Marketing, Tips and Advice

cross promoting between your apps requires creativity - here are 9 ideas how to do cross promo

Most companies in the mobile app ecosystem today have more than one app. Once your company reached this stage, you should start considering cross promoting your new app in the existing apps. You should probably read The Complete Guide to Cross Promotion ROI in addition to checking out these 8 awesome ways to cross promote your apps.

Interstitials and App Trailers

This method is the most obvious way and has been in use for as long as people were making apps. You have one app, you launched a new one. Simply make an app trailer or at least a full page banner ad and add them in the existing app. Most mediation platforms supports this practice and it’s easy enough to do. Keep in mind however that you are taking away from your potential ad-revenue with this method.

Virtual goods / coins bonus

This method is for games only. Virtual goods and currencies are an integral part in most mobile games today. Once your new game is ready you can offer the virtual goods or coins of the new game as a bonus to the users of the existing game. This way the cross promotion message makes the users feel special and has more chances of attracting the users.

In-app notifications

While google and apple are not allowing using push messages for cross promotion, in-app notifications are still allowed. The in-app messages a simple yet effective tool that pops up a “system notification” style message to the user which immediatly grabs his attention.

More games button

This is a classic but still very effective, simply plant a button in your lobby/home screen and allow your users to check what other games you developed for them. Users normally assume that if they liked one of your games they are likely to like another.

Email messages that cross promote a new app

If your iOS app asks users to login or use a social network to connect, you should be able to leverage this method. Android apps can ask a permission to access the user email in the operating system or revert to social login. Once you have a long list of user emails you can leverage them to announce the coming of a new app. If you do this, make sure you include a way to unsubscribe in order to comply with Can Spam Act

Retargeting on Facebook and Google

This method costs some money but could still be effective if your new app monetizes well. Both Facebook and Google allows to target a list of customers and promoting a new app to them. You will need to either integrate an SDK in your existing app in advance for this or if you are a using an attribution provider you can probably ask them for a list of identifiers you can upload for this purpose.

crossy road cross promo method is to introduce avatars from other games

Adding the new game avatars in the existing game

Another method that can only used by games. It was first used by Hipster Whale in their game Crossy Road very effectively except it was used to promote other games. The users get acquinted with the new characters and are interested to explore the new game.

Bonus levels featuring the new app

This method is inspired by the playable ads that are getting a lot of momentum lately. The playable ads allow a user to play a few moves in the existing game before deciding to try the advertised game. Since your company is the developer of both games, you can actually build a better experience and incorporate a short bonus level in the existing game to get the users interested in the new one.

Name hints as a cross-promo tool

This is a generalization of sequales. Obviously, adding the number “2” to the title is an effective way to get users of an existing app interested in the new app. However, sequales requires the apps to be very similar and is a method only for games. Creating a name that hints to the other app creates a softer association that allows the new app to inherit the trust that the users generated towards the existing apps. Some examples:

  • Candy Crush Saga – King created at least 5 more games with a name ending in “Saga”
  • Clash Royale – Supercell hinted that their new game is related to their top game – Clash of Clans
  • Du Apps Studio – Android utility apps maker is dominating the top free charts while all their apps start with “DU”

 

If you would like to measure the tradeoff between cross promotions and ad revenue you should probably start attributing your advertising revenue. Check out SOOMLA Traceback – Ad LTV as a Service.

Learn More

Feel free to share:
Analytics, App Monetization

calculating the ROI of cross promotion activity is complex and requires a powerful analytics service

Once your company has been in the mobile app space long enough it will normally have more than one app and you will start promoting one app within another. This is normally referred to as cross promotion or cross promo for short. In reality, you are simply advertising one of your app inside another and you are reducing the advertising space that you could have given ad-networks. There is a clear trade off between cross promotion and ad revenue so once you start attributing your advertising revenue, you would want to also get a grip on your cross promotion ROI.

Example of cross promotion ROI calculation

Lets think about a single user journey. You paid $3 CPI to bring him to your first app, he generated $1 in the first app that had aggressive cross-promo ads. Over 2 months of playing he watched 500 cross promo ad impressions and then eventually installed your second app where he generated additional $5 in from buying in-app products of the second app. The total he paid you is $6 on a $3 marketing investment. In high level this was a good user but we are interested in the cross promotion ROI. We need to look at each app individually:

The first app lost ad revenue on the cross-promo

When we are looking at the story from the perspective of the first app we realize that there is more to it. The first app paid $3 and only received $1 direct revenues. If we don’t assign any revenue to the cross promotion ads the manager of the first app will stop the campaign that brought this user. Furthermore, the 500 ad-impressions could have generated a few dollars from those 500 ad impressions if it weren’t for the cross-promo ads.

The second app received a free install

The story of the second app is that the $5 generated usually comes with a significant marketing cost. While the manager of the second app could claim $5 to his profit, the reality is that some of this revenue should be claimed by the first app. Lets see how much exactly using two different methods

Use affiliation model to assign a share of the revenue

The first option is to simply decide that a portion of the revenue generated by the second app will be considered as generated by the first app in return for the cross promotion. The origin of this method is in affiliation models and the typical split is between 30% to 50% for the app that brought the traffic. If we go back to our example and use a 50-50 split, the first app would claim $2.5 from the $5 generated in the second app. The ROI analysis will be as follows:

  • The first app spent $3 and received $3.5 – profit of $0.5
  • The cross-promo ads yielded $2.5 on 500 impressions – eCPM of $5
  • The second app spent $2.5 and generated $5 – profit of $2.5

This method is a bit complex and requires the internal BI to track user activities between different apps. In addition, the time that might pass until the 2nd app generated the revenue could be long which makes it hard to relay on.

Assigning a CPI value based on market price

Another method is more inline with how the mobile app economy operates today. Simply decide on a CPI value that the 2nd app is willing to pay based on what they are currently paying. If the 2nd app normally pays $4 CPI, that should be the price. The ROI analysis in our example will there for be:

  • The first app spent $3 and received $5 ($1+$4) – profit of $2
  • The cross-promo ads yielded $4 on 500 impressions – eCPM of $8
  • The second app spent $4 and generated $5 – profit of $1

Prioritizing cross promotion in your mediation platform

Another aspect to consider here is the waterfall configuration. In both methods the ROI analysis we did also yielded an eCPM figure. This figure should be used in the mediation configuration of the first app. If you have providers that can pay higher eCPM they should get higher priority as they will yield more revenue from the company for the same impressions.

Attribution aspects – who brought the install

The example we used is simplified in the sense that the user was only exposed to ads of the second app in the first app. In reality however, he is also likely to get exposed to the second app in other channels. To avoid a situation of double compensation it is advised to apply the same logic you are using when attributing your regular/external campaigns. Typically this is means last click attribution with a 30-day attribution window for clicks and optional 7-day attribution window for impressions.

Another important measurement aspect is to be able to count the cross-promo impressions and differentiate them from the regular ad impressions.

If you want attribute your ad revenue and be able to track cross promotion ROI you should check out SOOMLA Traceback – Ad LTV as a Service.

Learn More

Feel free to share:
App Monetization, Startup Tips

can app companies succeed with ads only header image featuring the word success on an optimistic green gradient background

Many mobile app companies are asking themselves if they still have a shot these days. Are there still opportunities left for someone starting small these days where so much competition already exists from much bigger guys like Supercell, King, EA, Zynga, etc.

The short answer is yes. Lets see how:

The rise of rewarded videos

The top grossing games are monetizing mainly with IAP and competing with them becomes harder and harder. One of the main obstacles for smaller companies is the competition with the huge user acquisition budgets that bigger companies have. On the flip side, these budgets are an opportunity to make revenue from placing ads in your app. This is the opportunity that exists in rewarded videos today. The big game publishers are willing to pay high CPIs that translates into big payouts for apps that can get enough users to watch videos.

Forecasts show more money going into mobile advertising

The good news doesn’t stop with the current trend. Forecasts shows that mobile advertising and specifically video advertising in mobile is going to triple over the next 4 years. This is a result of big brand advertisers starting to warm up to video advertising. Research firm eMarketer is forecasting this revenue to reach $195B in 2019.

mobile internet ad spending worldwide 2013-2019 based on eMarketer research - showing a forecast to reach $195B by 2019

This means that the opportunity to create ad-supported apps is going to get bigger in the next few years.

Organic traffic or paid marketing

Traditionally app companies that monetize through in-app advertising are relaying on organic discovery and word of mouth virality. However, in the last 18 months there is a new breed of companies that are able to generate enough revenue from advertising to be able to also invest in paid marketing. These companies are paying in marketing dollars to get users into their apps and getting paid back for sending these users to other apps. As counter intuitive as this may sound, an app that is able to make more money on a single user than it pays to bring that user in can justify their marketing spend.

Examples of successful ad-supported App Companies

Some app companies that were able to make double digit millions of dollars (based on estimations) while monetizing mainly through advertising: Outfit7, Tabtale, Mobilityware, Gram Games, Tapps Games.

Maybe your company is the next on this list.

If you are planning an ad-supported app you should plan on attributing your ad revenue. Check out SOOMLA Traceback – Ad LTV as a Service.

Learn More

Feel free to share:
App Monetization

Not attributing your ad revenue is like shreding your dollar bills in the air

If your company is making a significant amount of ad revenue it should consider attributing this revenue to users, cohorts, and sources. You might ask yourslef what is the meaning of significant in this context – I would say that $1M of annual ad revenue is the minimal amount to start worrying about ad revenue attribution. However, if you are making over $5M / year from ads and you are not attributing revenue you are really leaving a big sum of money on the table. Here are five ways in which you are losing money by not attributing your ad revenue:

#1 – Shutting down ROI positive campaigns

The first reason why companies worry about attribution is to measure their marketing efforts. Some companies might call it user acquisition or media buying but these are all different names for a situation where you spend money in order to attract customers and need to know if your marketing efforts have ROI. If you are only attributing your IAP revenue to your marketing efforts you are missing out. There are ad-groups and campaigns that are attracting good users that might not spend so much in your game but they do generate ad-revenue and this revenue makes the campaign ROI positive. Not attributing ad revenue properly means you will be shutting down campaigns and ad-groups that are ROI positive and will not be able to enjoy this revenue.

#2 – ROI negative campaigns are kept running

Many companies do the following when it comes to in-game ads:

  • They don’t show ads to paying users
  • They attribute ad-revenue by assuming it follows the same split as the IAP revenue
You probably figured the irony here. If you are not showing ads to paying users than neccessarily segments that are heavy in IAP revenue are light in ad revenue. If you are assuming even distribution between all installs you are a bit better off but you are still over attributing revenue in IAP heavy segments. The impact of this is that mostly likely many campaigns that should have been shut down are kept running.

Lets look at this example:

  • An app makes 50% ad revenue and 50% IAP
  • The company spent $100K on a campaign that brought $60K in IAP revenue
  • Since the split is 50/50 they assume that they made additional $60K in ad-revenue so $120K in total
  • In reality they only made $20K from ad-revenue on that segment so the total was $80K (less than the $100K they spent)
  • The result is that the campaign is kept running although its losing the company money

#3 – Can’t create lookalikes of VIP players with the most ad revenue

Facebook ad campaigns targeted to lookalike audiences of your VIP users are typically the most profitable campaigns. Most companies start off with this method when they start buying media. However, if your app is ad-supported you don’t know who are your VIP users unless you attribute your ad revenue. Not knowing who are you your most profitable users means you company is deprived of this profitable marketing method.

#4 – Can’t use A/B testing to optimize ad exposure levels

A/B testing is a core method of smart marketing in the last few decades. Companies that make most of their ad-revenue from IAP are A/B testing their apps to death and are able to significantly improve conversion rates and other factors. Not being able to attribute ad-revenue means you are not able to measure the impact of different ad-exposure levels and you can’t make data driven decisions when to introduce your cross-promo ads vs. revenue making ads. Not being able to makde data driven decisions about your ad revene could be a major weakness of your compnay.

#5 – Making ad mediation rules on a country level

If your app is making over $1M in ad revenue you are most likely using several ad-networks with a mediation platform to control which one gets what impressions. The logic of the mediaiton platform is limited to the country level unless you are attributing the ad-revenue to users and segments. The mediation platform is assuming that all the users in a given country are the same. Obviously this is not true. For example, if you have brand oriented ad-networks who pay CPM and performance oriented ad-networks who pay CPI. In this situation you would want your ad-mediation to show the performance ads in situations where users are more likely to click and install. Mediating only on a country level basis means you are losing a lot of potential ad revenue.

If you want to start attributing your ad revenue with minimum effort you should check out SOOMLA Traceback – Ad LTV as a Service.

Learn More

Feel free to share:
App Monetization

3_Reasons_Ad_Mediation_Broken

In today’s mobile app ecosystem, ad mediation became the standard for any app company who is doing more than $10K a month from in-app advertising. This makes perfect sense since different ad-networks have strengths and weaknesses when it comes to eCPM and fill rates. For example one ad network might have great campaigns in Russia but underperform in India and vice versa.

There are many problems with the way ad mediation is done today. Here are 3 of them:

Country level segments are not granular enough

The basic function of the ad mediation is to allow you to create a waterfall of ad-networks. Basically this means that you can select which ad-network gets the 1st chance, which one gets the 2nd chance if the first one doesn’t have an ad, which one gets the 3rd chance and so on. This waterfall can be configured differently for different countries. However, ad mediation platform do not allow configuring waterfalls for more advanced segments. For example, you might want to have a different waterfall for males vs. females – there is no way to do that with current mediation solutions.

All ad mediation platforms except for 2 are owned by ad networks

The mediation platform’s role is to be an unbiased 3rd party that works in the service of the publisher to maximize his advertising yield. The selection of what ad-network to show first should be guided only by the interest of the publisher. In reality however, all ad mediation platforms are owned by ad networks. This makes it hard for them to be objective about their decisions and in many cases you can see that the mediation is making sub-optimal setups from the publisher’s perspective.

Automatic optimization mode relays on yesterday’s data

Automatic optimization mode is the default choice for most mediation platforms. The idea is pretty cool – if there was a way to know how much an ad network is going to pay for certain impression, the auto-pilot mode of the mediation could easily decide which network should get the impression and give it to the highest bidder. In reality however, the data that the ad mediation platform has to make that decision is insufficient. It is only able to extract yesterday’s eCPM per country from each network. Since the eCPM is based on how many users ended up converting to installs for the advertisers, the eCPM rates fluctuates quite a lot. The mediation auto-pilot ends up with this cycle:

  • Good network is on top and bad network is receiving less impressions
  • Bad network eCPM fluctuates more due to increased randomness in small sample sizes
  • Every few days the bad network gets “good day” and finds itself on top the day after

In most cases, you will see that the auto-pilot makes a bad decision like that every 4-5 days. Bad days resulting in a loss of about 25% of the revenue that day.

If your app is using a mediation platform with multiple ad networks you should probably start attributing your ad revenue. Check out SOOMLA Traceback – Ad LTV as a Service.

Learn More

 

Feel free to share:
Marketing

LTV calculation for mobile apps that use Google Analytics.

Google Analytics is a popular choice among app developers. However, Getting LTV using GA is harder than one might think. I created this slideshare to explain how to find the required retention rates and the DAU data in the Google Analytics Dashboard. The slides also show how to use an online calculator tool for the lifetime value calculation.

When calculating your LTV, make sure you are including your ad revenue in the mix. If you need a tool to accurately report ad revenue and ad LTV in different segments, cohorts and traffic sources you should check out SOOMLA Traceback.

Learn More

Calculating LTV with Google Analytics Caption

1. MOBILE APP LTV Calculation Using Google Analytics
2. About Me MD @ Kontera (Blog/Text Monetization) Co-founder / CEO @ SOOMLA (Ad LTV as a Service) Co-founder / VP Sales @ Eyeview (Video Ads & Analytics)
3. About SOOMLA Traceback Flexible integration with your BI and Attribution via S2S APIs Leverages listener SDKs that require zero client side code Unique technology that extracts ad revenue per user from inside the ad-networks
4. LTV Calculation Steps Find your ARPDAU Your key retention rates – where to collect them Use online LTV calculator to get the result
5. FINDING YOUR ARPDAU
6. Aggregated Daily Revenue Monthly Revenue Revenue from Google Play $2,000 Revenue from Apple $4,000 Ad Revenue $3,000 Total $9,000 Daily Revenue – the monthly revenue divided by number of days. In this case it’s $300
7. DAU in GA – Step 1 Go to the “Active Users” view and select a date range of 1 week and “1 Day Active Users”
8. DAU in GA – Step 2 Either collect the data points one by one by copying and pasting or simply download the CSV
9. Averaging DAU DAU Sunday 562 Monday 907 Tuesday 1,071 Wednesday 1,244 Thursday 1,019 Friday 940 Saturday 2,278 Average 1,146 Tip – the DAU usually fluctuates during the week so it’s important to use average of at least one week
10. ARPDAU Calculation ARPDAU – the daily revenue divided by the average daily active users (DAU) Calculation Average Daily Revenue $300 Average DAU 1,146 Total $0.26
11. KEY RETENTION RATES
12. Retention in GA – Step 1 Select “Cohort Analysis” and set the date filter to “Last 30 days” and the resolution to “by day”
13. Retention in GA – Step 2 Collect the points from the top row – you need day-1, day-7, day-14 and day-30
14. Key Retention Rates Retention Rate Day1 7.37% Day7 3.53% Day14 3.10% Day30 2.70% Note – we took a slightly lower number for Day30. Flurry had only Day28 Retention
15. USING THE CALCULATOR http://blog.soom.la/2016/04/clv-calculation-modeling-lifetime.html
16. Feeding Retention Data In Use the key retention rates from step 2 in the top part of the LTV calculators
17. Feeding ARPDAU Data In Use the ARPDAU we calculated in step 1 in the bottom part of the calculator
18. The Result The result is shown in the bottom part of the calculator
19. Thank you!

Feel free to share:
App Monetization

mastering "CPM commitments" will allow your ad revenue to reach the skies like a rocket

Many app publishers today are utilizing in-app advertising to monetize their apps. This article teaches how to secure fixed CPM commitments from ad-networks and how to use them to boost ad-revenue. It includes explanation how to set up your ad-mediation to negate counter measures that are likely to be taken by the ad-networks and how to outsmart them.

CPM commitments needs to be locked with IO

Once you reach a certain volume of about 10M impressions per month in US, ad-networks will start chasing you. If you are using a mediation platform these ad-networks will try to get a bigger share of the impressions by making all sorts of guarentees about CPMs in order to get priority. A typical offer might be: “put us on the top priority in the waterfall and we can promise $7 CPM”. If you get one of these, you should close it with an IO. If you haven’t heard of this term – IO stands for insertion order and it’s a standard way of buying and selling advertising space. A typical ad-network would execute hundreds of IOs every month so they should be very familiar with the process. Locking down the commitment with an IO gives you a few benefits:

  • It means that the ad-network has to keep its word and pay you a fixed price based on impressions
  • The ad-network takes the risk in this case so fluctuations that are caused by campaign changes will impact their profitability and not your revenue
  • This gives a much better basis to go to other networks and get better offers

Expect that a CPM floor will be applied

The ad-network is a smart organizm that leaves and drives data and constently optimizes so what will likely happen is that the ad-network will apply a CPM floor on their side to make sure they are not losing money. Behind the scenes, each network has advanced algorithms that associate an eCPM with each ad display opportunity, when they apply a CPM floor they are telling the algorithm to drop any request that is evaluated below that threshold. The result on your side is that the ad-network will only send you their top campaigns and the fill rate will be dropped. If they give you a CPM of $7 the floor will make sure that you are actually giving them impressions that could have earned you more. There is a cure however. You need to give the best impressions to the other ad-networks.

Configure your ad mediation around CPM deals to boost ad revenue

To understand how to avoid the negative impact of the CPM floor we first have to understand a critical thing about the impact that multiple ad impressions have on eCPM for performance campaigns. Users are less likely to click and install an app that is being advertised to them if they are being exposed to many ads. While each game has their own response curve they all follow the same trend of the 1st impression being the highest paying and the last impression being the lowest paying. The chart below shows the difference in eCPM between performance campaigns and committed CPM campaigns.

image

With this new realization you can now go to your mediaiton platform and find the way to configure it so it would:

  • Give the 1st impressions, 2nd impression and 3rd impression to ad-networks that are paying you based on performance – this way you get to keep the high eCPMs on these impressions.
  • Give impressions 4 and after to the network that gave the CPM commitment – this way you are using the fixed CPM to increase the revenue on these impressions
  • Make sure you have at least 2 additional networks to catch the last impressions that the are left

This method is demonstrated in the chart below. On the left side you will see the most basic setup of putting the network that gave the CPM commitment on top of the waterfall. This will actually result in an overall revenue decrease. On the right hand side you can see what happens when you allow performance campaigns to get the first few impressiosn of every user.

image

The ad revenue difference in this example is pretty big. On the left side your average eCPM of all networks will be $4.9 while on the right side, the average will be $6.1. That’s a 24% revenue increase. The eCPM boost on the performance campaigns will be even higher – 57% lift.

Leave room for real time bidding (RTB)

Once you have a fixed CPM commitment, you would need to configure it in the waterfall using your mediation platform. You should keep in mind that there are 3 types of networks you are configuring:

  1. Network with Fixed CPM commitment
  2. Network with rev-share deal paying based on performance
  3. SSP SDKs that provide real time bids for impressions they serve

Unlike #2, ad responses coming from #3 would have a specific CPM value attached to them. Let’s consider 2 cases:

  • The fixed CPM of #1 is $7 and the real-time bid of #3 is $6 – in this case you would want to give the impression to network #1
  • The fixed CPM of #1 is $7 and the real-time bid of #3 is $9 – in this case you would want to give the impression to network #3.

You should configure your mediation platform to allow high bids to win against the fixed CPM if you know that the bid is real CPM and not eCPM. The setup of every mediation platform is a bit different but they all have a way to do it. You should also keep in mind that most mediation platforms would also have their own real time bidding so even if you didn’t add external SSP, you should still allow room for RTB.

 

If you want to analyze the ad revenue you are making on each ad impression you should check out SOOMLA Traceback – Ad LTV as a Service

Learn More

Feel free to share:
Marketing

Calculating LTV for mobile apps with flurry analytics and an online calculator.

In the early years of the mobile app ecosystem, Flurry analytics was the only way to go. The free platform offered basic KPIs, charts and trends that will satisfy mobile app developers measurement needs. Flurry remained a popular choice among smaller app developers even when more competitors entered the space. While the platform gives many KPIs, calcualting LTV is still pretty complex for app publishers who relay on Flurry. The presentation below provides an easy solution and walks the reader through collecting information from flurry and inserting it into an online LTV calculator.

 

When calculating your LTV, make sure you are including your ad revenue in the mix. If you need a tool to accurately report ad revenue and ad LTV in different segments, cohorts and traffic sources you should check out SOOMLA Traceback.

Learn More

Calculating LTV with Flurry Analytics Caption

1. MOBILE APP LTV Calculation Using Flurry Analytics
2. About Me MD @ Kontera (Blog/Text Monetization) Co-founder / CEO @ SOOMLA (Ad LTV as a Service) Co-founder / VP Sales @ Eyeview (Video Ads & Analytics)
3. About SOOMLA Traceback Flexible integration with your BI and Attribution via S2S APIs Leverages listener SDKs that require zero client side code Unique technology that extracts ad revenue per user from inside the ad-networks
4. LTV Calculation Steps Find your ARPDAU Your key retention rates – where to collect them Use online LTV calculator to get the result
5. FINDING YOUR ARPDAU
6. Aggregated Daily Revenue Monthly Revenue Revenue from Google Play $6,000 Revenue from Apple $2,000 Ad Revenue $40,000 Total $12,000 Daily Revenue – the monthly revenue divided by number of days. In this case it’s $400
7. DAU in Flurry Analytics – Step 1 Go to the “Active Users” view and select “Last Week”
8. DAU in Flurry Analytics – Step 2 Either collect the data points one by one by copying and pasting or simply download the CSV
9. Averaging DAU DAU Sunday 2,450 Monday 2,305 Tuesday 2,773 Wednesday 3,054 Thursday 2,957 Friday 2,597 Saturday 2,278 Average 2,631 Tip – the DAU usually fluctuates during the week so it’s important to use average of at least one week
10. ARPDAU Calculation ARPDAU – the daily revenue divided by the average daily active users (DAU) Calculation Average Daily Revenue $400 Average DAU 2,613 Total $0.2
11. KEY RETENTION RATES
12. Retention in Flurry Analytics – Step 1 Select “Return Rate” and set the date filter to “Last Month” and the resolution to “days”
13. Retention in Flurry Analytics – Step 2 Collect the points from the bottom row – this is the average retention rate for that day
14. Key Retention Rates Retention Rate Day1 37.90% Day7 8.70% Day14 4.10% Day30 1.10% Note – we took a slightly lower number for Day30. Flurry had only Day28 Retention
15. USING THE CALCULATOR http://blog.soom.la/2016/04/clv-calculation-modeling-lifetime.html
16. Feeding Retention Data In Use the key retention rates from step 2 in the top part of the LTV calculators
17. Feeding ARPDAU Data In Use the ARPDAU we calculated in step 1 in the bottom part of the calculator
18. The Result The result is shown in the bottom part of the calculator
19. Thank you!

Feel free to share:

Join 14441 other smart people who get email updates for free!

We don't spam!

Unsubscribe any time

Categories

Archives

SOOMLA - An In-app Purchase Store and Virtual Goods Economy Solution for Mobile Game Developers of Free to Play Games