UA in Ads-Driven Gaming Business + Q&A

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12

Luka Rade (App Sales Director at Outfit 7) talks about the differences between IAP-driven and Ad-driven games when it comes to user acquisition, the best way to calculate Ad-LTV, increase ROI and what to focus on.

Source:
UA in Ads-Driven Gaming Business + Q&A
(no direct link to watch/listen)
(direct link to watch/listen)
Type:
Presentation
Publication date:
June 16, 2020
Added to the Vault on:
July 11, 2020
These insights were shared through the free Growth Gems newsletter.
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💎 #
1

Data has an immense value. Just like the big networks collect data to improve their algorithms, so should you - proprietary data is of the utmost importance when doing paid user acquisition. 

45:30
💎 #
4

One effort to better calculate your Ad LTV is to focus on knowing how many impressions each user has seen from each provider and the ad type (banner, video, interstitials). So get daily reports from your ad providers on the revenue generated and the number of impressions (per ad type, platform, country, etc.) then combine with MMP data to aggregate data on dimensions like country, platform, network and publisher. This might become tricky! 

52:45
💎 #
5

The biggest way a UA team of an Ad-driven game can have an impact on ROI is to have an impact on costs, by increasing IPM (install per 1000 impressions) which can be done through improving creatives. This will in turn increase the reach of UA. 

55:24
💎 #
6

Having the UA team share numbers from creatives with the product team can have an impact on retention because you can incorporate what performs well in acquisition in the actual product. Example: emotional hooks in outfit 7's creatives that can be added to the game. 

56:54
💎 #
7

Despite the progress of machine learning on Google and other platforms to acquire engaged users, focus your campaigns on targeting for shallow events (level 2/3, watching rewarded video ads, etc.) because a big percentage of users reach them and reach them fast + they are good indicators of high quality users. 

58:43
💎 #
8

Deeper events don't necessarily work because the LTV deviation between players are usually fairly small. If you optimize for events that are not reached often the increase in cost of your campaigns will not be compensated by the increase in LTV.  

59:23
💎 #
9

Still because of the low LTV deviation between players, Ad-driven businesses have the advantage of allowing to test new geos cheaper and faster: a small amount of installs allows to accurately estimate the value of users in certain markets. This allows you to focus on improving IPM through creatives and localization. 

01:02:04
💎 #
10

Because there is not enough scale at the creative level to have a strong signal enough on ROI, beyond IPM Nordeus looks at the Cost per D1 retained users as a proxy metric. [Nordeus] 

01:15:11
💎 #
11

The most important thing to test currently is which events to optimize for, and this includes custom events (as long as they happen enough in the first few days and are predicting high user quality). [Nordeus]

01:18:44
💎 #
12

You can get good results optimizing for "watch X rewarded videos" events. To do this you want to know the % of users reaching these kind of events, how fast they are reaching these events and how these events correlate with being a higher quality user. 

01:21:14
💎 #
2

Targeting for Ad-driven games is usually broad because anyone can generate revenue and LTV is limited by retention. The key UA campaign focus is therefore mostly on IPM in order to decrease the eCPA (vs. ROAS for IAP-driven games). 

47:02
💎 #
3

Calculating your Ad LTV in its most basic form (a function of ARPDAU and retention) is not enough because the value generated by users from different markets/networks/publishers differs. So you need more granular data. 

48:13
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  • Define your preferred categories and receive new relevant gems directly in your inbox
  • Discuss key insights (and any other mobile growth topic) in the members-only community.
Upgrade Your Plan
💎 #
1

Data has an immense value. Just like the big networks collect data to improve their algorithms, so should you - proprietary data is of the utmost importance when doing paid user acquisition. 

45:30
💎 #
4

One effort to better calculate your Ad LTV is to focus on knowing how many impressions each user has seen from each provider and the ad type (banner, video, interstitials). So get daily reports from your ad providers on the revenue generated and the number of impressions (per ad type, platform, country, etc.) then combine with MMP data to aggregate data on dimensions like country, platform, network and publisher. This might become tricky! 

52:45
💎 #
5

The biggest way a UA team of an Ad-driven game can have an impact on ROI is to have an impact on costs, by increasing IPM (install per 1000 impressions) which can be done through improving creatives. This will in turn increase the reach of UA. 

55:24
💎 #
6

Having the UA team share numbers from creatives with the product team can have an impact on retention because you can incorporate what performs well in acquisition in the actual product. Example: emotional hooks in outfit 7's creatives that can be added to the game. 

56:54
💎 #
7

Despite the progress of machine learning on Google and other platforms to acquire engaged users, focus your campaigns on targeting for shallow events (level 2/3, watching rewarded video ads, etc.) because a big percentage of users reach them and reach them fast + they are good indicators of high quality users. 

58:43
💎 #
8

Deeper events don't necessarily work because the LTV deviation between players are usually fairly small. If you optimize for events that are not reached often the increase in cost of your campaigns will not be compensated by the increase in LTV.  

59:23
💎 #
9

Still because of the low LTV deviation between players, Ad-driven businesses have the advantage of allowing to test new geos cheaper and faster: a small amount of installs allows to accurately estimate the value of users in certain markets. This allows you to focus on improving IPM through creatives and localization. 

01:02:04
💎 #
10

Because there is not enough scale at the creative level to have a strong signal enough on ROI, beyond IPM Nordeus looks at the Cost per D1 retained users as a proxy metric. [Nordeus] 

01:15:11
💎 #
11

The most important thing to test currently is which events to optimize for, and this includes custom events (as long as they happen enough in the first few days and are predicting high user quality). [Nordeus]

01:18:44
💎 #
12

You can get good results optimizing for "watch X rewarded videos" events. To do this you want to know the % of users reaching these kind of events, how fast they are reaching these events and how these events correlate with being a higher quality user. 

01:21:14
💎 #
2

Targeting for Ad-driven games is usually broad because anyone can generate revenue and LTV is limited by retention. The key UA campaign focus is therefore mostly on IPM in order to decrease the eCPA (vs. ROAS for IAP-driven games). 

47:02
💎 #
3

Calculating your Ad LTV in its most basic form (a function of ARPDAU and retention) is not enough because the value generated by users from different markets/networks/publishers differs. So you need more granular data. 

48:13
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💎 #
1

Data has an immense value. Just like the big networks collect data to improve their algorithms, so should you - proprietary data is of the utmost importance when doing paid user acquisition. 

45:30
💎 #
4

One effort to better calculate your Ad LTV is to focus on knowing how many impressions each user has seen from each provider and the ad type (banner, video, interstitials). So get daily reports from your ad providers on the revenue generated and the number of impressions (per ad type, platform, country, etc.) then combine with MMP data to aggregate data on dimensions like country, platform, network and publisher. This might become tricky! 

52:45
💎 #
5

The biggest way a UA team of an Ad-driven game can have an impact on ROI is to have an impact on costs, by increasing IPM (install per 1000 impressions) which can be done through improving creatives. This will in turn increase the reach of UA. 

55:24
💎 #
6

Having the UA team share numbers from creatives with the product team can have an impact on retention because you can incorporate what performs well in acquisition in the actual product. Example: emotional hooks in outfit 7's creatives that can be added to the game. 

56:54
💎 #
7

Despite the progress of machine learning on Google and other platforms to acquire engaged users, focus your campaigns on targeting for shallow events (level 2/3, watching rewarded video ads, etc.) because a big percentage of users reach them and reach them fast + they are good indicators of high quality users. 

58:43
💎 #
8

Deeper events don't necessarily work because the LTV deviation between players are usually fairly small. If you optimize for events that are not reached often the increase in cost of your campaigns will not be compensated by the increase in LTV.  

59:23
💎 #
9

Still because of the low LTV deviation between players, Ad-driven businesses have the advantage of allowing to test new geos cheaper and faster: a small amount of installs allows to accurately estimate the value of users in certain markets. This allows you to focus on improving IPM through creatives and localization. 

01:02:04
💎 #
10

Because there is not enough scale at the creative level to have a strong signal enough on ROI, beyond IPM Nordeus looks at the Cost per D1 retained users as a proxy metric. [Nordeus] 

01:15:11
💎 #
11

The most important thing to test currently is which events to optimize for, and this includes custom events (as long as they happen enough in the first few days and are predicting high user quality). [Nordeus]

01:18:44
💎 #
12

You can get good results optimizing for "watch X rewarded videos" events. To do this you want to know the % of users reaching these kind of events, how fast they are reaching these events and how these events correlate with being a higher quality user. 

01:21:14
💎 #
2

Targeting for Ad-driven games is usually broad because anyone can generate revenue and LTV is limited by retention. The key UA campaign focus is therefore mostly on IPM in order to decrease the eCPA (vs. ROAS for IAP-driven games). 

47:02
💎 #
3

Calculating your Ad LTV in its most basic form (a function of ARPDAU and retention) is not enough because the value generated by users from different markets/networks/publishers differs. So you need more granular data. 

48:13
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Become a member to:
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Notes for this resource are currently being transferred and will be available soon.

Before this presentation, there is a presentation by Andrej Kugonič (User Acquisition Lead at Nordeus - Top Eleven) on "Post COVID-19 UA strategy for IAP-driven business". At the end there is a Q&A with both Luka and Andrej, included here.

[💎 @45:30] Data has an immense value. Just like the big networks collect data to improve their algorithms, so should you - proprietary data is of the utmost importance when doing paid user acquisition.

[💎 @47:02] Targeting for Ad-driven games is usually broad because anyone can generate revenue and LTV is limited by retention. The key UA campaign focus is therefore mostly on IPM in order to decrease the eCPA (vs. ROAS for IAP-driven games).


[💎 @48:13] Calculating your Ad LTV in its most basic form (a function of ARPDAU and retention) is not enough because the value generated by users from different markets/networks/publishers differs. So you need more granular data.

In an ideal scenario we would know the exact LTV of each user but it is very unlikely because you work with a lot of partners.


[💎 @52:45] One effort to better calculate your Ad LTV is to focus on knowing how many impressions each user has seen from each provider and the ad type (banner, video, interstitials). So get daily reports from your ad providers on the revenue generated and the number of impressions (per ad type, platform, country, etc.) then combine with MMP data to aggregate data on dimensions like country, platform, network and publisher.

Because monetization is a ARPDAU x Retention, it is hard for the UA team to have a big impact on revenue.

[💎 @55:24] The biggest way a UA team of an Ad-driven game can have an impact on ROI is to have an impact on costs, by increasing IPM (install per 1000 impressions) which can be done through improving creatives. This will in turn increase the reach of UA.

How to collaborate with product and creative team to increase Ad LTV and be able to enter specific markets?

[💎 @56:54] Having the UA team share numbers from creatives with the product team can have an impact on retention because you can incorporate what performs well in acquisition in the actual product. Example: emotional hooks in outfit 7's creatives that can be added to the game.


[💎 @58:43] Despite the progress of machine learning on Google and other platforms to acquire engage users, focus your campaigns on targeting for shallow events (level 2/3, watching rewarded video ads, etc.) because a big percentage of users reach them and reach them fast + they are good indicators of high quality users.


[💎 @59:23] Deeper events don't necessarily work because the LTV deviation between players are usually fairly small. If you optimize for events that are not reached often the increase in cost of your campaigns will not be compensated by the increase in LTV.



[💎 @01:02:04] Still because of the low LTV deviation between players, Ad-driven businesses have the advantage of allowing to test new geos cheaper and faster: a small amount of installs allows to accurately estimate the value of users in certain markets. This allows you to focus on improving IPM through creatives and localization.


LTV calculations are even more important in Ad-driven games because the margin of error in Tier 3 countries (India, Indonesia) can be so small that 1 or 2 cts can be a determining factor.


Focus on automatization because it will keep you flexible and responsive to market trends and limit errors. Leverage APIs and algorithms.

Luka mentioned Brazil and Russia.


UA: good and best practices. Discussion and Q&A session.

On calculating the K factor and ROI of campaigns

  • [Outfit 7] Not something that is static per geo and it changes based on your rank. Outfit 7 has a huge amount of data to make calculations even on smaller geos but they are not really looking at it in their profitability calculations.

How to attribute and measure the effect of traditional media (tv, radio, etc.)?

  • [Nordeus] They use almost only TV. Some attribution models follow the TV airing timestamps (minute) and check for spikes in organic uplifts vs. baseline in the next 15-30 minutes. Then use LTV from organic installs to measure ROI.
  • [Nordeus] If it's for branding then they do not look at ROI.
  • [Nordeus] They also measure the effect of TV on CTR for digital campaigns.
  • [Outfit 7] Not possible at the user level. But you can compare what happens in markets where you're using traditional media vs. countries where you are not by calculating the delta. Also look at IPM increases in digital campaigns

How do you set ROI target for your UA campaigns? Do you have targets for all campaigns separately or for GEOS, platform, etc.

  • [Nordeus] If it is not incentivized traffic then the LTV curve behavior is pretty similar across channels and countries, especially after D7. So they have similar ROI thresholds for channels/countries. Typically use D3/D7/D30.
  • [Outfit 7] Not big difference either per channel/countries.

Creative optimization: have you seen phenomenal IPM from a creative that did not translate into a good ROI?

  • [Outfit 7] As long as users see ads monetization and you have decent retention then it is fine. Some creatives do bring in users efficiently while bringing monetization below other creatives but the deviation is typically low.
  • [Nordeus] Check beyond CPI and what is important is IPM.
  • [💎 @01:15:11] Because there is not enough scale at the creative level to have a strong signal enough on ROI, beyond IPM Nordeus looks at the Cost per D1 retained users as a proxy metric.

Ways to test creatives?

  • [Nordeus] Changing the way they test creatives. Now they put new creatives in campaigns and check if they get traffic and then performance.

Automation/machine learning vs. being control freak?

  • [Nordeus] Testing a lot of things manually.
    - Google: don't really target a lot but you can test behavior depending on budget to find the sweet spot.
    - Facebook: change % of LAL vs. budget by checking CPI/LTV ratios.
    - [💎 @01:18:44] The most important thing to test currently is which events to optimize for, and this includes custom events (as long as they happen enough in the first few days and are predicting high user quality).
  • [Outfit 7] Testing custom events a lot as well beyond classic events, especially on platforms leveraging machine learning.

Best possible event to start optimization with? Is it worth bidding towards Ad Events like "Ads watched: 10 ads watched, 30...") and not just "reach level X".

  • [Outfit 7] [💎 @01:21:14] You can get good results optimizing for "watch X rewarded videos" events. To do this you want to know the % of users reaching these kind of events, how fast they are reaching these events and how these events correlate with being a higher quality user.
  • [Outfit 7] These events differ from product to product and there will be trial and error but these kinds of events allow you to bid higher and reach pockets of users you were not targeting before.

Changed anything in the game during covid?

  • [Nordeus] Tried to be user focused and therefore gave more things inside the game: live events, special sponsoring, etc.
  • [Outfit 7] No big shifts in the game but big shifts in monetization (advertisers pulling out) but also decreased cost on the advertising side as well.

CPI decrease with LTV constant: depended on channel?

  • [Nordeus] Was true for most channels
  • [Outfit 7] Also have seen LTV decrease a bit but ROI/bottom line actually improved.



The notes from this resource are only available to premium members.
↘ At this point, you know what to do ↙
Upgrade Your Plan

Before this presentation, there is a presentation by Andrej Kugonič (User Acquisition Lead at Nordeus - Top Eleven) on "Post COVID-19 UA strategy for IAP-driven business". At the end there is a Q&A with both Luka and Andrej, included here.

[💎 @45:30] Data has an immense value. Just like the big networks collect data to improve their algorithms, so should you - proprietary data is of the utmost importance when doing paid user acquisition.

[💎 @47:02] Targeting for Ad-driven games is usually broad because anyone can generate revenue and LTV is limited by retention. The key UA campaign focus is therefore mostly on IPM in order to decrease the eCPA (vs. ROAS for IAP-driven games).


[💎 @48:13] Calculating your Ad LTV in its most basic form (a function of ARPDAU and retention) is not enough because the value generated by users from different markets/networks/publishers differs. So you need more granular data.

In an ideal scenario we would know the exact LTV of each user but it is very unlikely because you work with a lot of partners.


[💎 @52:45] One effort to better calculate your Ad LTV is to focus on knowing how many impressions each user has seen from each provider and the ad type (banner, video, interstitials). So get daily reports from your ad providers on the revenue generated and the number of impressions (per ad type, platform, country, etc.) then combine with MMP data to aggregate data on dimensions like country, platform, network and publisher.

Because monetization is a ARPDAU x Retention, it is hard for the UA team to have a big impact on revenue.

[💎 @55:24] The biggest way a UA team of an Ad-driven game can have an impact on ROI is to have an impact on costs, by increasing IPM (install per 1000 impressions) which can be done through improving creatives. This will in turn increase the reach of UA.

How to collaborate with product and creative team to increase Ad LTV and be able to enter specific markets?

[💎 @56:54] Having the UA team share numbers from creatives with the product team can have an impact on retention because you can incorporate what performs well in acquisition in the actual product. Example: emotional hooks in outfit 7's creatives that can be added to the game.


[💎 @58:43] Despite the progress of machine learning on Google and other platforms to acquire engage users, focus your campaigns on targeting for shallow events (level 2/3, watching rewarded video ads, etc.) because a big percentage of users reach them and reach them fast + they are good indicators of high quality users.


[💎 @59:23] Deeper events don't necessarily work because the LTV deviation between players are usually fairly small. If you optimize for events that are not reached often the increase in cost of your campaigns will not be compensated by the increase in LTV.



[💎 @01:02:04] Still because of the low LTV deviation between players, Ad-driven businesses have the advantage of allowing to test new geos cheaper and faster: a small amount of installs allows to accurately estimate the value of users in certain markets. This allows you to focus on improving IPM through creatives and localization.


LTV calculations are even more important in Ad-driven games because the margin of error in Tier 3 countries (India, Indonesia) can be so small that 1 or 2 cts can be a determining factor.


Focus on automatization because it will keep you flexible and responsive to market trends and limit errors. Leverage APIs and algorithms.

Luka mentioned Brazil and Russia.


UA: good and best practices. Discussion and Q&A session.

On calculating the K factor and ROI of campaigns

  • [Outfit 7] Not something that is static per geo and it changes based on your rank. Outfit 7 has a huge amount of data to make calculations even on smaller geos but they are not really looking at it in their profitability calculations.

How to attribute and measure the effect of traditional media (tv, radio, etc.)?

  • [Nordeus] They use almost only TV. Some attribution models follow the TV airing timestamps (minute) and check for spikes in organic uplifts vs. baseline in the next 15-30 minutes. Then use LTV from organic installs to measure ROI.
  • [Nordeus] If it's for branding then they do not look at ROI.
  • [Nordeus] They also measure the effect of TV on CTR for digital campaigns.
  • [Outfit 7] Not possible at the user level. But you can compare what happens in markets where you're using traditional media vs. countries where you are not by calculating the delta. Also look at IPM increases in digital campaigns

How do you set ROI target for your UA campaigns? Do you have targets for all campaigns separately or for GEOS, platform, etc.

  • [Nordeus] If it is not incentivized traffic then the LTV curve behavior is pretty similar across channels and countries, especially after D7. So they have similar ROI thresholds for channels/countries. Typically use D3/D7/D30.
  • [Outfit 7] Not big difference either per channel/countries.

Creative optimization: have you seen phenomenal IPM from a creative that did not translate into a good ROI?

  • [Outfit 7] As long as users see ads monetization and you have decent retention then it is fine. Some creatives do bring in users efficiently while bringing monetization below other creatives but the deviation is typically low.
  • [Nordeus] Check beyond CPI and what is important is IPM.
  • [💎 @01:15:11] Because there is not enough scale at the creative level to have a strong signal enough on ROI, beyond IPM Nordeus looks at the Cost per D1 retained users as a proxy metric.

Ways to test creatives?

  • [Nordeus] Changing the way they test creatives. Now they put new creatives in campaigns and check if they get traffic and then performance.

Automation/machine learning vs. being control freak?

  • [Nordeus] Testing a lot of things manually.
    - Google: don't really target a lot but you can test behavior depending on budget to find the sweet spot.
    - Facebook: change % of LAL vs. budget by checking CPI/LTV ratios.
    - [💎 @01:18:44] The most important thing to test currently is which events to optimize for, and this includes custom events (as long as they happen enough in the first few days and are predicting high user quality).
  • [Outfit 7] Testing custom events a lot as well beyond classic events, especially on platforms leveraging machine learning.

Best possible event to start optimization with? Is it worth bidding towards Ad Events like "Ads watched: 10 ads watched, 30...") and not just "reach level X".

  • [Outfit 7] [💎 @01:21:14] You can get good results optimizing for "watch X rewarded videos" events. To do this you want to know the % of users reaching these kind of events, how fast they are reaching these events and how these events correlate with being a higher quality user.
  • [Outfit 7] These events differ from product to product and there will be trial and error but these kinds of events allow you to bid higher and reach pockets of users you were not targeting before.

Changed anything in the game during covid?

  • [Nordeus] Tried to be user focused and therefore gave more things inside the game: live events, special sponsoring, etc.
  • [Outfit 7] No big shifts in the game but big shifts in monetization (advertisers pulling out) but also decreased cost on the advertising side as well.

CPI decrease with LTV constant: depended on channel?

  • [Nordeus] Was true for most channels
  • [Outfit 7] Also have seen LTV decrease a bit but ROI/bottom line actually improved.



The notes from this resource are only available to premium members.

The detailed notes taken for a resource are an easy way to see the gems in context to get a better understanding. They also include any relevant visuals from the source.
↘ At this point, you know what to do ↙
Request Access

Before this presentation, there is a presentation by Andrej Kugonič (User Acquisition Lead at Nordeus - Top Eleven) on "Post COVID-19 UA strategy for IAP-driven business". At the end there is a Q&A with both Luka and Andrej, included here.

[💎 @45:30] Data has an immense value. Just like the big networks collect data to improve their algorithms, so should you - proprietary data is of the utmost importance when doing paid user acquisition.

[💎 @47:02] Targeting for Ad-driven games is usually broad because anyone can generate revenue and LTV is limited by retention. The key UA campaign focus is therefore mostly on IPM in order to decrease the eCPA (vs. ROAS for IAP-driven games).


[💎 @48:13] Calculating your Ad LTV in its most basic form (a function of ARPDAU and retention) is not enough because the value generated by users from different markets/networks/publishers differs. So you need more granular data.

In an ideal scenario we would know the exact LTV of each user but it is very unlikely because you work with a lot of partners.


[💎 @52:45] One effort to better calculate your Ad LTV is to focus on knowing how many impressions each user has seen from each provider and the ad type (banner, video, interstitials). So get daily reports from your ad providers on the revenue generated and the number of impressions (per ad type, platform, country, etc.) then combine with MMP data to aggregate data on dimensions like country, platform, network and publisher.

Because monetization is a ARPDAU x Retention, it is hard for the UA team to have a big impact on revenue.

[💎 @55:24] The biggest way a UA team of an Ad-driven game can have an impact on ROI is to have an impact on costs, by increasing IPM (install per 1000 impressions) which can be done through improving creatives. This will in turn increase the reach of UA.

How to collaborate with product and creative team to increase Ad LTV and be able to enter specific markets?

[💎 @56:54] Having the UA team share numbers from creatives with the product team can have an impact on retention because you can incorporate what performs well in acquisition in the actual product. Example: emotional hooks in outfit 7's creatives that can be added to the game.


[💎 @58:43] Despite the progress of machine learning on Google and other platforms to acquire engage users, focus your campaigns on targeting for shallow events (level 2/3, watching rewarded video ads, etc.) because a big percentage of users reach them and reach them fast + they are good indicators of high quality users.


[💎 @59:23] Deeper events don't necessarily work because the LTV deviation between players are usually fairly small. If you optimize for events that are not reached often the increase in cost of your campaigns will not be compensated by the increase in LTV.



[💎 @01:02:04] Still because of the low LTV deviation between players, Ad-driven businesses have the advantage of allowing to test new geos cheaper and faster: a small amount of installs allows to accurately estimate the value of users in certain markets. This allows you to focus on improving IPM through creatives and localization.


LTV calculations are even more important in Ad-driven games because the margin of error in Tier 3 countries (India, Indonesia) can be so small that 1 or 2 cts can be a determining factor.


Focus on automatization because it will keep you flexible and responsive to market trends and limit errors. Leverage APIs and algorithms.

Luka mentioned Brazil and Russia.


UA: good and best practices. Discussion and Q&A session.

On calculating the K factor and ROI of campaigns

  • [Outfit 7] Not something that is static per geo and it changes based on your rank. Outfit 7 has a huge amount of data to make calculations even on smaller geos but they are not really looking at it in their profitability calculations.

How to attribute and measure the effect of traditional media (tv, radio, etc.)?

  • [Nordeus] They use almost only TV. Some attribution models follow the TV airing timestamps (minute) and check for spikes in organic uplifts vs. baseline in the next 15-30 minutes. Then use LTV from organic installs to measure ROI.
  • [Nordeus] If it's for branding then they do not look at ROI.
  • [Nordeus] They also measure the effect of TV on CTR for digital campaigns.
  • [Outfit 7] Not possible at the user level. But you can compare what happens in markets where you're using traditional media vs. countries where you are not by calculating the delta. Also look at IPM increases in digital campaigns

How do you set ROI target for your UA campaigns? Do you have targets for all campaigns separately or for GEOS, platform, etc.

  • [Nordeus] If it is not incentivized traffic then the LTV curve behavior is pretty similar across channels and countries, especially after D7. So they have similar ROI thresholds for channels/countries. Typically use D3/D7/D30.
  • [Outfit 7] Not big difference either per channel/countries.

Creative optimization: have you seen phenomenal IPM from a creative that did not translate into a good ROI?

  • [Outfit 7] As long as users see ads monetization and you have decent retention then it is fine. Some creatives do bring in users efficiently while bringing monetization below other creatives but the deviation is typically low.
  • [Nordeus] Check beyond CPI and what is important is IPM.
  • [💎 @01:15:11] Because there is not enough scale at the creative level to have a strong signal enough on ROI, beyond IPM Nordeus looks at the Cost per D1 retained users as a proxy metric.

Ways to test creatives?

  • [Nordeus] Changing the way they test creatives. Now they put new creatives in campaigns and check if they get traffic and then performance.

Automation/machine learning vs. being control freak?

  • [Nordeus] Testing a lot of things manually.
    - Google: don't really target a lot but you can test behavior depending on budget to find the sweet spot.
    - Facebook: change % of LAL vs. budget by checking CPI/LTV ratios.
    - [💎 @01:18:44] The most important thing to test currently is which events to optimize for, and this includes custom events (as long as they happen enough in the first few days and are predicting high user quality).
  • [Outfit 7] Testing custom events a lot as well beyond classic events, especially on platforms leveraging machine learning.

Best possible event to start optimization with? Is it worth bidding towards Ad Events like "Ads watched: 10 ads watched, 30...") and not just "reach level X".

  • [Outfit 7] [💎 @01:21:14] You can get good results optimizing for "watch X rewarded videos" events. To do this you want to know the % of users reaching these kind of events, how fast they are reaching these events and how these events correlate with being a higher quality user.
  • [Outfit 7] These events differ from product to product and there will be trial and error but these kinds of events allow you to bid higher and reach pockets of users you were not targeting before.

Changed anything in the game during covid?

  • [Nordeus] Tried to be user focused and therefore gave more things inside the game: live events, special sponsoring, etc.
  • [Outfit 7] No big shifts in the game but big shifts in monetization (advertisers pulling out) but also decreased cost on the advertising side as well.

CPI decrease with LTV constant: depended on channel?

  • [Nordeus] Was true for most channels
  • [Outfit 7] Also have seen LTV decrease a bit but ROI/bottom line actually improved.