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9 User Acquisition Metrics Marketers Need to Know

Jun 28, 2023
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Tracking user acquisition metrics is critical for any performance marketer. Discover the KPIs you need to monitor to achieve your marketing goals.

Learn how to measure cost per acquisition, customer lifetime value, retention rate, and more

Performance marketing can seem complex, but it can yield remarkable results. Success requires a keen understanding of how users engage with your product, as well as an analytical mind capable of driving growth while minimizing costs. Understanding the essential user acquisition metrics that underpin that balance will help you make smarter ad budget decisions, improve campaign performance, and maximize your return on ad spend. 

 

9 User Acquisition Metrics Marketers Need to Know

Cost Per Install

Cost per install measures how much ad spend it takes to get one user to download and install your app. It’s often abbreviated to, and has long been one of the most crucial customer acquisition metrics marketers should know. Its importance has come under scrutiny as more comprehensive metrics vie for the north-star position. Metrics like return on ad spend and stickiness have gained popularity as marketers take greater accountability, and shift focus towards maximizing lifetime value. Still, it’s crucial to understand your CPI rates as a constituent part of overall performance.

How to calculate CPI: Cost per install is calculated by dividing the total number of installs by the total advertising spend. 

 

Cost Per Install = Total Ad Campaign Spend / Total App Installs During Campaign

 

Cost Per Acquisition

Cost per acquisition measures how much money it takes to gain a new customer, whether that’s a new user for your mobile game, a purchase on your website, or a signup for a monthly subscription plan. It’s typically shortened to CPA and is one of the most fundamental user acquisition metrics performance marketers use and is the foundation for minimizing advertising costs while maximizing your potential revenue. Plus, CPA can help you get a better sense of your users’ overall lifetime value.

How to calculate CPA: Like CPI, cost per acquisition can be calculated by dividing your total advertising spend by the total number of tracked acquisitions:

 

Cost Per Acquisition = Total Advertising Spend / Total Number of Acquisitions

 

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Customer Lifetime Value

This KPI measures the total revenue a single customer or user generates throughout their relationship with your company or product. This value can represent the revenue generated over time from a combination of product purchases, monthly subscriptions, ad revenue, and other sources of profit. It's commonly known as CLTV, but can be shortened to just LTV.

Marketers need to ensure that the lifetime value your customers provide is greater than the cost of acquiring and maintaining that relationship before their time in the product life cycle is complete. Figuring out the lifetime value of your customer base will help you inform your overall marketing efforts and the amount you spend on them, as well as identify whether your retention strategies need to be adjusted to maximize revenue.

How to calculate CLTV: Figuring out customer lifetime value requires a few preparatory steps.

 

First, you need to determine your customer value. This is represented by the following formula:

 

Customer Value = (Average Purchase Value x Average Number of Purchases)

 

To get the average purchase value, you divide your total revenue over a designated time period by the total number of purchases:

 

Average Purchase Value = Total Revenue / Number of Purchases

 

To get the average number of purchases, divide the total purchases by the total number of customers.

 

Average Number of Purchases = Total Purchases / Total Number of Customers

 

You’ll need one more value before we can determine the average LTV of your customers. Multiply the sum of all customer lifespans by the number of customers to get your average customer lifespan.

 

Average Customer Lifespan = Sum of Customer Lifespans / Number of Customers

 

Now, we can calculate the lifetime value by multiplying your customer value by the average customer lifespan.

 

Lifetime Value = Customer Value x Average Customer Lifespan

 

Return on Ad Spend

Return on ad spend is a metric designed to measure the direct relationship between money going out in the form of an ad campaign and revenue coming in as a result of that specific campaign. This is different from return on investment, which measures the overall profit generated by an entire project. Typically abbreviated to ROAS, this metric helps marketers determine whether their ad dollars directly lead to revenue generation. Where acquisition KPIs like cost per acquisition measure how effective advertising brings in users, ROAS determines how effective it is at bringing in money. 

How to calculate ROAS: Return on ad spend is calculated by dividing the total revenue generated as the result of a finite ad spend by the total cost of that ad spend.

 

Return on Ad Spend = Revenue Generated by Ads / Cost of Ads

 

With mobile app user acquisition, however, correctly attributing revenue to ad spend can be difficult due to factors such as recent privacy policy updates that make it more difficult to track user data. This is where mobile measurement partners (MMPs) like Singular, Appsflyer, and Tenjin come in. They act as an unbiased intermediary between you and your data, helping to accurately attribute which media source led to your desired activation.

Click-Through Rate

Click-through rate measures how many times people are clicking on (or otherwise engaging with) the ads you’re paying for. It’s measured as a percentage of the total ad impressions (when your ad is displayed to a potential customer) that result in the customer clicking on the ad.

Also known as: CTR

Why you need to know it: CTR is a helpful metric for determining how engaging your ads are. If users aren’t clicking on the ads you’re paying for, it may be time to reevaluate your approach and continue testing and optimization. CTR can vary wildly, depending on where you’re advertising or the keywords you’re targeting. Also, a low CTR isn’t necessarily a bad thing if those clicks ultimately lead to valuable conversions, whereas a high CTR without conversions means you’re spending money without the results to justify it.

How to calculate it: You can calculate your click-through rate with the following formula:

 

Click-Through Rate = Total Number of Clicks / Total Ad Impressions

 

Conversion Rate

Conversion rate is similar to click-through rate, though it takes measurement one step further. Rather than merely determining the percentage of users who clicked on an ad, conversion rate measures the percentage of users who actually take action once the ad is clicked. Your conversion rate tells you the effectiveness of the sum of your campaign decisions — targeting, creative quality, and even your app’s onboarding experience — in mathematical terms. If you’re spending money on ads that aren’t leading to conversions, you need to examine where the disconnect is happening. 

How to calculate conversion rate: You can calculate your conversion rate by dividing your total number of conversions by the total number of clicks.

 

Conversion Rate = Total Number of Conversions / Total Number of Clicks

 

Incrementality

Incrementality is the measurement of how effective an ad campaign is at influencing conversion compared to organic traffic. With mobile user acquisition, it’s crucial to understand whether conversions are happening due to your paid advertising. Otherwise, you’re spending money on users who would have converted regardless of your efforts. This is where incrementality can help — by examining the effects of ad spend on your audience and comparing them to a control group that isn’t exposed to ads, you can determine the kind of impact your campaign actually makes on your user acquisition efforts.

How to calculate incrementality: To calculate incrementality, you need two groups: a test group that sees your ad and a control group that doesn’t. Once you’ve run your campaign, you can perform the following calculation:

 

Incrementality = (Test Group Results - Control Group Results) / Test Group Results

 

For example, if your test group sees 125 installs while your control group only sees 100 installs, you can subtract 125 by 100 to get 25. Divide that number by 125, and you’ll get 0.2, or a 20% incrementality rate.

Retention Rate

Retention is essentially the opposite of churn rate — instead of calculating how many customers are leaving, you’re figuring out what percentage of customers are sticking around during a set time. Determining the growth of your business requires three key data points: how many new customers are joining, how many current customers are staying, and how many old customers are leaving. If you can keep your existing customers happy and prevent them from leaving while also continuing to bring in new business, congratulations — your business is growing. This metric will help you determine how successful your retention efforts are and whether you can keep more customers than you lose.

How to calculate retention: Before calculating your retention, you need to determine what your Day 0 value is — that is, the number of people who use your app on the first day of measurement. 

Then, you need to choose which retention calculation you want to make. There are a few ways to measure retention, and each one comes with its own strengths and weaknesses.

First, there’s classic retention. It’s easy to calculate but is susceptible to day-to-day noise (such as holidays or unusual spikes in usage). Calculate classic retention with the following formula:

 

Classic Retention Rate = Number of Users Who Return to the App on a Day after Day 0 / Number of Users Who First Opened Your App on Day 0

 

For example, if 20 people open your app on Day 0, and eight of those users come back on Day 5, your Day 5 retention rate is 8/20, or 40%

Then there’s range retention, which is helpful for discovering how many users return within a specific time period. This can help you detect trends and remove some of the noise from your calculation, but is also less granular than other measurements. You can calculate range retention with the following formula:

 

Range Retention Rate =  Number of Users Who Return to the App During a Following Interval of the Same Range / Number of Users Who Open the App During an Initial Range of Time

 

Say you want to measure a 7-Day Range Retention Rate. First, you measure how many users open your app during the first seven days — in this case, we’ll say 50. Then, you measure how many of those users return in the following seven days. If 35 users return the following week, we can divide 35/50 for a 7-Day Range Retention Rate of 70%. 

Last, you can measure rolling retention, which can tell you how many users are coming back after a set amount of time. It’s the quickest to measure and will help give you an idea of how “sticky” your app is, but numbers can constantly change based on when you’re calculating. Calculate rolling retention with the following formula:

 

Rolling Retention Rate = Number of Returning Users Who Open Your App On or After a Specific Day / Number of Users on Day 0

 

For example, if 10 users visit on Day 0, three return on Day 7, two different users return on Day 9, and one more unique user returns on Day 10, your Day 7 Rolling Retention rate is 6/10, or 60%. 

Stickiness

Like rolling retention, stickiness can help you determine how many of the users that you’ve acquired continue to return to your app. Unlike rolling retention, stickiness is tied to daily and monthly active users, providing a more specific macro-level view of how loyal your users are. Stickiness is becoming one of the most important metrics for maximizing the results of your user acquisition efforts. Knowing your app’s stickiness can tell you when to throttle your ad spend or by how much. And if you’re holding onto users longer, you can spend less on acquisition. 

How to calculate stickiness: All you need to calculate stickiness is your daily active users (DAU) and monthly active users (MAU):

 

Stickiness = Daily Active Users / Monthly Active Users

 

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