Glossary Categories: C

Churn Rate

The percentage rate at which customers stop subscribing to a service or employees leave a job.

What is Churn Rate?

Churn rate is a metric used to gauge the percentage of users who have disengaged from an app, either by ceasing to use it or uninstalling it. This term is interchangeable with “abandonment rate” and is the opposite of “app retention rate.”

Calculating the churn rate of an app is typically done on a daily, weekly, or monthly basis. To determine the churn rate, subtract the number of active users at the end of a given time period from the number of active users at the beginning of the same time period. Divide the resulting figure by the number of active users at the beginning of the time period.

How to Calculate Churn Rate:

Churn Rate = (Active Users at the Beginning – Active Users at the End) / Active Users at the Beginning

For example, if an app had 5,000 active users at the beginning of a 90-day period and 3,500 active users at the end of the same time period, the churn rate would be calculated as follows:

Churn Rate = (5000 – 3500) / 5000 = 0.3 or 30%

Therefore, the churn rate for the app in this example would be 30%.

Churn Rate: Understanding Customer Disengagement in Mobile Apps

Churn rate, often referred to as the rate of attrition, signifies the speed at which customers cease utilizing a product or service. In the realm of mobile applications, it specifically denotes the pace at which users disengage from an app, be it through uninstallation, subscription cancellation, or passive neglect. This disengagement can stem from user dissatisfaction, migration to competitors, or financial constraints. High churn rates pose significant threats to a business’s profitability and impede its growth. Hence, prioritizing efforts to minimize churn and enhance user retention becomes imperative for sustainable expansion and financial prosperity.

Churn Rate vs. Retention Rate: A Comparative Analysis

Churn rate quantifies the percentage of users lost within a defined timeframe, whereas retention rate gauges the portion of existing customers who persist in using an app. For example, if a mobile app commences a month with 1,000 users and loses 200 by month-end, the churn rate for that period stands at 20%, while the retention rate equals 80%. These metrics are pivotal in evaluating customer satisfaction and business viability, often serving as key performance indicators (KPIs) for app companies.

Significance of Churn Rate: A Holistic View

Understanding churn rate is instrumental in assessing customer satisfaction and business health. It offers insights into user departure reasons, enabling businesses to gauge their app’s stickiness. Moreover, churn rate analysis provides valuable data for calculating customer lifetime value (LTV) and determining the budget for customer acquisition. The LTV-to-customer acquisition cost (CAC) ratio serves as a barometer for spending efficiency, with a balanced ratio indicating profitability. Monitoring churn is crucial for multiple reasons, including cost-effective customer retention, ensuring product-market fit, and maximizing customer lifetime value to justify higher user acquisition expenditures.

Calculating Churn Rate: A Methodical Approach

Regularly measuring an app’s churn rate facilitates the tracking and enhancement of user satisfaction and engagement. Calculations can be performed monthly or annually, offering valuable insights into month-to-month and year-over-year growth trends. Monthly churn rate quantifies user loss within a month, exemplified by a scenario where an app starts with 10,000 users and ends with 8,500, resulting in a 15% monthly churn rate. Conversely, annual churn rate analyzes yearly user loss, exemplified by a reduction from 50,500 to 45,000 users, yielding a 10.89% annual churn rate.

Determining an Optimal Churn Rate

While attaining a zero churn rate is ideal, it is practically unachievable. On average, apps lose 77% of their daily active users within the first three days post-installation. An acceptable annual churn rate typically falls between 4% and 7%, yet industry-specific benchmarks vary. Therefore, defining a “good” churn rate necessitates alignment with specific goals and adherence to industry standards.

Analyzing Churn Reasons

Understanding why users churn requires meticulous examination of data patterns, especially focusing on retention trends during the initial days, weeks, and months. Identifying spikes in uninstall data aids in pinpointing specific disengagement points, such as app bugs, limited core features access, or inadequate onboarding processes. Evaluating communication strategies, including customer support interactions and timely, relevant messaging, contributes to re-engagement efforts and retention.

Strategies for Churn Reduction

• Cohort Analysis: Utilizing cohort analysis aids in understanding user behavior by categorizing them based on acquisition channels, user actions, and timeframes. This segmentation enables businesses to identify critical moments in the user journey, facilitating targeted actions to enhance engagement.
• Optimized Onboarding: Implementing a user-friendly onboarding process simplifies app usage, reducing the risk of early churn. Streamlining the onboarding experience and minimizing steps ensure users swiftly comprehend the app’s features, fostering a sense of support and empowerment.
• Personalization: Personalized app experiences, tailored to user preferences and behavioral data, bolster engagement. Customizing interactions and messaging based on user actions, search history, and device preferences enhances user satisfaction and reduces churn.
• Re-engagement through Owned Media: Leveraging owned media channels, such as in-app messaging, push notifications, SMS, and email, enables proactive engagement. Triggered reminders and personalized content encourage repeat visits, showcasing the app’s value to users.
• Deep Linking: Implementing deep linking directs users to specific in-app locations, enhancing user experience. This feature enables seamless re-engagement by guiding users directly to relevant points within the app, eliminating manual navigation barriers.
• Addressing Churn Causes: Close scrutiny of app data helps identify specific points of user disengagement. Analyzing user drop-off locations and rectifying issues, such as app malfunctions or overwhelming tutorials, ensures a smoother user experience, reducing churn.

Navigating Churn for Sustainable Growth

In summary, understanding and mitigating churn rate are indispensable endeavors for app businesses seeking sustainable growth and enhanced profitability. By adopting strategic measures, including cohort analysis, optimized onboarding, personalization, re-engagement efforts, deep linking, and data-driven issue resolution, businesses can effectively combat churn, ensuring enduring user satisfaction and prolonged app engagement.

Clearing Price

The final price paid for an impression.

Click Flooding

Click Flooding

Click flooding, categorized as mobile ad fraud, occurs when networks deliberately generate a substantial volume of deceitful clicks. This strategy aims to attribute the last click just before an app installation takes place. By doing so, these networks seek to claim full credit for the conversion.

Click Flooding Explained

Click flooding, sometimes referred to as click spamming, constitutes a variant of click fraud. This deceptive practice involves malicious entities orchestrating the dissemination of a large number of counterfeit click reports. Their goal is to secure credit for the concluding click prior to app installations. This not only allows them to reap rewards from advertisers but also wreaks havoc on marketing budgets.

How Click Flooding Works

How exactly does click flooding operate? Fraudulent actors manipulate click attribution by fabricating clicks on behalf of users who did not initiate them. This enables them to lay claim to fabricated clicks, positioning themselves for unwarranted gains.

A fraudulent application might execute these counterfeit clicks while the user is actively engaged with it or even when it’s running in the background (such as battery-saving apps or launchers). These apps might even convert impressions into clicks, offering up deceptive engagement metrics, all without the user’s awareness or intention.

How to Prevent Click Flooding Fraud

Countering click flooding fraud is achievable through anti-fraud solutions designed to automatically thwart traffic stemming from sources involved in click flooding.

In order to identify the origins behind a click flooding assault, these solutions scrutinize traffic patterns characterized by prolonged Click-To-Install Time (CTIT) distributions, diminished click-to-install conversion ratios, and/or elevated rates of multi-touch contribution (note: this necessitates access to multi-touch attribution data).

A valuable yardstick when assessing one’s data is that approximately 75% of installations materialize within the first hour following a click, with around 94% of installs taking place within 24 hours of the initial click.

It’s important to note that video ads and larger applications often exhibit extended CTIT durations.

Click Injection

What is Click Injection?

Click injection is a sophisticated form of click-spamming. By publishing (or having access to) an Android app that listens to “install broadcasts,” fraudsters detect when other apps are downloaded and trigger clicks before an install completes. The fraudster then receives credit for installs as a consequence. If fraud prevention tools are inadequate, individuals who commit click injection fraud can take advantage of a low-quality app to take control of a device at a strategic moment (and with the necessary data) in order to produce a false advertisement click that looks genuine, causing payouts based on cost per install (CPI).

How does click injection work?

The click injection technique is often employed by fraudulent actors through the use of “junk apps” installed on a user’s device. These apps lay dormant until an installation broadcast activates them, allowing them to take control of the user’s device and generate false clicks that steal credit for organic or non-organic installs generated by other networks.

Aside from the financial damage caused by draining advertising budgets, click injection can have serious implications for advertisers’ future targeting and segmentation of traffic. It can distort the planning and distribution of ad spend by highlighting fraudulent sources ahead of legitimate ones.

Click to Install Time (CTIT)

What is Click to Install Time (CTIT)?

Introduction to Click to Install Time (CTIT)

Click to Install Time, abbreviated as CTIT, refers to the time interval between a user clicking on an advertisement and the subsequent opening of an application. This metric holds significant value as it plays a crucial role in identifying and thwarting instances of mobile ad fraud perpetrated by malicious entities seeking to fabricate final clicks.

Defining CTIT

CTIT constitutes a form of distribution modeling utilized in the identification of two distinct forms of ad fraud: install hijacking and click flooding.

Install Hijacking CTIT Analysis

In the case of install hijacking, CTIT analysis is primarily focused on detecting patterns where a substantial number of installations occur within the initial 3 to 10 seconds after the initial click.

Click-Flooding CTIT Analysis

Conversely, when dealing with click flooding, CTIT analysis aims to uncover an almost uniform distribution pattern occurring on a larger scale. This pattern is observed between the 2nd and 24th hours, as well as between the 2nd and 7th days following the installation.

Why is CTIT Important?

CTIT holds fundamental importance in the detection and tracing of fraud. It stands as a primary and crucial metric to assess when scrutinizing potential fraudulent endeavors within your web traffic.

Click Spam

Also known as organics poaching, click spam is a type of advertising fraud that happens when a fraudster executes clicks for users who haven’t made them. Unless preventative measures are in place, this allows fraudsters to claim credit for fake clicks.

What is Click Spamming?

Click spamming, also known as click flooding, is a form of mobile ad fraud wherein networks generate a substantial volume of fake clicks in an attempt to receive credit for the last click before a conversion, such as an app installation. This malicious activity aims to deceive advertisers into paying for fraudulent clicks, thereby causing significant financial losses.

To carry out click spamming, fraudsters send a massive amount of clicks to a Mobile Measurement Partner (MMP). The high volume of clicks increases the probability of misattribution by the MMP, resulting in the fraudsters receiving payouts for their illegitimate activities.

Apart from robbing advertisers of their marketing budgets, click spamming also has the potential to distort or skew the advertiser’s marketing data. This can cause marketers to increase their budgets for these networks, even though they are not generating any real clicks, users, or conversions. Hence, it’s critical to implement robust fraud prevention measures to mitigate the risk of click spamming and other fraudulent activities in the mobile ad ecosystem.

What are the uses of Click Spamming?

Click spamming is a fraudulent practice that involves generating fake clicks in various ways, such as using a fraudulent app that executes clicks in the background of a user’s mobile device without their knowledge or consent. By claiming credit for these fraudulent clicks, the fraudsters aim to deceive advertisers and steal their marketing budgets.

Click Spam Example

A user downloads a fraudulent app, which may appear to be a legitimate utility app, game, or other type of mobile app. The app has code that runs in the background, generating spam clicks on ads without the user’s knowledge. The clicks are then attributed to the developer of the fraudulent app, who can then receive payment for the clicks.

This example highlights the negative consequences of click spamming, such as reduced battery life for the user and distorted marketing data for advertisers. Moreover, click spamming techniques are becoming increasingly sophisticated, with fraudsters targeting specific users who are more likely to engage with the fraudulent ads.

To combat click spamming, advertisers and Mobile Measurement Partners (MMPs) are implementing advanced fraud prevention techniques to ensure that their advertising budgets are spent on legitimate users and driving real conversions. As click spamming continues to pose a growing threat, it’s crucial for businesses to remain vigilant and adopt robust fraud prevention strategies to protect their marketing investments.

How to Prevent Click Spam?

Detecting and stopping click spam requires careful monitoring and analysis of data. One approach is to analyze traffic and conversions, as fraudulent activity often leads to sudden spikes in clicks without corresponding conversions. Suspicious sources, such as mobile apps or websites, should be isolated and removed, and further investigation should be conducted to determine the cause of the problem.

Another method involves analyzing publisher analytics to identify patterns and click distributions that indicate the presence of fake clicks. Unusual patterns can be detected and avoided in the future to prevent similar fraudulent activity from occurring again.

Validating apps before using them in advertising campaigns is also recommended, as this can help detect and prevent malicious code from infiltrating an advertiser’s network. However, the validation process can be time-consuming, and not all developers are willing to share their code.

Taking a proactive approach to fighting click fraud involves investing in anti-fraud solutions that use sophisticated algorithms to detect and block fraudulent activity before it causes significant damage to an advertiser’s budget. Solutions that offer in-depth traffic and click analytics should be considered, as they can help identify suspicious activity and prevent it from occurring in the first place.

Finally, manually selecting ad networks and placements can be time-consuming, so investing in a technology stack that streamlines the process can be beneficial. This can help minimize the workload and automate tasks associated with managing advertising campaigns, ultimately leading to a more efficient and effective approach to preventing click spam.

Cohort Analysis

Cohort Analysis is a common and powerful methodology used by marketers to understand how different groups behave over the long-term.

What is Cohort Analysis? 

Cohort analysis is a method used to analyze the behavior of a particular group of customers over time. In this approach, cohorts are created as unchanging groups, where no new customers join a cohort once it’s formed, and customers cannot move from one cohort to another.

The most common type of cohort is the group of customers who became part of the business in a specific time frame, such as the second week of January or the fourth quarter of the year. Also known as “static pool analysis,” cohort analysis tracks the behavior of these specific, fixed customer groups over time, as they move along the customer lifecycle curve.

How do Marketers use Cohort Analysis?

Cohort analysis is useful for identifying trends within customer behavior that may be hidden when looking at more general analytics data. For example, overall analytics data may show an increasing number of monthly purchases, which seems like a positive sign for the business. However, cohort analysis may reveal that the higher overall percentage is due to many first-time buyers, while cohorts of older customers are actually returning to make purchases much less frequently than in the past. Therefore, following the behavior of particular cohorts over time provides a more accurate view of business performance.

When a company experiences a “bad month,” it’s essential to understand if the unexpected performance drop was due to a market-wide factor or a specific problem that might be identified and adjusted. For example, if most new customers in a particular month spent much less than the customers acquired in previous months, it would be wise to examine any changes in acquisition strategy and identify under-performers.

Advanced Cohort Analysis

Sophisticated cohort analysis involves tracking the longer-term impact of a particular marketing action on a group of customers who were treated with that marketing action. By creating a cohort of this customer group and tracking its behavior over time, the marketer can achieve much deeper insight into the long-term effects of a particular marketing action.

Another advanced use of cohort analysis is combining cohort analysis with behavior-based customer micro-segmentation. This involves defining a cohort of customers who exhibit certain behaviors, such as high spending on a particular product over a specific period, and spotting trends among this specific group of customers to gain insights into customer acquisition, uplift marketing, and customer retention.

Conversion Rate

The percentage of users who have completed the desired action known as the conversion. The formula for conversion is as follows: you take the number of conversions and divide that by the number of total ad interactions during the same time period (that can be tracked to the conversion).

What is a Conversion Rate?

Conversion rate refers to the percentage of viewers who take a desired action, such as registering for an event, making a purchase, or clicking a link. This metric is used to measure the effectiveness of a campaign or content. The higher the conversion rate, the more successful the campaign is considered. Average conversion rates vary by industry, but typically range in the low single digits, such as 2% for app downloads leading to a purchase. A small change in the conversion rate can have a significant impact.

The importance of conversion rate

Conversion rate is crucial because it indicates how effective a page or content is in achieving its marketing objectives. While metrics like page views or impressions are informative, they do not provide insight into whether the content is achieving its purpose of driving users to act. For example, a good click-through rate (CTR) for a digital ad campaign may indicate that the ad is grabbing people’s attention, but if few people download the app, the campaign is not performing as it should. By tracking conversion rates, marketers can identify weaknesses in their marketing funnel and improve their landing pages or promotional offers.

How to calculate conversion rate?

Conversion rates can be calculated by dividing the number of conversions by the number of interactions with the content and multiplying by 100 to get a percentage. Many analytics platforms, such as Google Analytics, automatically calculate conversion rates once goals are set up. For example, a landing page with 1,000 views and 25 resulting purchases would have a conversion rate of 2.5% (25/1,000 = 0.025 or 2.5%).

Conversion rate factors 

When it comes to online buying decisions, users are faced with a complex array of factors to consider. From product compatibility to pricing and company trustworthiness, there are multiple objections that must be overcome in a very limited time window. In order to increase conversion rates, it is essential to not only showcase the value of your product or service through messaging and imagery, but also to create a seamless user experience with a strong call to action.

There are several factors that can impact conversion rates, including page load time, page design, differentiation, pricing and offer, and the call to action message. Ensuring that your website or landing page loads quickly is essential, as research shows that slow loading times can lead to user disinterest and a lack of trust. A well-designed website with a mobile-friendly interface and optimized content can also improve conversion rates, and differentiation strategies can help your offering stand out among competitors.

Pricing and offers are also important factors to consider, as users may be turned off by high prices or unappealing promotions. By benchmarking your pricing against competitors and offering special deals or limited-time promotions, you can create a sense of urgency and incentivize users to convert.

Perhaps most important of all is the call to action message. Effective messaging should prompt users to take action and provide a clear next step. It is important to choose the right words to convey the value of taking action, and to test different CTA messages to find what works best. By following these best practices and continually testing and refining your approach, you can improve your conversion rates and achieve greater success in your online marketing efforts.

How to Optimize and Improve Conversion Rate

1. Measure the Right Action To optimize your conversion rate, you need to ensure that you are measuring the right action. For bottom-of-the-funnel content, the goal is typically to complete a purchase. However, for top- or middle-of-the-funnel content, you may want to measure lead generation and nurturing conversions instead. Examples include downloading a resource, subscribing to a newsletter, or following your social media page. Once you have added someone to your email list, you can measure conversions according to your next goal, such as signing up for a free trial.
2. Avoid Asking for Too Much Information Lengthy lead generation forms can cause people to abandon them before completing them. Consumers abandon nearly 70% of eCommerce shopping carts due to cumbersome checkout processes. To avoid this, keep the checkout process short and sweet. Customers abandon conversions when they feel that the time investment or experience outweighs the benefit they anticipate.
3. Provide Enough Information Customers need to clearly see the value before taking the next step. You can accomplish this by listing tangible and intangible benefits, showing multiple images, videos, and product details, and offering social proof such as customer reviews, industry awards, or media coverage. Be clear about your privacy policy if you are asking for personal information. Consider using the word “free” in your CTA or other reassurances to help people feel more comfortable taking advantage of an offer.
4. Localize Your Content It’s essential to localize your content if you have a global audience, especially if you’re running paid campaigns in multiple countries. Localize your messaging to account for language, dialect differences, and cultural references. Creating country-specific web pages and app listings can help you accomplish this. Localize your images to ensure they resonate with the demographic you’re talking to, and ensure that the functional aspects of your conversion like currency, shipping, and product availability are localized upfront.
5. Sharpen Your Messaging If your ad is seeing good engagement but your conversion rate is lagging behind, take a closer look at your landing page content. Does it grab attention? Is the value of your offering clear? It’s smart to hire a professional copywriter or agency to optimize your page content. Use market research or A/B testing through dynamic content to uncover which message resonates best with your audience.
6. Create a Sense of Urgency Creating a sense of urgency makes people feel like they’re winning by saving money or getting something for free. Inversely, you create a sense of scarcity that they may miss out on something by not acting. Use phrases like “Claim your special offer by Dec 1” or “Register today to save $100” to create urgency. Even if you don’t have a discount or freebie to offer, you can still use this tactic by highlighting when inventory is low or by positioning value in a direct way.

CPC (Cost per click)

A pricing model in which advertisers pay the publisher each time a user clicks on their ad. It is calculated by dividing the cost of a paid advertising campaign by the number of clicks.

What is Cost Per Click (CPC)?

Cost per click (CPC) is a widely used term in paid advertising, where advertisers pay publishers for each click on an ad. Also known as pay per click (PPC), CPC is a key metric that helps advertisers determine the cost of displaying ads to users on search engines, social media platforms, and other publishers.

CPC plays a significant role in determining bidding strategies and conversion bidding types, helping businesses maximize clicks relative to their budget size and target keywords. Various types of ads, including text, rich-media, and social media ads, use CPC as a factor in calculating total paid advertising campaign costs. However, certain ad types are only displayed on specific networks, such as Google Search Network (ads at the top of Google’s search engine result pages) and Display Network (Google-owned or partnered sites like YouTube and Gmail).

Calculating CPC involves dividing the cost of a paid advertising campaign by the number of clicks received. Popular online advertising tools like Google AdWords often show CPC for target keywords. Other related metrics include average cost per click and maximum cost per click, with the latter referring to the highest amount an advertiser is willing to pay for a click.

Manual CPC bidding is an approach where advertisers set the maximum CPC for each ad by hand, while enhanced CPC is an automated conversion bidding strategy in Google AdWords used to maximize ad conversions for certain types of ads on Google’s Search and Display Network.

CPC has several advantages, including its ability to help businesses drive traffic to their sites or stores, improve paid advertising campaigns, determine the most effective ad types, and choose manual or automated bidding strategies based on their understanding of their business, audience, and paid advertising strategies.

In summary, CPC is a crucial metric for businesses looking to run effective online advertising campaigns. By understanding how CPC works and how to calculate it, businesses can optimize their advertising campaigns to generate more clicks and conversions, leading to increased revenue and growth.

CPA (Cost per acquisition/action)

A pricing model in which advertisers select a post-install action to measure and only pay if users engage in that action. For this action to be calculated, the user must see the ad, install the app, and perform the action. To calculate CPA, one must divide the advertising cost by the number of times the action occurs. For example, advertisers can provide a survey and once a user completes the survey, this can be calculated as an action.

What is Cost Per Acquisition (CPA)?

Cost per acquisition (CPA), alternatively referred to as cost per conversion, is a growth marketing key performance indicator (KPI) that quantifies the cumulative expenditure incurred by a user undertaking a task that results in a conversion. The conversion may involve various actions, including purchases, clicks, sign-ups, form submissions, or app downloads.

How to Calculate CPA?

The formula for computing CPA is the total advertising cost divided by the total number of conversions as follows:

CPA = Total Advertising Cost/Total Number of Conversions

For example, let’s assume that you have run an advertising campaign on Facebook, Twitter, and Google to promote your e-commerce business for a week. If the total advertising cost for the campaign was $1000, and there were about 50 conversions, the CPA would be $20 ($1000/50).

CPA is a critical KPI for every business, as it provides a business perspective to measure the success of your campaign. However, many marketers tend to concentrate on traffic and sales acquisition and overlook cost optimization. Focusing on cost optimization by reducing the cost per acquisition can increase your return on investment (ROI) within a relatively short period.

Cost per acquisition is an important metric that is utilized in various paid marketing activities, including Pay-per-click (PPC), Affiliate marketing, Display advertising, Social media advertising, and Content marketing.

What is CPA in mobile marketing?

Cost per action (CPA) is a performance-based pricing model that enables marketers to pay media sources a fixed rate based on a predetermined action. Unlike cost per install (CPI), which relies on attributed user installs to achieve campaign conversion, CPA can be selected from various in-app events, including registration, app launch, item purchase, and other actions.

The value of CPA is simply the price an advertiser pays a media source for each pre-specified action (e.g., purchase, registration, etc.) driven by that source. To obtain a comprehensive overview of a particular ad network’s performance, you can calculate the effective cost per action (eCPA) by dividing the total cost incurred from that network by the total number of specified actions based on a pre-selected time range.

This metric includes all campaign CPAs you want to measure, giving you an overall view of advertising costs over time on the media source level.

How to Track Cost Per Acquisition (CPA):

Tracking cost per acquisition (CPA) is a crucial aspect of digital-first businesses, and it can be done using several methods, including:

1. Utilizing UTM parameters to generate link codes for social media or affiliate marketing.
2. Exporting pay-per-click (PPC) campaign data from AdWords.
3. Creating custom links for internal campaigns by using promotional codes.
4. Implementing an effective Customer Relationship Management (CRM) system.
5. Including a form field on lead forms that asks customers how they found out about a campaign, which helps to minimize lead attribution gaps.

By leveraging UTM parameters, digital-first businesses can generate link codes for social media or affiliate marketing, which help to track CPA more effectively. Exporting PPC campaign data from AdWords and using promotional codes to build custom links for internal campaigns can also provide valuable insights into CPA. An effective CRM system can streamline the tracking process, making it easier to monitor CPA accurately. Additionally, including a form field on lead forms can help identify the lead source, reducing lead attribution gaps and providing a clearer picture of CPA.

CPI (Cost per Install)

A pricing model or the cost that advertisers pay for each time a user installs the app. This can be calculated only once per user. Basically, the cost of the ad that leads to an app install.

What is Cost Per Install (CPI)?

The CPI, or Cost per Install, refers to a pre-agreed upon price that an advertiser will pay to a publisher for every user who installs their app directly as a result of an advertisement served by the publisher. It is important to note that this term is sometimes confused with eCPI, or effective CPI, which is the actual cost per install that an advertiser incurs as they receive installs in real-time or after the campaign has concluded.

For instance, suppose an advertiser allocates a marketing budget of $10,000 to a publisher, which results in 5,000 installs. In this scenario, the eCPI for this campaign would be $2. Occasionally, media outlets will optimize their campaigns based on an eCPI objective. This means that before the campaign begins, the advertiser and publisher agree to a target eCPI and work towards optimizing the campaign to achieve this objective.

However, it is important to note that self-reporting networks, such as Facebook, Google, and Snap, charge advertisers based on CPM or cost per mille, which refers to the price per 1,000 impressions viewed. These networks optimize their campaigns towards eCPI or the advertiser’s maximum bid levels, while charging advertisers based on CPM. Consequently, their eCPI may differ from the eCPI calculated by the attribution provider since an SRN charges based on engagement, regardless of whether it was attributed for the last touch or not.

How to Calculate Cost Per Install

To calculate the Cost Per Install (CPI) for your mobile app, you need to divide your total ad spend for a specific time period by the number of new installs generated during that same period. The resulting figure is your CPI.

For instance, if you invested $500 in ads for your app and generated 200 new installs during the campaign, your CPI would be $2.50.

Formula: CPI = Ad spend / Number of new installs

Example: CPI = $500 / 200 = $2.50

Therefore, your Cost Per Install for this campaign would be $2.50.

CPI Factors

The calculation of Cost Per Install (CPI) is affected by various factors that determine the price an advertiser pays to a publisher for every new install resulting from an ad. Here’s a detailed explanation of these factors:

Country or Region: The geographical location of the user plays a crucial role in determining the CPI. The socio-economic standards of a region can influence the price an advertiser pays for a CPI, with more affluent countries resulting in higher value users and therefore, higher CPIs. As an example, the average CPI in North America is $5.30 compared to LATAM, where it is $0.30.

Channel: Different channels offer varying services and popularity and thus, different CPI costs. Social media channels like Facebook and Twitter, which cater to larger audiences, can charge higher CPIs, though they need to balance audience size with the CPI. On the other hand, niche channels with targeted audiences can demand higher CPIs despite their smaller scale.

App Vertical/Genre: CPI can vary significantly across verticals and genres within the same vertical. For instance, hyper-casual games usually have a CPI of $1 or less, whereas mid-core and hardcore games can have up to five times that CPI.

Cost of Ad Unit: The CPI cost can also depend on the ad unit’s value, with more prominent ad inventory commanding higher prices than remnant inventory that advertisers cannot sell.

Android vs. Apple: The difference between iOS and Android platforms is another significant factor affecting CPI. For the same reasons as geolocation, iOS users tend to spend more than Android users on average. Regions with a higher GDP, such as North America, Japan, and Europe, tend to have more iOS users, while Android has a greater presence in regions such as LATAM, India, and Southeast Asia. For example, the average CPI for Android is $1.20, while that for iOS is triple at $3.60. Within different gaming genres, there is also a significant CPI gap. For example, puzzle games in Japan have a CPI of $1.77 on Android compared to $3.69 on iOS. Action games range from $2.01 on Android to $3.96 on iOS, while educational games are $1.09 on Android and $3.04 on iOS.

CPL (Cost per lead)

A type of mobile advertising that suggests paying DSP’s for each lead that it has generated. The advertisers pay for information about the potential customer and not for the product or service sold. The calculation formula is the budget spent on the campaign divided by the amounts of leads generated.

Lead generation is a critical marketing metric for your sales and marketing teams. To acquire new leads, you need to conduct various marketing efforts, such as display advertising and webinars. Tracking not only the number of quality leads but also the cost of acquiring potential customers is essential. This is where the cost per lead (CPL) comes in.

What is CPL (Cost Per Lead)?

CPL is the average cost for each new lead generated in your ad campaign. It is a lead metric that measures the cost-effectiveness of your marketing campaigns, ensuring that generating leads is worth the ad spend. Similar to CPM and CPC, it is also an online advertising pricing model where the advertiser pays for a sign-up from a potential customer instead of a view or click.

It is crucial not to confuse CPL with other similar acronyms in digital marketing such as Cost Per Acquisition (CPA), Cost Per Click (CPC), Cost Per Thousand (CPM), and Customer Relationship Management (CRM).

How to Calculate CPL?

Calculating the CPL is relatively simple. You divide the total ad spend for a given period by the number of leads generated for the same period. The formula for calculating CPL is as follows:

Total ad spend / number of leads = cost per lead

What is a Good Cost Per Lead?

While a good cost per lead varies across different industries, it should be equal to or less than your gross profit per sale. For instance, if a sale gives you a total amount of $100 after deducting total costs and expenses, your cost per lead should be $100 or lower. On the other hand, a bad cost per lead is when each lead costs more than your average gross profit per sale.

How to Improve CPL?

To improve your lead generation and lower your cost per lead, consider the following best practices:

1. Use retargeting to reach leads that didn’t convert into paying customers.
2. Optimize your ad campaigns on Google or social media to ensure that lead generation doesn’t cost you an exorbitant amount.
3. Check ad performance on different devices and networks to optimize your ad campaigns.

CPM/CPT (Cost per mille/Cost per thousand)

An advertising payment model that refers to the cost or expense of every 1000 impressions (or views).

What is Cost Per Mille?

Creative

Creative, specifically ad creative, is a file that houses the digitally formatted design and artwork for an advertisement. This file is rendered as a display ad on the publisher’s medium and can take the following formats: Image (GIF, PNG, JPEG), Flash File (SWF), HTML or JavaScript.

CRM (Customer relationship management)

The process of managing interactions with customers from the past as well as current and potential customers. By analyzing a customer’s history and interactions with a company, you can optimize all aspects from customer retention to the ultimate goal of increasing sales growth.

CTA (Call to Action)

A word, phrase, or sentence that encourages the user to perform a specific action. Examples would be “click here”, “buy now”, “download”, “install”, or other creative ways to urge the user to take action. You are essentially motivating the user to act immediately.

CTR (Click-through rate)

The ratio of users who click on a specific link, to the number of total users who view an advertisement. It is often used to measure the success of an advertising campaign.

eCPM

Effective cost per thousand impressions. Total ad revenue generated by 1,000 impressions. It is a metric used to calculate an app developer’s monetization performance or the ad revenue generated by a specific campaign.

Valid Clicks

Clicks not made by mistake.