The mobile marketing sector uses many performance metrics to estimate the success of a mobile application. One of the most critical metrics is the K-Factor, also known as the viral coefficient.
If you are a mobile app publisher or developer, understanding what the K-Factor measures and how to use a K-Factor calculator are essential to ensuring the success of your apps and mobile digital properties.
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What is the K-Factor in Online Marketing?
The K-Factor is a mobile application’s viral coefficient, also referred to as the coefficient of virality. It can be considered a type of Key Performance Indicator (KPI) because it measures your application’s virality, or in other words, how effectively your app is spreading to other users through word-of-mouth, invites, or referral programs.
The term “K-Factor” is borrowed from the medical world, as epidemiologists use it to measure a given pathogen’s infection rate and estimate its contagiousness. In other words, the higher your mobile application’s K-Factor, the more your existing users introduce your application to other people, bringing in new users.
Therefore, the K-Factor is a critical metric to evaluate whether your application’s user base is growing, stagnating, or shrinking. The K-Factor calculator is a simple but essential tool to plan your app’s user growth strategy.
How to Use a Simple K-Factor Calculator
K-Factor calculators can help determine your current user base’s growth rate. To use a typical K-Factor calculator, all you need is three basic metrics:
- The number of users or starting customers your app currently has
- The average number of invites or referral codes sent by each member
- The percentage of sent invites that are accepted, converting them into new users (in other words, the conversion rate of your invites)
1. Enter the number of starting customers
First, enter your number of starting users or customers in the requisite field. For example, if your application currently has 3,200 users, enter 3,200 in the K-Factor calculator’s relevant field.
2. Enter the number of invites each member sends
Determine the average number of invites sent by each user. You can typically find this information in your mobile app’s analytics dashboard. For example, if the typical user sends an average of 3.4 invites, enter 3.4 in the corresponding field.
3. Enter the percentage of sent invites accepted (conversion rate)
Your app’s analytics dashboard can also provide you with information regarding the number and percentage of sent invites that have been accepted, also known as the conversion rate.
If your dashboard doesn’t provide you with a percentage to use directly, you can calculate it by dividing the number of accepted invites by the number of total invites sent. For instance, if 600 out of 2,000 total invites sent have been accepted, your conversion rate is 30%, and you’ll need to enter “30” in the K-Factor calculator’s corresponding field.
4. Click “Calculate”
Once you have all three data points, simply click the “Calculate” button and calculate the k factor. Most K-Factor calculators will take the data and calculate two results: your current K-Factor (viral coefficient) and an estimation of your user base’s size for each invite period, also known as a “loop.”
For example, if you have 3,200 users, each sending approximately 3.4 invites, of which 30% are accepted, your K-Factor is 1.02. If you define a loop as a 1-month period, assuming the average invites sent and conversion rates do not change, your user base will grow to 6,464 members at the end of the 1st loop (1 month), 9,793 after two loops (2 months), and 16,651 after four loops (4 months).
In reality, the number of invites sent and the conversion rate likely fluctuate with each loop. This phenomenon is especially likely if your app is relatively large and popular. The best way to ensure these estimates are accurate is to run the calculator at the end of each loop.
What K-Factor Coefficient Do I Need?
Generally speaking, the higher the K-Factor, the better. A higher coefficient translates into a higher number of new users coming in solely through virality. While it is a vital KPI to understand how quickly your app is growing, the K-Factor alone is insufficient to determine whether that growth rate is sufficient.
To understand the K-Factor you need to grow, you must compare it with your churn rate (also known as attrition rate), which is the number of users that abandon the application.
A user is considered to have abandoned the application when it ceases interacting with it for a significant period, often correlating with the length of a “loop” (e.g., one month).
Your app’s churn rate is calculated with the following formula:
- (Users at the start of a loop – Users at the end of a loop) / Users at the start of a loop = Churn rate.
For instance, if you had 4,200 members at the start of a loop and 4,000 members at the end, your churn rate is 0.048. The formula is: (4,200 – 4,000) / 4,200.
Your user base is experiencing growth if your K-Factor exceeds your churn rate. For example, if your K-Factor is 1.2 and your churn rate is 0.4, word-of-mouth and virality are currently bringing more users than are lost by abandonment, resulting in a net increase.
In contrast, if the K-Factor is inferior to the churn rate, you are losing more users per loop than you are getting from virality, suggesting your user base may be shrinking.
Why the K-Factor is Important
Knowing your app’s K-Factor and how to use a K-Factor calculator allows you to gain insights into how effectively your application is being shared from existing users to new users. High K-Factors reflect apps that are popularly referred to as “going viral,” or in other words, experiencing a period of very high user growth. A K-Factor is generally considered high when it is 1.0 or more, as it suggests the user base is doubling or more with every loop.
The information you can obtain from knowing your app’s K-Factor, especially if you compare it with the churn rate, makes it a critical KPI if you primarily focus on attracting new users and generating higher app installation rates. The K-Factor also allows you to compare and contrast how well your app is being shared “naturally” (by your users directly) instead of more traditional avenues, such as paid advertising campaigns.
Optimize Your Digital Properties with CodeFuel
Regardless of your app’s number of users, knowing and optimizing its K-Factor is critical to ensure your user base grows steadily. If you need help finding the best ways to optimize your app’s growth, the experts at CodeFuel are here to help.
Our team of mobile advertising experts can analyze your app’s current performance and help you explore as many growth and monetization avenues as possible. Contact us to learn more about our services.
FAQs
1. Does A High K-Factor Translate Into High User Retention?
No. The K-Factor measures how many new users your app acquires due to existing users bringing them, such as word-of-mouth or a built-in invite system. User retention is measured over time using other metrics, such as active user rates over multiple months or yearly periods.
2. What is the Difference Between K-Factor and Churn Rate?
The K-Factor measures your app’s virality; the growth rate of your user base from invites and word-of-mouth. In contrast, the churn rate measures the rate of app abandonment; the rate at which existing users stop using the application, no longer being active users. Comparing the K-Factor and the churn rate is critical to estimate your application’s net growth.
3. What Are the Best Practices to Increase My App’s K-Factor?
The best way to increase your mobile application’s K-Factor is to improve it in ways that enhance its shareability. In other words, you should incentivize your user base to share the application, and the sharing process should be as easy as possible.
For example, if your app is a mobile game, you can offer rewards for every invite that converts into a new user and plays for a specific period. Building a generally high-quality application that your users enjoy is also a significant factor in increasing its shareability and ensuring that the app retains most of these new users efficiently.
