Analytics, App Monetization, Game Design, Tips and Advice

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

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

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

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

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

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

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

2 – Analyze opt-in for cohorts

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

FREE REPORT – VIDEO ADS RETENTION IMPACT

3 – Differentiate users from different traffic sources

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

4 – Treat your ad whales to nice Incentives

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

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

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

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

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Game Design, Tips and Advice

Tutorials in Match 3 Games – Time to Kill Them?

Is it time to end Match 3 Game tutorials?

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

Match 3 – a popular genre

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

image-5

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

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

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

image-6

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

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

The tutorial is redundant for experienced users

image-4

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

FREE REPORT – VIDEO ADS RETENTION IMPACT

Detecting experienced users automatically

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

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

7 App Monetization Predictions for 2018

7 App Monetization Predictions for 2018

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

1 – Let the ad whale hunting begin

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

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

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

3 – More publishers that are also advertisers

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

Q1 2018 MONETIZATION BENCHMARKS

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

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

5 – Better control over ad experience and creative

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

6 – More apps will advertise competitors in 2018

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

7 – Ads will surpass IAP for mobile game monetization

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

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

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App Monetization, Tips and Advice, Video

Top 7 Incentives for Video Ads in Mobile Games

Top 7 incentives using video ads in your app!

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

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

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

1. Lives or “save me” option

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

2. Time related incentives

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

3. In game currency

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

FREE REPORT – VIDEO ADS RETENTION IMPACT

4. Earnings doubler

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

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

5. Re-dealing of a randomly assigned element

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

6. Renting items

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

7. The daily spin

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

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Analytics, Announcement, Industry News, Tips and Advice

GDPR 101 for Mobile Apps or How to Avoid a €20M Fine

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

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

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

The price tag difference

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

US companies also on the hook

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

Everything is personal

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

Encrypting and protecting and documenting data transactions

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

CASE STUDY ON ADVERTISERS CHURN & eCPM

Is your data coming to US for business or pleasure

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

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

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

Keeping data in EU

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

Privacy Shield

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

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

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

EU Model Clause

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

The right to be forgotten

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

What you should ask from your providers

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

Here is quick compliance checklist for your providers.

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

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

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

Providers Certified with Privacy Shield

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

 

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App Monetization, Research

SOOMLA Webinar # 1 – Lotum Case Study

SOOMLA Webinar # 1 Lotum Case Study on ads and churn

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

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


Start Webinar Transcript

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

End Webinar Transcript

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App Monetization, Research

The Q4 – 2017 Ads and Churn Case Study Is Out

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

We are excited to announce our new “Ads and Churn Case Study with Lotum” report today. This is one of the many industry data reports that we will continue to publish providing important insights related to monetization through ad revenue. Our new reports focuses on the effects of advertising director competitors and their effects on eCPM, churn and seeks to identify which advertisers may be stealing your traffic.

You are welcome to download the report through this link or via the banner to the right.

Would also be great if you can help us spread the word by sharing my post on Linkedin.

Linkedin post about mobile monetization report - q2 2017

 

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Analytics, App Monetization, Tips and Advice

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

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

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

Networks put their best campaign first

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

Average eCPM is a self fullfilling prophesy

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

FREE REPORT – VIDEO ADS RETENTION IMPACT

Changes in 1st impression eCPMs are clear triggers for action

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

Tracking 1st impression eCPM – Easier than ever

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

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Analytics, App Monetization, Tips and Advice

In-App Events That Give You Insights for Your Game’s Performance

Easy In-App Events That Can Give You Insight on Your App's Performance

No matter what you are looking to achieve, in-app events are a great way to go about getting performance indicators on some of the central issues faced by your app’s growth. While it might sound great to track every swipe, click, open or close event within your app, it can become a bit overwhelming to make use of all the data.

There is already an established list of benchmarks that should be closely monitored to give you some insights about your app’s performance, however the focus here is to dive into specific in-app events and how they should be approached.

Here is the short list (we could have made it much larger):

Registrations and the dreaded drop-off

Registration drop-offs are the bane of every app. We work so hard to get the quality traffic and the installation, but when it comes to registering – poof they are gone. The golden rule is reduce the amount of steps required for the user to complete the registration. With each additional step, the drop off chance is higher.

Solution – Keep a close eye on your registration drop offs. Identify key steps that are causing it and work to reduce. A/B testing is key here.

Tutorials

Some apps have them, some don’t, but it all depends on how much of an onboarding experience you want to provide the new user. Whether or not they are effective or not, I’ll let you be the judge, however if you do have them, a user’s completion of the tutorial can give you some insight as to how engaged your users are.

Solution – Overall on-boarding completion is a good metric to keep an eye on, however if the number is significantly low, it would be worthwhile to set up multiple in-app events for various stages to check out where the drop-offs are occurring.

User Progression

How quickly your user’s progress through your beginning game content is a great identifier on how your app is performing, but also can give you great insights on which users to segment and target specifically. Conversely, those users who move through the content slow should also be identified.

Solution – Logging several events throughout (beginning, middle, end), should be examined to monitor drop-offs and provide some insights on how engaged your users are.

Video Ads Completion

There are a multitude of parameters to look at and analyze when considering how effective your video ads are. Several studies have been put out, but the macro trends show that there has been a big shift towards video ads and its respective portion of ad revenue.

Where you place your ads within your app and how frequently can influence your revenue, uninstall rate, player experience and many other key KPIs.

Solution – Monitor and A/B test the placement and frequency of your video ads. They can have a big effect, but also have the potential to damage your app’s overall performance. Also be sure to check out our post on optimizing your opt-in rate for video ads which can help boost your ad revenue significantly.

FREE REPORT – VIDEO ADS RETENTION IMPACT

In-App Purchases

If your app has in-app purchases, an obvious tell-tale how your app is performing is how many of your users are making purchases. It is a great indicator of how engaging your app is, be it either via content or level of addiciton. A user’s purchasing behaviour can then be leveraged for future purchases. Knowing what your users have purchased and how much they have spent in the past are key for segmenting promotions and sales for specific users.

Solution – If the frequency of in-app purchases are very low, try to lower the costs / increase the offer to entice users. The ultimate goal is finding that sweet spot between making the in-app purchases valuable but not too much so that they make it too easy for the user.

Conclusion

Very likely each app has it’s own category specific in-app event that is closely monitored, however we tried to focus on the basics that touch on many different types of apps. We hope that this list helps you gain some insights on how your app is performing.

If you can think of any other critical in-app events that should be added to this list, let us know!

 
 

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Analytics, App Monetization, Guest Post, Tips and Advice

Comparing the Best Ways to Increase Ad LTV

Call App's Jonathan Raveh - Best Ways to Increase Ad LTV

Jonathan Raveh is a mobile monetization expert and the Director of Monetization at CallApp, a world leader in Caller ID & Call Recorder services.

One of the interesting abnormalities in the world of app monetization is the relatively low number of people assigned to it. UA acquisition departments usually take up much more personnel, while the main focal point for generating revenues in an app development company, is usually understaffed or assigned to the product team.

While this may not be the best policy, this is definitely the reality. Monetization is a shared responsibility across many departments in the company, including UA, Product & Marketing. This leaves any dedicated monetization employees in a serious dilemma – with low resources, where should they invest their time and effort the most? With ad monetization getting bigger even for IAP focused apps, this is a true challenge.

CallApp, a caller ID & call recorder app is one of those apps. With over 35M installs worldwide, our app is totally free to use, and while there are some IAP offers in place, most revenue is ad-related. Joining a very small team and being solely responsible for the app monetization efforts, I faced this challenge from the very first day – FOCUS. Granted, there is no limit to what you can focus on when you’re in charge of monetization. However, there is a definite time limit to (1) hours in the day and (2) Being able to concentrate without making too many mistakes analyzing data. The other major constraints are limited development resources and UX.

These limitations ultimately shaped up our 4 major, strategic responsibilities for mobile ad monetization that rise over and influence the day-to-day actions and task. We’ve put them to that to the test, and came up with some findings that helped figure out exactly what task our time will be best spent on.

Ad Frequency & Location

Right off, this is that one is the very basic element. Forget ad partners, forget business – determining ad frequency has a huge effect on the entire app eco-system. In the short run, ad location, and more importantly ad frequency influence development, usage, data, UX, user satisfaction. In the long run – ratings, reviews, PR, ASO and much more. We found that these types of changes may amount to 50% change in revenue. In term of development time, this is not an easy task, but as these changes aren’t usually done on a daily or weekly basis, it’s definitely barrable.

Focus on GEO’s

Ad monetization wise, app developers tend to give attention to 1 of the following:

  • High eCPM yielding counties
  • High impression yielding countries
  • Countries that possess 1+2

In more cased than not, attention means full attention, and that means that countries that do not generate high impression volume or high eCPM are simply neglected. In most cases, neglected GEO amount to more than 25% of traffic. In order to optimize those loose ends, there is usually a need to work with more localized ad networks, expand and complicate your ad waterfall and sometimes work with additional ad formats. Not only does this burden your development team, it also creates tons of work for the person in charge of monetization. So, a tough decision. However, this clear subjective decision that varies from one app to another, usually influences over 20% of revenues, in average.

Adding More Ad Networks

The actual deciding factor on how many ad networks an app needs, depends heavily on the level of monetization you want to achieve. The actual number of monetization networks an app needs relies on 4 parameters, known as the FORM model which we developed in CallApp: Formats, OS, Regions, Maximization. The entire model has been widely explained (here), yet it embodies another critical decision in the maximization element: how much work are you will to make to get those extra 10 percent of revenue. These 10 remaining percent of revenue require some work from the IT side (adding more ad networks), and a lot of Monetization hard-labor analytics.

FREE AD NETWORK COMPARISON SPREADSHEET

Setting Floor Price

If you monetize your app using Facebook and Google (and a few others), this is a must. There are automated mechanisms in place, by both ad giants, to make sure you generate a minimal amount of revenue, but true optimization cannot be reached without designated price floors.

When it comes to price floors, there’s a major difference between Google & Facebook: While Google’s price floor (via Admob’s & AdX) tend to merely set a floor from which your eCPM cannot go under, FAN’s floor prices are actually ‘target eCPM’, a level that sets the goal for its performance to reach, regardless of any other elements – CTR, impression and mainly fill rate. However different, both price floor mechanisms are a pretty powerful tool. They require no effort from the development team, yet a lot of attention from the monetization team. Price floors are affected by anything from ad frequency, GEO’s and seasonality, so they need to be monitored on a daily basis. A hell of a lot of work, with a 30% revenue bounce potential.

After experiencing the effects of these 4 pillars of strategic monetization decisions on all sides – revenue, product, development time, monetization time, etc – we were able to visualize these strategies, to better understand the role of the monetization team.

Effects Compared To Development Team Work:

Development Resources for AD LTV

Effect Compared to Monetization Team Work:

Day-To-Day Resources

The last 7 months at CallApp taught me, first and foremost, that in ad monetization, focus & prioritization are strategic decisions. Time equals money, but it’s a lot more than your money – it’s the money you could have been generating doing something else to improve results. Not all apps will follow the same path in this time/effect/results equation, many simply just into the pool of the day-to-day duties without taking a single moment to breath and think about what they want to gain. The CallApp experience has definitely taught me that everyone should give it some serious thought. That will ultimately lead to better result in the long run.

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