in a given day, divided by the number of total unique users in the same day.

List of ideas for improving opt-in ratio for rewarded video

Here you can find a few game design suggestions to improve the number of people opting in to videos. However, we don’t recommend implementing all of them. The way to use this list is to set up a system like SOOMLA TRACEBACK that allows you to measure opt-in on a segment and cohort level and then try different methods for different segments while monitoring the improvement through the system.

1 – Guide users to watch a video as part of the tutorial

The rational here is simple. D0 is the only day where you have 100% retention. Guiding users to watch a video in the tutorial allows you to get a lot of 1st impressions and also teaches users that rewarded videos are an integral part of the experience.

2 – Daily offer that require users to watch a video

Once users come back, a nice way to promote the videos to them is to offer some special benefit, bonus screens or game advancement in the form of a daily promotion.

3 – Surprise box in exchange for a video

Many users like to get a surprise box in the game. Making the surprise box the reward of watching a ad is a great way to incentivize more users to engage with the ads.

4 – Lives for video views

Many games has energy mechanic built into them. It could be lives, energy, fuel or any other resource that is consumed with every attempt of the user. Users who want longer sessions usually have to pay but in many cases rewarded video can be offered as an alternative to payment for the non-payers segment.

5 – Save Me / Revive

Games often offer an option to keep playing from the last point by watching a video ad

In many action or arcade games ther user is able to play until some tragic event kills his character. This is the perfect opportunity to offer him an opportunity to keep playing from the same point in exchange for watching a video ad.

6 – Virtual currency for video completion

Another popular place to introduce the value exchange is inside the store of the game. The user can buy coing with money or he can get some for free if he watches some video ads.

7 – Double virtual currency collection for a limited time

Future play offers a 2x profit doubler for a period of 4 hours in exchange for a video viewMany games have coin collection mechanics into their games. In game design these are known as ‘pools’. The option to double the effectiveness of a pool is very appealing to a player and creates an incentive to watch an ad. Futureplay is one company that did a nice job with this option in their game Farm Away.

8 – Remove other ads in return for video view

Another option for introducing rewarded video is to offer the user an interruption free session in return for watching a single ad. You can see examples of this option here.

9 – Accelerate delivery/building time in return for video

Some games have built in waiting periods. This is specifically true for games in the strategy, simulation and racing genres. In these games the user have to wait for some action to be completed and is offered to pay to accelerate. Another option would be to give him an option to accelerate the action by watching a video ad.

10 – Users that don’t opt-in for videos – show them other ads

The final tip wouldn’t directly improve the opt-in rate to rewarded video but it is important just the same. About 2% if your game users pay for In-App Purchases, A typical opt-in ration might be 25%-40% and games that have optimized their opt-in ratio might get to 80%. This still leaves at least 20% of your users that are not contributing any monetization. To these users, you can show interstitials, banners and native ads to round up the monetization.

If you want to improve your opt-in rate to rewarded videos try these ideas and monitor which one works using SOOMLA Traceback.

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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.

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Analytics, App Monetization

there are many things even the experts don't know about life time value - here are 5 of them. this image is a header image for the blogpost

You might have heard some industry experts talk about LTV (life time value) and how important it is. Here are 5 things even some of the experts don’t know about LTV.

1 – Life time value (LTV) is not just for marketing campaigns

You might have heard that you need to know your life time value to do marketing. This is correct but there are actually more reasons. The first reason for for calculating LTV is related to the early design phase. Before you even start making the game you should analyze the potential LTV based on benchmarks from similar games. This important for fundraising as well as for choosing the right games to build. The second reason is even more important. LTV is the one KPI that wraps both ARPDAU and retention and it is highly correlated with long term success. By actively tracking LTV your team will be focused on the right thing when making decisions about the game and monetization techniques.

2 – There is no real life time value – only predicted life time value

Knowing the real LTV requires waiting a very long time – technically you will have to wait a lifetime. You can assume some maximal lifetime – in games 180 days and 365 days are common values for the maximal lifetime. These time frames are just too long to make any meaningful decisions about marketing, product or monetization. Lets say you made a new feature and want to know if you should keep it or not – waiting 180 days for a decision is just impractical. Whenever someone is talking about life time value he means the predicted life time value. That’s the only parameter you can actually work with. To predict yours, you can use one of these 6 LTV calculators

3 – You can succeed with low LTV but not with declining LTV

There are successful games with LTVs as high as $20 or as low as $0.3. You can succeed with low lifetime value and many games have – this is especially true if you are able to constantly increase it. However, you can’t succeed if your LTV is declining – it means that something is fundamentally broken with your game.

4 – Most companies have both CPI > LTV and CPI < LTV

LTV has to be greater than CPI! There are a ton of articles that explain that If your get the basic formula right you are golden. In fact, there was even a conference with that name (http://ltvgtcpi.com). In real life however, you can’t be golden in all segments so the trick is more around finding your golden segments and expanding on them. If your app uses ads, you will need to trace ad LTV per segment using a traceback platform.

5 – In successful games most of the life time value is created after day 30

If you build a life time value spreadsheet and play around with the numbers you will soon see that typically the first 30 days contribute between 25% to 50% of the total life time value. Plugging in the known ratios of 40%,20%,10% for d1, d7 and d30 retention shows that the yield in days 31 to 180 is twice as much as your first 30 days. This means that you should invest time in giving your most loyal users reasons to play for a really long time. King has mastered that art well and Candy Crush has 1,880 levels in the game. I’m sure they are working on some new ones as we speak.

Plugging in 40%, 20% and 10% as the values for d1, d7 and d30 retention shows us that only one third of the LTV is generated in the first 7 days.

 

If your game uses ads and you want to track the LTV per cohort, segment and testing groups, you need a traceback platform. Check out SOOMLA Traceback – Ad LTV as a Service.

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Analytics, App Monetization

measuring your ad revenue in mobile apps is a tricky business and many publishers makes mistakes doing so. Here are the 5 most common ones.

This post is about the mistakes that mobile app publishers are making when measuring their ad based monetization. Whether your company is using general purpose analytics, attribution, the mediation dashboard or in-house BI to track your revenue from advertising you are probably making at least one of these mistakes.

1 – Week by Week Testing instead of A/B testing

From what I have seen so far this one is a fail for 100% of the mobile app publishers I have talked with. Lets say you want to test a new feature that increases the number of allowed rewarded videos from 3 to 5. There is a right way and wrong way to do it. A/B split is pretty easy to implement on Google play due to their controlled roll-out feature and on iOS it’s not that hard either. However, when it comes to ad revenue companies use week by week testing. In other words they implement something and compare the ad-revenue of this week vs. last week. Here are a few reasons why this is wrong:

  • There could be campaign changes between week 1 and week 2 – campaigns go up and down on the ad-network side all the time if week 2 was better due to a big campaign you might think it’s because the changes you made. A/B tests eliminate that
  • Your user behavior and usage volume might be impacted by real world events like a holiday weekend or a big sporting event – with A/B tests the events impact both groups so it’s a fair test
  • With week by week testing you have to go “all-in” and you don’t even know if the revenue change came from the group who received the change
  • It’s almost impossible to reach statistical significance with week by week testing

The reason why companies don’t implement A/B testing for ad-revenue is that doing so without a specialized ad revenue tracking solution is very complex. However, optimizing with week by week testing is very limited.

2 – Assuming all users are worth the same

Most mobile app publishers assign very specific value to each user when it comes to IAP revenue but fail to do the same for ad revenue. The typical approach is to assume all users are worth the same amount of revenue. This is in-fact very far from reality. First of all, not all users even see ads when it-comes to rewarded videos and even if you look at the group that does see ads there are users that install a few apps and are worth more than $10 while others who only watch the videos end up not generating any revenue.

3 – Not measuring your eCPM decay

“The 1st impression of a user is worth the same amount of money as the 10th impression” – FALSE. The performance of the 1st impression is higher and so the CPM that advertisers are paying in RTB are higher and the eCPMs you are getting from the rewarded video network is also higher for the first impression from the very same reason. As the same users sees more and more impressions in the same day he becomes blind to the ads and the CPM decays. Assuming that all the impressions are worth the same amount of money is a common mistake by mobile app companies.

4 – Focusing on impressions rather than Opt-in ratio

Rewarded video became one of the biggest sources of advertising revenue for mobile app companies. However, it’s important to understand that this is an opt-in type of interaction. With some games, only 10% of the users choose to see the ads while in others it can be as high as 70%. Since the 1st impression pays a lot more than the subsequent impressions, focusing on increasing the number of impressions is a mistake. Companies should focus on increasing the Opt-in ratio instead

5 – Not tracking churn by campaign creative

The last mistake is related to the relationship between ads and churn. There are 2 type of ad interaction that can cause your users to churn:

  • Ads that have a negative experience – are deceptive or have low quality creative
  • Ads of competing apps might steer your users away from your app

Not tracking the impact of different ad creatives placed by the ad-networks in your app could be dangerous.

 

If you want to improve the way you are measuring your ad revenues and stop making these 5 mistakes – check out SOOMLA Traceback – Ad revenue tracking platform.

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App Monetization, Video

5 in app advertising tips based on the session that Christian Calderon, CRO of Ketchapp gave at Postback

In a recent talk at Postback event, Christian Calderon gave a very interesting presentation about Ketchapp’s approach to in app advertising. Christian recently joined the Ketchapp team after leading Dots monetization for about 2 years. There is a lot to be learned from him so if you have 15 minutes – I highly recommend viewing this video.

 

FREE REPORT – VIDEO ADS RETENTION IMPACT

 

Mobile ad spend per user is growing

Companies who are condiering in app advertising as a source of monetization should study this chart closely. If you felt like CPMs were high in the last 12 months. This chart says it will increase by almost 2x in the next 3 years.

the mobile ads market forecasts says that average ad spend per mobile users will increase almost 2x in the next 3 years

Mediation is a “must have” not a “nice to have”

In his talk, Calderon explains that mediation is the way to aggregate demand and create a competitive situation between the ad networks. This is important in oder to maximize your yield. To learn about the pros and cons of the top mediation platform refer to this comparison.

Advertisers pay more for the 1st impression and eCPM decays after

This is an important point to understand. Since eCPM levels are driven by performance and conversion rates, the first impression is usually paying a lot more than the 10th impression. Smart buyers like Machine Zone are focusing on the first impression and are willing to pay premium CPMs for that one. To analyze eCPM decay for your app you need a specialized tracking tool like SOOMLA TRACEBACK.

CPM decay means that the first impression a user sees in the day is the one that will yield the most revenue and the revenue for subsequent impressions drops

Adoption rate (aka Opt-in rate) is linear with revenue

Adoption rate or Opt-in rate is how many users out of your daily active users get to see ads. In other words, how many 1st impressions you have. Calderon hints that in both Dots and Ketchapp focusing on the opt-in rate is part of the secret sauce to high yield from your in app advertising.

Focusing on adoption rate or opt-in rate means that you are getting more 1st impressions and optimizing your in app advertising
Improving the adoption rate requires 2 things:
  • Good ways to measure it in different segments so you can identify opportunities and track progress
  • Iterating and testing new ideas that are focused on increasing the adoption rate

Understanding the business side of of in app advertising is critical

The last tip that we can learn is that ad-based monetization requires more than just plugging the ads SDK and waiting for the revenue to come. There is much to be achieved by developing a relationship with the ad providers, tweaking the deals you are getting and negotiating with them. In his slides, he explains that there are 3 pieces that makes a good ad-partner and one of them is their ability to work with you and get you the deals you need.
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SOOMLA - An In-app Purchase Store and Virtual Goods Economy Solution for Mobile Game Developers of Free to Play Games