Churn / Churn Rate — Why It Matters, How to Calculate It, and How to Reduce Player Churn

Publication date: 21 September 2026

Churn refers to users who stop being active on a gambling or betting platform over a specific period. Depending on the operator's methodology, this can mean that a player stops placing bets, making deposits, playing casino games, or performing other activities used to define an active user.

Churn Rate is the share of users who stop being active during a selected period relative to the relevant user base at the beginning of that period. Before calculating it, it is important to define what counts as churn and which users are included in the calculation.

Churn is closely related to user retention and Retention Rate. The more users become inactive, the smaller the active audience becomes. For affiliates, churn shows not only how much traffic an offer attracts but also how long that audience continues interacting with the product.

Churn Rate Formula

The basic formula is:

Churn Rate = number of users who churned during the period / number of users in the base at the beginning of the period × 100%

For example, suppose a platform had 500 active users at the beginning of the month. During the month, 100 of them stopped meeting the defined activity criteria.

Churn Rate = (100 / 500) × 100% = 20%

With this methodology, 80% of the original user base remained active during the period.

However, Churn Rate and Retention Rate should not always be treated as simple complements. The relationship Churn Rate = 100% − Retention Rate is valid only when both metrics use the same cohort, period, and activity criteria.

Why the Churn Definition Matters

In iGaming, operators may define churn differently. One platform may classify a player as churned after 30 days without a bet, while another may use the absence of a deposit or any account activity as the trigger.

Therefore, when comparing offers, traffic sources, or cohorts, affiliates should make sure that the same churn definition is being used. Otherwise, identical Churn Rate figures may represent very different user behavior.

Why Track Churn Rate?

• Evaluate traffic quality. If users from a particular source become inactive quickly, this can be a reason to investigate the quality and intent of the audience. It is useful to compare traffic sources and their performance rather than looking only at registration volume.
• Improve LTV forecasts. Higher churn generally means a shorter period of user activity. This can reduce the projected value of the audience and affect LTV calculations and user lifetime value.
• Assess traffic economics. When users churn quickly, the operator has less time to monetize the acquired audience. This can be particularly important for affiliates working with models where earnings depend on continued player activity.
• Compare offers. Two offers can generate the same number of FTDs while showing significantly different retention patterns. First-time deposits alone therefore do not always reflect the long-term value of acquired traffic.

Types of Churn

Voluntary churn occurs when users decide to stop using a product. Possible reasons include dissatisfaction with the product, bonus terms, payment experience, customer service, or more attractive alternatives.

Involuntary churn occurs when a user's activity is interrupted by circumstances outside their direct decision to leave. Examples include account restrictions, verification issues, technical problems, or payment-related limitations.

Separating these two types is important for analysis. If users leave because of product-related issues, product or marketing changes may be required. If churn is caused by technical restrictions or account blocks, the relevant operational process needs to be investigated instead.

What Causes Churn in iGaming and Betting?

Strict Bonus Conditions

High wagering requirements or complicated wagering and bonus conditions can reduce continued user activity. This is particularly relevant when the player's expectations after registration differ significantly from the actual terms of the offer.

Payment and Withdrawal Issues

Limited payment options, withdrawal delays, or technical payment problems can negatively affect the user experience. Reliable payment systems for iGaming are therefore an important factor to consider when analyzing churn.

Lack of Trust in the Operator

Licensing, transparent terms, customer support, and clear product rules can all contribute to user trust. However, churn should not automatically be attributed to the absence of a license without supporting user or cohort data.

Weak Retention Strategy

Users may become inactive faster when an operator does not provide relevant retention mechanisms. Depending on the product, these can include personalized offers, loyalty programs, bonuses, or other engagement tools.

Low-Quality Acquired Traffic

Users acquired primarily for a one-time bonus or another short-term incentive may show lower long-term engagement. This is why affiliates should consider the characteristics of motivated traffic and incentive-driven users when analyzing churn.

Self-Exclusion and Reduced Gambling Activity

Some users may voluntarily restrict or stop their gambling activity. Such churn should not automatically be interpreted as dissatisfaction with the product, as the underlying reasons can be unrelated to product quality or marketing.

How to Reduce Churn Rate

Work with traffic quality. Sources that bring users with genuine interest in the product are more likely to match user expectations and the operator's offering. Analyze not only acquisition volume but also subsequent cohort behavior.

Choose offers with transparent conditions. Clear bonus mechanics and reasonable wagering requirements can reduce the gap between what users expect and what the product actually offers.

Consider the payment infrastructure of each GEO. Users need convenient ways not only to make an initial deposit but also to complete subsequent transactions. When selecting an offer, affiliates should therefore consider the payment systems and payment methods available in the target market.

Analyze churn by cohort. An average churn figure across the entire database can hide significant differences between traffic sources, GEOs, acquisition periods, and user segments.

Separate churn reasons. Analyze users who leave voluntarily separately from those whose activity is interrupted by account restrictions, verification requirements, technical issues, or other operational factors.

Connect churn with traffic economics. Churn should not be evaluated as an isolated percentage. It should be analyzed together with FTD, user revenue, LTV, acquisition costs, and other performance indicators.

Churn Rate and Traffic Economics: The Connection to LTV and CAC

Churn is particularly important when evaluating the long-term economics of acquired traffic.

When users become inactive quickly, the potential monetization period becomes shorter. This can reduce LTV and affect the relationship between user value and acquisition costs.

For this reason, churn should be analyzed alongside CAC and customer acquisition cost. A low-cost traffic source is not necessarily economically efficient in the long term if the acquired users become inactive shortly after conversion.

At the same time, Churn Rate does not determine profitability on its own. Overall economics can also depend on ARPU, ARPPU, FTD, commission structure, advertising costs, retention, and other metrics.

Common Churn Rate Analysis Mistakes

Calculating churn across the entire player base. This can hide significant differences between traffic sources, GEOs, and acquisition cohorts.

Failing to define the churn criterion. If one group is considered churned after 30 days without activity while another uses a 60-day threshold, the resulting metrics cannot be compared directly.

Confusing churn with the absence of a deposit. A user may not make a deposit but still remain active on the platform. The churn definition should therefore reflect the specific behavior used by the operator's analytics.

Ignoring churn when forecasting LTV. User activity duration affects how many periods a player can potentially generate revenue.

Looking at churn separately from CAC. Low acquisition costs do not guarantee positive economics. It is also important to consider how long users remain active and how much value they generate during that period.

Relying only on an average churn figure. Overall churn may remain stable while individual traffic sources or cohorts experience significant changes.