Taking the guesswork out of paid user acquisition

A simple tool to estimate the right budget to grow your audience

Developers often want to know whether they should spend money on user acquisition, and what the key factors are to help inform their decision.

There are many useful tools and models to help with this question. After working closely with our key partners in South East Asia, Australia, and New Zealand, and spending many hours testing, my team created a simple but useful calculator to help you answer this question.

First, I’ll describe the inputs you need to use the calculator and explain how the results can help developers make better-informed decisions about paid user acquisition. I’ll also share an example of how one developer used this lifetime value (LTV) calculator and generated significant value for their business.

Before I continue, however, a word of caution. This LTV calculator — or indeed any LTV calculator — is simply a guide to assist in making decisions about paid user acquisition. It helps you predict the LTV you’ll see from acquired users and therefore what spend is sensible to achieve this return. The model makes assumptions about the impact of investment, CPI, organic spin-offs, payer rate, engagement rate, and portfolio effect. These assumptions aren’t guaranteed or confirmed. Additionally, estimates of buyer rate, ARPPU, and advertising revenue per user will need to be set based on your app’s data. Where I can, I’ll show you where to find those numbers.

OK, so that keeps the folks in the legal department happy, just one more note before we jump into the real details. The calculator uses US ($USD) as the default currency, but you can easily substitute your local currency. The important thing to remember is to make sure all the data you use is specific to the country or region you want to target and relevant to your app and its type or genre. It may seem obvious, but don’t use US figures for a casual game to plan a campaign for a messaging app targeting India.

As you read the next section, you might want to download the LTV Calculator to see how it uses these inputs. You’ll notice that the download includes the option to request a member of the app marketing team to contact you. This team’s job is to help app developers create and execute online marketing strategies and can help you determine the best values to use in the calculator.

LTV calculator inputs

Investment: This is how much to spend on user acquisition. If you plan to use universal app campaigns, start with a daily budget 50-times your target CPI. This level of investment will help AdWords’ machine learning algorithms optimize. So, with a $2.50 CPI target your daily budget would be $125 or approximately $3.7k per month. Another way to view investment is to set it so that you acquire a statistically relevant sample size, enabling you to understand user engagement and LTV with confidence, the goal should be approximately 5000 users.

Cost Per Install (CPI): This is the cost of generating one install. Note that CPIs vary by country as well as app and game genre or category.

Organic spin-off (K-factor): Studies have shown that paid installs can boost organic installs (organic growth) because of spillover from word of mouth and social sharing as well as installs from any listing in a store top apps chart. The K-factor measures the number of organic installs generated by each paid install, with 0 indicating that paid installs generate no additional organic installs.

Buyer rate: The percentage of the user base that makes in-app purchases. You can find the rate from your Play Console: Select your app, open User Acquisition, click on Acquisition reports, and select Buyers.

Buyer rate multiple: This variable represents the multiple by which users from a paid acquisition campaign become payers compared to users acquired organically. To illustrate, if 1% of organic users made purchases in the app while 2% of paid users made purchases, the buyer rate multiple is 2. Well targeted acquisition should achieve a multiple greater than 1 while more generic, mass-market targeting may result in a multiple of less than 1.

Average Revenue Per Paying User (ARPPU): This is the average of the revenue expected from each user who makes at least one purchase between their first and last use of the app. You can find the rate for your app from the Play Console revenue and buyer data reports: Select your app, open Financial Reports, and on the Buyers page select ARPPU.

Average advertising revenue per user: This is the revenue you generate from showing ads to a user over their lifetime and should include revenue from rewarded and non-rewarded ads. Remember, in line with the other figures you’re using, to include ad revenue from the country or region you are running the model for. The ‘Ad Revenue Calculation’ section of the model is designed to help you calculate this value. To get started, you’ll need to access your advertising dashboard: find the total ad revenue generated for a month and divide it by the number of active users in that month. You then need your retention figures for day 1, 7, 14, 28, 60, and 90; these can be found using a third-party analytics tool or Google Analytics for Firebase. The model uses the 90-day value, but you can substitute the 28-day or 60-day values, if you want to be conservative in your calculations.

Engagement rate multiplier: This multiplier reflects how much more engaged users acquired from paid installs are compared to users acquired organically. To illustrate, if users acquired from a paid campaign stick around longer, that is they show improved retention, you could expect to see a higher multiple. Well targeted acquisition should achieve a multiple greater than 1 while more generic, mass-market targeting may result in a multiple less than 1.

Portfolio effect multiple: If you’ve a portfolio of apps, that is, more than 1 app, a paid install may generate additional value by driving the installation and generation of revenue from other apps in the portfolio. Use of tools, such as house ads, would help maximize this multiple.

Using the LTV calculator

Once you’ve gathered the numbers relevant to your app and the region you’re going to promote it in, plug them into the calculator. In my example, I’m working with a campaign investment of US$5,000, have a K-factor of 2, buyer rate multiple of 1.5, and engagement multiple of 1.3, but no portfolio multiple. The ARPPU and ad revenue figures I pulled from the Play Console.

Example figures plugged into the LTV calculator.

In this example, return of advertising spend (ROAS) is over 100% so a paid acquisition campaign should have a positive return.

And the result? I can see that a paid campaign alone won’t deliver a positive return. However, organic spin-off will pick up additional users and revenue that lifts the return on advertising spend (ROAS) to a healthy 110%.

In general, using the calculator as a decision-making tool is simple. If ROAS is over 100% you should return a profit from a paid acquisition campaign. Less than 100% and you probably won’t see a benefit. In the example, we have a ROAS of 110% so it makes sense to go ahead with a campaign.

However, even if the calculator returns a positive result — unless you’ve been testing extensively to determine your organic spin-off and other multiples — it’s worth running a test campaign to confirm your assumptions.

If the calculator says that paid acquisition isn’t worthwhile, you can adjust the CPI to find the level that offers a return. However, rather than chasing a lower CPI, you may be better served by looking to improve your app’s fundamentals, such as retention, monetization, and social functionality (virality). Once these metrics have improved, look again at the value of a paid acquisition campaign.

The LTV calculator in action

Not Doppler, an Australian games developer, used the LTV calculator to decide whether paid user acquisition made sense for Crash of Cars.

The calculator provided Not Doppler with a clear understanding of the total revenue (both from ads and in-app purchases) they generated from a user over their lifetime engagement with Crash of Cars. While the calculator aims to answer the question of whether paid user acquisition is likely to be beneficial, for Not Doppler it also dispelled several misconceptions.

Misconception 1: User acquisition is expensive

“High CPIs had been an initial barrier to entry for us, given we questioned the feasibility of UA with our ad-heavy business model. Through education and controlled testing we were able to profitably acquire a substantial volume of users in the US at CPIs of less than US$1.” — Jason Daskalopoulos, Senior Business & Marketing Manager, Not Doppler

Misconception 2: All users are equal

When Not Doppler ran paid (non-incentivized) campaigns they saw a higher quality of user compared to their organic acquisitions.

We saw that the paid pre-qualified users who installed and opened Crash of Cars via an ad were 1.8-times more likely to spend in the game versus those who came in organically.”- Jason Daskalopoulos, Senior Business & Marketing Manager, Not Doppler

Misconception 3: Calculating ad revenue LTV

With in-app advertising playing a significant role in Not Doppler’s monetization strategy, it was important that they correctly calculated the average revenue generated per user over their lifetime.

The Model allowed us to better understand the ad revenue we generated from showing users ads in our game over their lifetime. By looking at the relationship between ad revenue per daily active users and retention in the US we were able to calculate the revenue we generated from ads over a 30, 60, and 90 day period.” — Jason Daskalopoulos, Senior Business & Marketing Manager, Not Doppler

Misconception 4: Organic spin-off

Soft launching Crash of Cars allowed Not Doppler to calculate the effect of organic spin-off (K-factor) from the game. Interestingly, Not Doppler made a deliberate effort to avoid Crash of Cars appearing in the store top charts and generating organic installs from there. This was because they wanted to discover what percent of additional installs were generated by paid traffic through social sharing, word-of-mouth, or other forms of user driven, unpaid promotion.

Through controlled testing we were able to measure the incremental lift we gained in organic users through paid marketing.” — Jason Daskalopoulos, Senior Business & Marketing Manager, Not Doppler

Try it yourself

Wondering what all this might mean for your user acquisition? There is a simple way to find out, download the LTV Calculator and plug in your app’s numbers! If you’d like to find out more about paid user acquisition or have any further questions about the blog or model, use the “I would like the app marketing team to contact me” option when downloading the LTV calculator and someone from my team will get in touch.

New to using ads to promote your app?

If you haven’t advertised your app or game before, we provide a simple way to get started with Google AdWords’ universal app campaigns. You can set up a universal app campaign in the Google Play Console in a few clicks. Google automatically optimizes your campaign to find users who are most likely to install your app at your target cost per install across Google’s networks including Google Play, Search, YouTube, and the Google Display Network. When you fill in the form for the lifetime value calculator, tick the box if you want to hear from an AdWords expert about setting up and running universal app campaigns for your app.


What do you think?

Do you have any comments on calculating LTV? Continue the discussion in the comments below or tweet using the hashtag #AskPlayDev and we’ll reply from @GooglePlayDev, where we regularly share news and tips on how to be successful on Google Play.