Marketing, Resource, Tips and Advice

The Best Mobile Gaming Conference To Attend And Why – Our Top Picks

We looked at what are the best mobile gaming conferences to attend and why.  Check out the breakdown of our top picks.

Every quarter, there are about a dozen, if not more, conferences that fall under the umbrella of mobile gaming / marketing / growth / data / analytics. Each conference tends to have a focal point, anywhere from growth, blockchain, indie gaming, monetization, retention and the list goes. Hopefully we will answer help answer “Which gaming conference should I attend / is the best?” by breaking down some of the top mobile gaming conferences out there.

The first question you should be asking yourself is, “What are my goals for the conference?”. A conference can be a great place to brainstorm ideas from peers, network, grow your client base, learn from speakers and lectures, play the upcoming games for 8 hours straight (I’m guilty of that) and of course connect with other people in your industry.

There is a pretty straightforward 10 point criteria system that should be looked at when choosing a conference:

  1. Goals
  2. Cost
  3. Location
  4. Who’s Going?
  5. Who’s Speaking?
  6. Topics / Tracks Offered
  7. Number of Relevant Topics / Sessions
  8. Conference Format
  9. Timeline
  10. Networking Opportunities

While I am sure none of those 10 criteria above are anything new to anybody who has contemplated whether or not to attend a conference, I do want to bring something new to the table here and give some insight how SOOMLA chooses which to attend.

First, let’s look at some of the conferences / events in the mobile gaming industry:

Delta DNA’s Game Industry Analytics ForumGame Industry Analytics Forum

Delta DNA’s Games Industry Analytics Forum is a series of events targeted at all industry professionals who seeks to make their games better through analytics. They bring a large mix of industry experts who speak on a variety of topics.

Name Games Industry Analytics Forum
Locations San Francisco and London
Avg. Companies NA
Avg. Attendees NA
Cost Free
Focus Analytics

Pocket Gamer Connects ConferencePocket Gamer Connects

Pocket Gamer’s Global Mobile Game Conference is held three times a year in various locations. The main focus tends to be on global game publishing strategies, opportunities in various markets. They have several (12 or so) content tracks each with a focus such as Monetization, Marketing, eSports, Growth and more.

Name Pocket Gamer Connects
Locations 3 per year: London, Helsinki, San Francisco
Avg. Companies 600+
Avg. Attendees 1200+
Cost Varies from several hundred $ to thousand +
Focus Mobile Gaming Industry

Casual Connect ConferenceCasual Connect

Casual Connects hosts several conferences across the globe, each with its own particular focus. Anywhere from developers, game design, east meets west, and game tech innovation.

Name Casual Connect
Locations 4 per year: USA, Europe, Asia, Eastern Europe
Avg. Companies 600+
Avg. Attendees 800-2000+
Cost Varies from several hundred $ to thousand+
Focus Mobile Gaming Industry

White Nights ConferenceWhite Nights

White Nights is considered to be a business conference for the gaming industry. They are focused on all aspects of the gaming industry, including mobile, PC, console, web, AR and VR.

Name White Nights
Locations 4 per year: Prague, St. Petersburg, Moscow and Berlin
Avg. Companies 800+
Avg. Attendees 1600+
Cost Several hundred $
Focus Business of Games

Mobile Growth SummitMobile Growth Summit

Mobile Growth Summit is a non-vendor conference targeted at those who work in the mobile growth industry. The conference aims to bring mobile growth and marketing professionals together to connect and learn from one another in areas such as UA, monetization, retention and eCommerce.

Name Mobile Growth Summit
Locations 4 per year: Prague, St. Petersburg, Moscow and Berlin
Avg. Companies 300+
Avg. Attendees 600+
Cost Varies from several hundred $ to thousand +
Focus Mobile Growth / Marketing

Mobile Games ForumMobile Games Forum

Mobile Games Forum brings together gaming industry decision makers to discuss the direction of the industry and potential strategies. The larger portion of attendees tends to be C level, senior managers and directors.

Name Mobile Games Forum
Locations 2 per year: London and Seattle
Avg. Companies 300+
Avg. Attendees 600+
Cost Several hundred $
Focus Upper Management / Decision Makers

Game Developers ConferenceGame Developers Conference

Game Developers Conference is a 5 day event that attracts thousands of attendees from all over the world. They have a wide variety of tracks / sessions on just about every topic from blockchain to VR to monetization. Many up and coming publishers use the conference as a great opportunity to show off their upcoming games.

Name Game Developer Conference
Locations San Francisco
Avg. Companies 700+
Avg. Attendees 3000+
Cost Depends on type of ticket: from free to several hundred.
Focus All things gaming

Game ConnectionGame Connection

Game Connection is a business convention for the game industry where publishers, developers, service providers and distributors come to find new partners and/or new clients. Considered to be the go-to conference for business.

Name Game Connection
Locations Paris and San Francisco
Avg. Companies 1500+
Avg. Attendees 2700+
Cost Several hundred $
Focus Business Creation for Game Industry

As you can see, each conference does have it own focus, and depending on what you are looking to achieve, one of the above conferences should meet your goals.

Criteria # 11 – The Meeting System

One of the topics that we did not cover however is the meeting systems that is made available to the attendees. Depending on the purpose of attending the conference, this could be irrelevant to you, but if you do plan to attend for networking purposes, a good meeting system can dramatically improve the success of your trip. Here are a few of the meeting systems we’ve encountered at SOOMLA:

Feature Pitch&Match MeetToMatch Let's Meet Bizzabo
Profile Creation Y Y Y Y
Search Filters Y Y Y Y
Internal Messaging Y Y
Mobile App Y
Block Meeting Time Slots Y Y Y
Agenda Export Y Y Y Y
“Smart” Scheduling System* Y

Smart System* refers to the meeting system’s method of organizing meetings. Let’s Meet is the only system that allows you to request a meeting without a set time before the event. Generally about a week before the event, all the meetings that have been accepted are automatically filled into your calendar based on a mutual time slot being available. This is significantly different and advantageous compared to the other meeting systems that require you to set a time, limiting your ability to be flexible.

Conclusion

While each conference has its own focus, you are bound to find a mobile gaming conference that meets your criteria. If you think there are any more that are worth mentioning, let us know in the comments below!

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Marketing, Resource, Tech Resources, Tips and Advice

Complete Mobile Advertising Glossary – Over 70 Terms Defined

SOOMLA's complete mobile advertising glossary - we've broken down the top 70 terms in ad tech to be easily understood.

From newcomers to mobile industry veterans, the amount of acronyms and terms that exist can be daunting, and frankly, often times confusing. The industry is constantly evolving, and with that, comes a steady flow of new terminology. We’ve compiled a list of 70 terms that are most prevalent in adtech and broken them down into easy to understand terms.

Here is the complete glossary to mobile advertising at your fingertips. Read, take notes and prosper.

1st Impression

Refers to the first ad displayed to a user within a session. Considered to be the most valuable in terms of eCPM.

1st Look

Ad-networks are prioritized in a a waterfall where the 1st ad-network gets to “look” at the ad request and decide if they want to provide an ad or not. If the ad-network passes the turn goes down the waterfall to the 2nd ad-network. When an ad-network asks for “1st look” it means they want to sit on the top of the waterfall and have the opportunity to see all the ad requests.

1st Price Auction

Where a bidder pays exactly what they bid. Often times leading to inflated prices and a lower demand for that publisher’s inventory.

2nd Price Auction

Where the top bidder pays the what the second highest bid was + $0.01. Allows for the saving of money due to overestimation of the value of a publisher’s inventory.

A/B Testing

A test in which all variables are identical aside from one. The purpose is to compare the two versions and see which performs better according to the established KPI.

Ad Exchange

An ad exchange refers to a platform that helps facilitate the buying and selling of advertiser inventory from multiple ad networks.

Ad Inventory

The amount of (virtual) space a publisher has available to be sold to advertisers. Also known as “ad space”.

Ad Mediation

A platform that sends requests for advertisements to multiple ad networks for publishers, ensuring the ad space is filled with the best possible deal.

Ad Network

An ad network connects advertisers and publishers looking to generate revenue by serving ads in a mobile app or website.

Ad Revenue

The amount of revenue generated from placing advertisements in an application / website.

Ad Whales

Refers to a group of users who make the most amount of ad revenue. Typically this is defined as the top 10% or 20% of the users who make 70% or 80% of the ad revenue. In other cases, the ad-whales are defined as a threshold of $0.7 (the equivalent of a $1 IAP).

Advertiser Blacklisting

The process of publishers blacklisting specific advertisers from appearing in their app. Some ad networks provide this as an option to publishers. The blacklisting is often based on competition, poor eCPMs or inappropriate content.

CASE STUDY ON OPT-IN RATES & SOOMLA INSIGHTS

Advertiser Identity

Identifying which advertisers are advertising in one’s app and their respective performance.

API

Application Program Interface. An API opens access to a limited part of a piece of software, allowing 3rd party developers to access previously unaccessible information.

ARPU

(Average Revenue Per User). Calculated by dividing the total revenue by the number of users across a time perdiod (generally monthly or annually).

ASO

(App Store Optimization). The process of improving the visibility of an app in the respective app store (Google Play, iTunes, etc.)

Attribution

The process of accrediting a traffic source with the conversion. Each platform has it’s own methodologies for doing so.

Audience

A group of consumers / users within a specific target market which are targetted for a specific ad campaign.

Blacklist

A list of advertisers that a publisher has decided to not allow to appear within their app.

Churn Rate

The rate at which users have stopped using an app during a specific time period

CLV

(Customer Lifetime Value). Has the same meaning to LTV – the total value of a user if given enough time to fully exhaust all opportunities to pay or watch ads in the game. This value is often averaged across a group of users (cohort) and most publishers try to create models for future prediction of CLV/LTV based on the activity of the first few days so they can make quick decisions on the marketing side.

Cohort

A group of users that share one or more similar characteristics. Used for grouping in data analysis.

CPA

(Cost Per Acquisition). The cost a publisher incurs to bring a new user through various paid channels.

CPC

(Cost Per Click). A campaign where the advertiser is charged everytime a user clicks on the ad they are shown.

CPI

(Cost Per Install). A campaign where a price is paid when a user views an ad, goes to the app store and installs an app.

CPM

(Cost per Mile). A campaign were advertisers pay for every thousand times the advertisement is shown.

CTR

(Click-Through-Rate). The ratio of users who click on an ad / opt-in to the total users who were displayed an ad.

DAU

(Daily Active Users). How many users open your app on a daily basis. This is one of the key metrics used to measure ad revenue.

Direct Deal

Rather than going through an ad network or mediation platform, publishers can make direct deals with advertisers, cutting out the middle men.

DSP

(Demand Side Platform). A platform in which marketers can buy ad inventory from multiple ad exchanges in one place.

eCPM

(Effective Cost Per Thousand). A metric used to measure ad revenue generated. Generally calculated by dividing total revenue earned by total number of impressions in the thousands.

eCPM Decay

The inevitable decrease in eCPM as ads begin to be displayed to your users. There are however methods proven to help slow it down.

Fill Rate

The number of ads requested that are successfully filled in relation to the total number of ads requested. Tends to be displayed in a percentage format.

Frequency / Frequency Capping

The rate at which users are shown ads. For example, some apps place a frequency cap of 4 ads per day for users.

GDPR

(General Data Protection Regulation). A comprehensive new set of regulations designed to give EU citizens more control / oversight on their personal data and the entities that collect it. Under GDPR, companies will need to notify their customers when collecting personal data. Consent can be given or denied based on the purpose of the data usage.

Header Bidding

The process by which publishers open ad space to be bid upon by multiple ad exchanges, resulting in an increased yield and revenue.

IAP Cannibalization

The notion that the integration of incentivized rewarded videos are damaging to the revenue gained from in-app purchases.

IDFA

The “Identifier for Advertisers” is a random identifier number given by Apple to a user’s device. It is used for advertising targeting.

Impression

Refers to the moment when an ad is fetched from its source and dispalyed to the user. Each ad type has a varying distinction of when the impression occurs. For banner ads, once an ad is fetched from its source and the user sees the ad. For video ads, the impressions is logged once the first frame of the video is displayed.

Interstitials Ads

Ads that are full-screen which are typically displayed at natural transition points in the flow of an app. For example, between levels or when the game is paused.

Q1 2018 MONETIZATION BENCHMARKS

Lookalikes

A method of targeting additional users based on similarities to existing users. Generally based on geo, interests, gender, age etc.

LTV

(Lifetime Value). Has the same meaning to CLV – the total value of a user if given enough time to fully exhaust all opportunities to pay or watch ads in the game. This value is often averaged across a group of users (cohort) and most publishers try to create models for future prediction of CLV/LTV based on the activity of the first few days so they can make quick decisions on the marketing side.

MAU

(Monthly Active Users) How many users open your app on a monthly basis. This is another of the key metrics used to measure ad revenue.

Mobile Ad Fraud

The process which fraudsters cheat advertisers into displaying ads to fake users / bot traffic.

Multi-Touch Attribution

Allows for the attiributing of all channels in the conversion process. Different from the existing last touch approach.

Offer Wall

A list of incentives which a user can receive by performing a specific action, typically downloading another app, watching a video ad, or sharing content on social media. The rewards for doing so tend to be some form of digital currency or other in-app incentives.

Opt In

When a user actively agrees to participate in viewing an ad.

Pipelining

The process of moving data from one point to another.

Playable Ads

Ads that request the user to interact, often showing off the basic gameplay of the game being advertised.

Postbacks

The ability to notify a third party of a specific event that occurs within an app (install, in-app event, etc.)

Programmatic

An automated process for purchasing digitial advertising, eliminating the need for a human touch.

Reach

The number of unique users who can potentially be targeted by advertising.

Real-Time Bidding

Bidding on inventory in real-time. The bid is often dynamically generated based on past performance of creatives, inventory, user groups, and other parameters.

Retargeting

A marketing effort in which targeted online advertisements are shown to users based on their previous behaviour.

Rewarded Video Ads

Video ads that are offer the user the option to opt-in to view them in order to receive some incentive. Can range from free coins, extra lives to free uprades.

ROI

(Return on investment). A performance measure used to determine the efficiency of an investment / effort.

SDK

(Software Development Kit). A set of software development tools that can be added to existing apps to support new capabilities.

SDK Mediation

Mediation of ad-networks allows publishers to use a few ad-networks in parallel and maximize fill rates and eCPM. SDK mediation is a form of mediation where each ad-networks installs an SDK on the publisher’s app and the mediation is done on the client side.

Server Side Mediation

Server side mediaiton is a form of mediation. Unlike SDK mediation, the goal of maximizing fill rates and eCPMs for the publisher is acheived with a single SDK provided by the mediaiton company and the ad-networks have to serve their ads through that SDK. This means that the mediaion is done on the server side

Share of Voice

Refers to the portion that one company controls out of the total. In terms of ads, can refer to an ad network who maintains a larger share of voice in rewarded video displays in comparison to other ad networks.

SSP

(Supply Side Platform) A platform that allows publishers to sell their advertising inventory in an automated way.

Target Audience

A group of consumers / users within a specific target market which are targetted for a specific ad campaign.

Traceback

SOOMLA’s unique ability to traceback individual user’s ad behavior.

Tracker

A tracker is a link structure generated by the attribution platform on behalf of the advertiser. The tracker is than passed along to the ad-network so clicks on the ads of the advertiser which are associated with the ad-networks can be identified through the unique link structure of the tracker.

Unified auction

On open auction where all ad networks are given an equal opportunity to bit on an app’s inventory, without any preferential treatment, in which the highest bid tends to win.

UDID

(Unique User ID). A unique identifier assigned to each device. Apple and Google have their own methods for doing so.

User Acquisition

The marketing efforts to acquire new users through advertising campaigns.

VAST Tag

(Video Ad Serving Template). A universal XML-based protocol specification created by the IAB for serving video ads.

Whitelisting

The opposite of blacklisting in which certain entities are explicitly approved.

Yield Management

The use of tools and business practices to maximize revenue.


Find a term that we didn’t define here? Let us know in the comments below and we’ll get them added ASAP.

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Analytics, App Monetization, Tips and Advice

Monthly vs. Daily Opt-in for Rewarded Video

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

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

What is daily and monthly opt-in for rewarded video

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

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

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

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

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

Why should you care about this

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

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

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

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

Create a habbit with the right incentives, segmentation and popups

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

Method 1 – Incentives and daily bonuses needs to work together

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

Method 2 – Simple pop-up for a segmented group

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

Method 3 – Selling Insurance

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

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

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Announcement, Industry News, Tips and Advice

Hyper Casual Games – Thoughts about Voodoo and Gram Deals

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

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

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

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

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

  • Tabtale
  • Mobilityware
  • Etermax
  • Gazeus
  • Kwalee
  • Ilyon
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Analytics, App Monetization, Tips and Advice

Data Based Formula – Which Advertisers to Block

Finally a Data Based Formula for deciding which advertisers to block

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

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

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

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

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

The analysis – revenue lost vs. revenue made

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

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

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

FREE E-BOOK – TOP 10 MOBILE GAMING REPORTS

Comparing 2 advertisers with positive net revenue by using nCPM

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

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

Improving the formula

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

Better way to prioritize advertisers

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

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App Monetization, Tips and Advice

Gazeus – Measuring Ads Allowed Us to Save 66% of Our Budget

How Gazeus saved 66% of their budget by measuring ads

At SOOMLA we are always advocating being more data driven when it comes to mobile app monetization. This way we are happy whenever we see a publisher stepping up their data game and starting to measure their monetization. In an earlier post we showed how Kongregate doubled their traffic by measuring ads and in this post we will see how Gazeus saved 66% of their budget.

About Gazeus

If you don’t know Gazeus I highly recommend watching the video below. The presentation is given by Paula Neves, CMO @ Gazeus.

 

 

Here are a few key points to know about Gazeus:

  • Owner of the Jogatina brand that is known from web/PC games
  • 40+ Titles
  • 9M MAU in mobile
  • 99% of mobile revenue coming from Ads
  • Strongest Geos – US, Canada

Measuring Ads – Critical and Challenging Problem

Since 99% of the revenue is coming from Ads, says Paula: “LTVs are lower and UA has to be spot on”. She then explains that they had ROI calculations only at the app level as a whole but not per campaign. On the product side, they didn’t have sufficient feedback loop for product to know if the features they are making are good. For these reasons, ad measurement is critical for Gazeus. In the video, Paula explains that her background is in the eCommerce domain where she took LTV for granted but when she came to Gazeus, she discovered that an entire infrastructure has to be created just to receive an answer for this question. This root cause of that is, of course, lack of user level data from the ad-networks.

CASE STUDY ON ADVERTISERS CHURN & eCPM

The outcome – 66% of marketing budget saved without sacrificing growth

Skipping to the bottom line quickly. Paula explained that the ability to measure ads allowed them to be much more focused in their UA efforts. In one example she gave, having the granular ad revenue per user data allowed them to chart the LTV curve for each cohort. By comparing the curves of iPad vs. iPhone users coming from different campaigns they were able to save a big portion of their ineffective marketing spending. The bottom line is that they were able to spend as little as 1/3 of what they were spending and still get the same revenue growth.

Gazeus ad measurement infrastructure and SOOMLA

In the middle part of the video, Paula explains how they built their ad measurement infrastructure. They had to collect API level data from each one of the ad-networks. For each one, different types of fields and dimensions are provided so normalizing that and the timezones is another challenge altogether. From the client side, they had to set up an event to be fired every time an ad is served. The server than allocates the average eCPM of the previous day for the relevant country and ad-format for each impression and multiplies by the number of impressions to generate user level revenue data.

Of course, a publisher doesn’t have to go through all this in order to get user level ad revenue. They can simply work with SOOMLA to get the data through API, directly into Amazon or via SOOMLA Dashboard. For Gazeus, they decided to go with their own solution since they use a few unique networks in Brazil that SOOMLA doesn’t support as Paula explains but for most publishers it’s not an issue. Here is a table to help you evaluate both options.

Build In-house Using SOOMLA
Initial Effort Up to 6 man months 1 week
Calculation Method Average eCPM Method* True eCPM Method**
Ad Network Support Tailored The 25 Most Popular Networks
Maintenance Internal resources Outsource to SOOMLA
Extra features N/A Advertiser identification, ad whale lookalikes, postbacks
Cost (for 5M MAU) Increase in hosting bill can reach $2,000 $2,500 to $3,500

*Average eCPM Method

  • In this method, the ad LTV system queries the API of each ad-network to retrieve the average eCPM of the previous day for each country and ad-format.
  • At the same time, the client side of the app reports to the ad LTV system each time an impression is shown to a user.
  • The ad LTV system calculates the revenue for the user by multiplying the number of impressions the user made in each ad-format by the average eCPM of that ad-format/country in that day and than dividing by 1,000. Than it sums the results for each ad-format for that user.
  • The process is repeated each day and data is aggregated on a user level basis and on a cohort basis.

Putting it in a formula – this would be the calculation of the revenue for user x (Imps is short for impressions here):

**True eCPM Method

  • In this method, the ad LTV system queries the API of each ad-network to retrieve the average eCPM of the previous day for each country and ad-format in addition to other dimensions that are available.
  • At the same time, the client side of the app reports to the ad LTV system multiple events for each impression: impression event, clicks, installs, ad interactions, advertiser identity, business model, bid levels.
  • The ad LTV system leverages advanced algorithms to deduct the true eCPM of each impression based on the data collected from the client side as well as the averages reported through the APIs. It then calculates the revenue for each user by summing up the contributions of each impression he viewed.
  • The process is repeated each day and data is aggregated on a user level basis and on a cohort basis.

The formula below shows the revenue calculation for user x where ‘n’ is the number of impressions he made in that day.

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Analytics, App Monetization, Tips and Advice

10 Mistakes that Will Keep Your Ad Revenue Low

10 Mistakes that will keep your ad revenue low

Most of the companies I talk with are interested in increasing their ad revenues. For many, increasing ad revenue is critical as they need to be profitable on their UA activities. Despite that, I see many mistakes companies are making that prevent them from improving on this front. Here are the top 10.

No new SDK policy

Some companies seem to have decisions made from the engineering to the business and not the other way around. It’s true that there are many SDK companies knocking on the door at any given time and many of them promise more than they deliver. However, not adding any new SDKs is like saying – our strategy is to not change anything. In a dynamic space such as the mobile app market – this is a big mistake.

How to fix it:

Establish a process for vetting new vendors based on business potential, risk and costs and make sure you include alternative cost as part of that equation. This will help you re-gain the confidance of the engineering team that you are not just making random requests.

No ads for payers

In 2018 mobile app publishers will make more revenue from advertising than from IAP and publishers needs to start thinking about ads as a main source and not a secondary one. In 2016, SOOMLA revealed the existence of ad-whales. These users can contribute $30 or $50 or $100 in your app – more than some of your payers contribute.

How to fix it:

It’s time to design monetization patterns where ads and IAP complement each other. Think about a user that just purchase a bag of coins maybe he can get 25% extra coins for watching a video right after the purchase. There are many other options to experiment with just make sure you measure the impact accurately.

Not measuring your ad monetization

You can’t manage what you can’t measure” said Peter Drucker in a famous quote. In other words, the path to improvement goes through measurement and the domain of app monetization is not different. Ad revenue has been lacking proper measurement tools but the situation is quickly changing and monetization measurement is becoming a neccessity for any company who takes their ad revenue seriously.

How to fix it:

Implement a monetization measurement system that allows you to get granular data about how your users interact with ads in your app. As Jeff Gurian from Kongregate said: “Ads count so count your ads

Banning competitor ads

The debate whether or not to show competitor ads in your app has been going on for years. Some companies simply block any app that seems competitive while others enjoy the high eCPMs that competitors could be generating. A recent study by SOOMLA revealed that ads showing competitors might not be the ones that take your users away and each app needs to be evaluated on a case by case basis before deciding to blacklist.

How to fix it:

There are several SDK providers that can give you insight into who is advertising in your app. Implementing such an SDK in your app will enable a more data driven approach to the decision whether or not to advertise a specific app or block it.

One size fits all

When it comes to ads, not all the users are created equal. For example, some users may respond better to rewarded videos while others yield more revenue from banners and native ads. Serving the same ad experience to all the users is a great way to keep your revenues low.

How to fix it:

Track the yield of each user from each ad-type (for example – by using SOOMLA) and use the data to segment them into groups. You can then build more tailored ad experiences that will improve your ad arpdau.

Introducing rewarded videos late

While it’s clear that most ad formats have a negative impact on retention and payer conversion it’s also clear already that rewarded videos do not have such impact. Since 80% of your users are likely to not survive the first week, delaying ads for 7 days will surely have a negative impact on revenue.

How to fix it:

Introduce rewarded videos as early as possible and even include them in the tutorial. If you want to be a bit more cautious, you can do this only for users who are not likely to pay.

FREE REPORT – VIDEO ADS RETENTION IMPACT

Incentives that don’t add up

In many apps and more specifically in games, the users are rewarded for watching videos. The rewards can range from an extra life to coins or pretty much any upgrade that the game has to offer. Some games have invested time and effort to carefully design the reward opportunities into the game but in other cases the reward for watching videos is in-game currency in small amounts that don’t allow the player to buy anything of value. Offering incentives with little value will discourage users from watching ads.

How to fix it:

First, you should measure opt-in on a cohort basis to see if your users lose interest in the rewards over time. If you detect such an issue you can consult this post for ideas how to improve the incentives – Top 7 Incentives for Video Ads in Mobile Games

Not managing the ad networks

Ad networks are an important part of your monetization but their interests are not always aligned with yours. Typically, for each $1 you are making, the ad-networks are also making a $1. This means that there is a lot of opportunity for the publishers who can closely monitor and negotiate the prices up. Without doing this, your ad monetization not be optimal and might decline over time.

How to fix it:

First, you need a way to track ad revenue per impression sequence so you can manage the waterfall. Additionally, you may also want to get visibility into the campaigns the ad-networks are bringing you. If you don’t have those, you can still negotiate with the ad-networks but it will be harder. To successfully negotiate – remember that your leverage will  be the share in the impressions they are getting as well as their position in the waterfall. In return, you will want to get guarantees for eCPM and fill rates.

Focusing your UA only on payers

If you ask most marketing teams what users are they trying to get for the app they might answer “payers” or “high value players” but in both cases they mean payers actually. What this means is that the monetization manager is trying to monetize with ads users who were supposed to be payers. This strategy is far from ideal. If you are not giving the UA team a task to bring ad whales don’t be surprised that your users don’t do well with ads.

How to fix it:

Step 1 is to figure out who the ad whales are. Once you do that, you can start sending postbacks for ad whales so ad networks can send you more of these high value players. At the same time, you can have the marketing team profile the ad whales and learn more about them so they look for the right media to reach this audience. Finally, targeting lookalikes of the ad whales on FB ads manager has brought great results for some of our customers.

Not doing direct deals

Do you know how many ad-tech middle-mans are between you and the advertiser placing ads in your app? You don’t. It could be 1 or 2 or 5 or 10. One way to know for sure is having no middle-mans. Not doing direct deals means you are leaving money on the table but what’s more important is that you don’t even know how much revenue you are missing out on which means you have very little leverage when you negotiate with ad-networks.

How to fix it:

You should start by getting visibility into who is advertising in your app. This will give you a priority list of who you should be approaching. Getting to the right contact in these companies is not very hard but if you get stuck, shoot me an email to yaniv [at] soom [dot] la and I will try to connect you. Also knowing the eCPM you are getting from each advertiser through the ad-networks could prove useful.

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Analytics, App Monetization, Tech Resources, Tips and Advice

Rewarded Video Ads Strategy for F2P Games

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

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

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

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

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

What design options exist for video ads in F2P games?

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

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

Method 1 – Pull – Gain Currency

Rewarded Video Ads Pull 1 - Gain Currency

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

Method 2 – Pull – Double Rewards

Rewarded Video Ads Pull 2 - Double Rewards

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

Method 3 – Pull – Speed Up

Rewarded Video Ads Pull 3 - Speed Up

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

Method 4 – Push – Forced Video

Rewarded Video Ads Push 4 - Forced Video

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

Most Requested Video Ad Type

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

Video Ad Types and Engagement

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

Do Video Ads Increase Churn?

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

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

Social Point's Results on Do Video Ads Increase Churn

FREE REPORT – VIDEO ADS RETENTION IMPACT

What About Push Video Ads?

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

Do Push Video Ads Increase Churn?


Do Video Ads Cannibalise IAP Revenue?

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

Do Video Ads Canniblize In-App Revenue?

CASE STUDY ON ADVERTISERS CHURN & eCPM

Oooops!

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

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

Too many rewarded videos results in drop in revenue


Conclusion

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

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

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

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

 

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Analytics, App Monetization, Game Design, Tips and Advice

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

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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