Think like an app marketer

Once upon a time I used to be a traffic director. 

Not a guy wearing a uniform and white gloves, blowing into a whistle while directing cars, but rather a guy whose single goal in the company was to generate a steady pace of quality registrations to the service. 

I had a huge budget, a large team of professionals and a tough target. 

There is one thing I can say for certain about that role – you could be the best at what you do, but without trustworthy data, you might as well throw bags of money out the window. 

Last week, some of us at SOOMLA discussed what insights and KPIs marketers need to rely on and how it impacts their decision-making process.
Let’s start with the head honcho of KPIs – Lifetime Value.  

Q3 2019 MONETIZATION BENCHMARKS

LTV is King

For those of you who still don’t know, a user’s lifetime value (LTV) is the entire amount of revenue a user generated during the activity from the day he/she started using the app until the day he/she ceased doing so. Without a doubt, this is the strongest KPI for an app. Without knowing the LTV, a marketer can’t measure the performance of the acquisition process properly.

The core blocks of LTV

LTV is made of two parameters – ARPDAU and Lifetime days. 
ARPDAU (average revenue per daily active user) is the total revenue for a single day divided by the number of users. 

Lifetime days is the average number of days a user is active in the app. This metric can be estimated by using various retention rates (D1, D7, D14, D30).

LTV – Typical Chart

The LTV chart has some distinct characteristics:

  • Fast climbing (as retention is high in the first days)
  • Trend tends to level out to a plateau after seven days as many users churn
  • App marketers often look at the first few days as an indicator for future performance

The CPI perspective

I’m not going into explaining what CPI is (look it up!) however, it is interesting to note that when publishers purchase media using the CPC model, they align the cost data with the conversion rate to determine the CPI. When publishers buy media using the CPM model, they check the click through and conversion rates to determine the IPM (instralls per mille) which can then be used to calculate the eCPI. 

The bottom line

After the user decides to quit the game, you can show him a full-size ad one more time.

Return on investment (ROI) is that every marketer should strive for, that’s why ROAS (return on advertising spend) is usually the more correct term to use when being a marketer. 

Reaching a positive ROI is simply a matter of LTV>CPI. 

Most app marketers don’t ask if the app is going to be ROI positive but rather ask when the ROI is likely to turn out to be positive. 

In many cases positive ROI only happens later on down the line rather than closer to the release date.

Q3 2019 MONETIZATION BENCHMARKS

The app marketer’s dilemma – test yourself

Even though this one isn’t available on iOS, it’s still worthy of consideration. The game can send push notifications to the players, and you can use it to promote your other games.

Take a look at the table below. 

Let’s say you are an app marketer and your D7 ROI goal is 20% while the D30 ROI target is 30%.

Can you calculate the metric in place of the question mark?

UsersCPIInstallsSpendD7 LTVD30 LTVD7 ROID30 ROILTV
Existing$000N/AN/A$1.57
New$040,0000N/AN/A
New
paid
users
$1.4210,000?
Total50,000$0.31$0.47$1.57

If the CPI and install metrics exist, the CPI can then be easily calculated by multiplying the two.

UsersCPIInstallsSpendD7 LTVD30 LTVD7 ROID30 ROILTV
Existing$000N/AN/A$1.57
New$040,0000N/AN/A
New
paid
users
$1.4210,000$14,200
Total50,000$0.31$0.47$1.57

Now let’s take a detour from the table and look into one of the most important parameters for publishers who display ads in their apps:

Q2 2019 AD LTV BENCHMARKS

Ad LTV

Ad LTV is simply the ad revenue component of the LTV (excluding IAPs and subscriptions).Being able to know one’s Ad LTV is not an easy task (though we at SOOMLA figured it out – read our recent report here) as the data needs to be compiled from multiple providers which usually avoid sharing this data.
Most of the Ad LTV data is generated by user installs.
Users who tend to react to ads and typically install apps are called Ad Whales – which are the equivalent of payers for ad monetized apps.

Let’s get back to the table. 
With the numbers added to the LTV columns, are you able to calculate the D7 ROI for new paid users and following that, can you then calculate the LTV? 

UsersCPIInstallsSpendD7 LTVD30 LTVD7 ROID30 ROILTV
Existing$000$0.31$0.47N/AN/A$1.57
New$040,0000$0.25$0.43N/AN/A?
New
paid
users
$1.4210,000$14,200$0.42$0.59???
Total50,000$0.31$0.47$1.57

For the D7 ROI, you’d need to divide the D7 LTV from the CPI so you should reach 29.5%.
Same logic applies for D30 ROI, so you should end up reaching a result of 41.5%.
Calculating the overall ad LTV is a bit more tricky but can be estimated by keeping the ratio between the Existing users LTV to the D30 LTV ($1.57/$0.47) and implementing it to calculate the expected New organic ($1.43) and New Paid ($1.97) LTV. 

UsersCPIInstallsSpendD7 LTVD30 LTVD7 ROID30 ROILTV
Existing$000$0.31$0.47N/AN/A$1.57
New$040,0000$0.25$0.43N/AN/A$1.43
New
paid
users
$1.4210,000$14,200$0.42$0.5930%42%$1.97
Total50,000$0.31$0.47$1.57

If this is the case, should we continue marketing? 
I’ll leave that up to you to decide (as long have ROI in mind).

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