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The mobile app market has been witnessing record levels of growth and valuation in the last decade. Apps emerged as a significant engine of business value via engagement-driven revenue models, such as in-app advertising or purchases, that highly depend on continued use. However, engagement typically diminishes quickly over time, pushing businesses to develop new strategies to maintain user activity. To keep users engaged, many companies implement gamification by incorporating features like levels, badges, points, etc., alongside traditional value rewards to enhance an app’s appeal. Still, it is hard to exactly determine how gamification serves to maintain user engagement and business value.

A investigates whether gamification can truly help keep users engaged in ways that also generate tangible business value. Specifically, the authors examine how chasing game rewards (points, levels, etc.) and value rewards (discounts, credits, etc.) interact to influence user engagement with the app and whether this interaction enhances the quality and quantity of such engagement. The findings suggest that game-based rewards are more effective than regular rewards at getting users involved, which in turn increases business value. They find that this effect is especially strong when users are closer to the rewards. At the same time, the study points out a drawback of gamification: When users become deeply absorbed in the game, their engagement with the game is less likely to translate into actions that add real value.

Game-based rewards are more effective than regular rewards at getting users involved, which in turn increases business value.

Managers can use these findings to design smarter reward systems in their apps. Adding simple game elements like points or levels is a low-cost way to keep users engaged, but these should be carefully linked to value-creating actions such as watching ads, making purchases, or completing tasks. Using both game rewards and real rewards works best when they are spaced out over time rather than given at the same moment. Managers should also be careful not to make the game so immersive that users ignore value-creating activities; showing ads or prompts earlier, before users become deeply absorbed, can help. Overall, the main idea is to balance fun and business goals so that engagement leads to real value rather than distraction.

We recently had the opportunity to contact all the authors of this research to gain deeper insight into their motivations, managerial implications of this research, and additional insights of interest:

Q: What was your motivation behind this research? Was there something you observed in real-world app usage that made you curious about how gamified rewards shape user behavior, and what prompted you to take a closer look at their impact on engagement and business outcomes?

A: This research was directly motivated by a collaboration with an app provider who approached us for advice on how to make their app more engaging. The focal app was a market research app, and their request immediately posed a challenge: the app’s core value-adding activity—that is, answering client survey questions—is not inherently engaging for most users. Moreover, these client surveys only arrive intermittently, meaning that users often simply could not do anything in the app that would have earned them rewards.

The provider had introduced an additional activity that was non-value-added from the firm’s perspective but potentially engaging for users: so-called “fun questions.” These questions were designed purely to keep users active in the app and to motivate repeated usage, even when no client surveys were available.

Importantly, the app’s incentive structure clearly separated these two types of activity. Specifically, users received (traditional) monetary rewards (in-app coins that could be redeemed for vouchers, for example) for answering client surveys (value-added activities). Answering fun questions (non-value-added activities) was rewarded with experience points and with climbing up levels by collecting experience points (gamified rewards). This design ensured that every activity contributed to one of the two reward systems—thus maintaining engagement—while only the value-added activities generated actual costs for the provider.

When we looked beyond this specific case and considered the mobile app market from a broader perspective, we realized that this dual reward system extends far beyond market research apps. Many apps combine value-added activities and non-value-added activities. A fitness app, for example, may create (monetary) value for the provider through subscriptions, while users primarily engage in workouts, challenges, or tracking features that are available for free, and revenue comes from a subset of users upgrading to premium. Similarly, social media and content apps rely on high levels of user engagement that only translate into revenue indirectly, for example, by increasing advertising exposure. This observation led to a broader conceptual insight: Many apps operate with dual or hybrid reward structures that simultaneously reward different types of activities through different psychological mechanisms. While marketing research has studied reward-pursuit effects extensively, this work has almost exclusively focused on a single reward engine, typically monetary rewards tied to value-added activities. However, once an additional gamified reward engine is introduced, the psychology of reward pursuit changes fundamentally. Understanding how these dual reward engines interact with each other, reinforce each other, or sometimes undermine each other became the central motivation for this research.

Q: Marketers often prize immersion (flow) as the gold standard of engagement. In fact, previous studies show that it can elevate customer experience, boosting satisfaction and loyalty. However, your work highlights an important dark side. Could you please elaborate on why a highly engaged user in a deep flow state might ultimately contribute less marginal value, even while spending more time in the app?

A: You are absolutely right that immersion and flow are often seen as the gold standard of engagement. From the user’s perspective, flow typically enhances enjoyment, satisfaction, and the overall experience when using an app. Our findings do not contradict this view, but they show that flow is not unambiguously beneficial from a firm’s value-creation perspective.

The key issue is that time spent in an app is not the same as the value created for the firm. In many engagement-based business models, value for the firm is generated only when users engage in specific activities, such as providing data, viewing ads attentively, or making purchases. In our context, these are the value-added activities that can interrupt the gameplay experience.

When users enter a deep flow state during gameplay, their attention becomes narrowly focused on the game-like activity itself. Psychologically, flow is characterized by intense concentration, reduced awareness of external stimuli, and a strong desire to maintain uninterrupted progress. In such a state, any activity that pulls users away from the game feels more like a disruption than an opportunity. As a result, even though highly immersed users spend more time in the app, they become less responsive to value-adding tasks because they want to avoid gameplay interruption.

Overall, users in a high flow state may engage in a lot of activity and time spent in the app, but the incremental value of the additional engagement for the firm decreases. These users’ attention is increasingly focused on maintaining the flow experience and less on performing value-added activities. In extreme cases, users may then rush through the value-added activities or avoid them altogether, reducing both the quantity and quality of value created for the firm. From a managerial perspective, this finding implies that maximizing flow is not always optimal.

Q: For companies that solely rely on traditional value-added programs (coupons, discounts etc.), how can marketing managers effectively introduce “game rewards” to complement (without cannibalizing) their existing strategy? Could you please share your thoughts on how to strike this balance?

A: For firms that already rely on traditional value-added reward programs, the key is not to replace these mechanisms but to use game rewards as a complementary motivational layer. Our findings suggest that the greatest challenge lies not in introducing game rewards per se but in introducing them in such a way that they do not compete with or distract from value-added activities.

First, functional separation is key to adding game rewards effectively. Game rewards should primarily incentivize non-value-added activities, such as exploration, learning, habit formation, or repeated app access, while value rewards should remain tightly linked to behaviors that directly generate value for the app provider. This separation preserves the economic logic of the reward system and avoids teaching customers that rewards can be earned “cheaply” through gameplay.

Second, managers should carefully manage timing and proximity. Our results show that proximity to rewards can be highly motivating, especially when users are close to both a game reward and a value reward at the same time. In terms of designing the reward system, this means that game rewards should prepare users for value-added activities by keeping them active and emotionally engaging them in using the app without triggering reward attainment in both reward systems at the same time. Avoiding simultaneous reward resets is important, as double reward attainment can temporarily dampen engagement.

Third, firms should actively manage flow levels. While some degree of gamified engagement is beneficial for sustaining usage, deep flow states can reduce responsiveness to value-added activities. Firms should thus insert value-added activities at natural breakpoints in the game experience, such as between levels, after milestones, or during cool-down phases, rather than during moments of peak flow.

Q: Your study highlights “double post-reward resetting” as a critical user retention risk. Why does receiving simultaneous rewards lead to a sharper decline in engagement compared to receiving just one reward? What specific strategies can marketing managers employ to prevent that dip and maintain user momentum?

A: Double post-reward resetting occurs when users attain a game reward and a value reward at approximately the same time. Each reward on its own can trigger a short-term decline in motivation and engagement, as users have achieved the immediate goal and the next goal suddenly seems further away. When both reward engines reset simultaneously, these declines in motivation compound, leading to a sharper and more persistent decline in engagement than after a single reward attainment.

Psychologically, this double reset happens because reward pursuit is driven by a sense of progress and momentum. When users are close to a reward, effort feels meaningful and directed. Once a reward is attained, that sense of progress collapses and has to be rebuilt. If two reward engines reset at the same time, users experience a double loss of momentum. There is no nearby goal in either system that pulls them back into activity, which makes disengagement more likely.

From a managerial perspective, this risk is particularly relevant in hybrid reward systems. While multiple reward types increase engagement during pursuit, they also increase the likelihood that users will reach multiple endpoints simultaneously.

One effective strategy is temporal separation of rewards. Managers can design reward thresholds so that game rewards and value rewards are unlikely to be achieved on the same day or within the same session. For example, game rewards can operate on shorter cycles, with frequent small milestones, while value rewards are spaced out over longer horizons.

A second strategy is staggered goal visibility. When a user attains a reward in one reward engine, the system should immediately make progress toward the next reward in the other engine highly salient. By highlighting that another attainable goal is already within reach, the system maintains a sense of forward momentum and prevents users from feeling as though they are starting from zero across the entire reward structure.

Third, firms can use post-reward bridging mechanisms. After a reward is attained, users can be offered a light follow-up task that quickly restores progress, such as a bonus challenge, a progress boost, or a limited-time multiplier. The goal is not to add more rewards but to shorten the psychological distance to the next meaningful milestone.

Overall, double post-reward resetting is not a reason to avoid hybrid reward systems. It is a reminder that firms need to use strategies that preserve user momentum and fully capture the engagement benefits of combining game and value reward.

Q: You propose using algorithms to detect users’ engagement state in real-time. Practically speaking, how do you envision AI-driven personalization and adaptive interfaces to shape the long-term effects of gamification on customer engagement, and do you believe AI can help mitigate the flow-state issue by detecting immersion and adjusting value-added prompts accordingly?

A: We do not propose AI as a way to make gamification more intense but as a way to make it more situationally intelligent. The central idea is that engagement is not static. Users move between different states over time, ranging from low engagement to goal-oriented reward pursuit to deep flow. The long-term effectiveness of gamification depends on responding to these states dynamically rather than applying the same interface logic and reward activities to everyone at all times.

In practical terms, AI-driven personalization can infer a user’s current engagement state from behavioral signals that are already available in most apps. These include interaction speed, session length, task switching, error rates, response times, and progression velocity. In our study, flow manifests itself in unusually fast progress and highly concentrated activity. It is precisely these patterns that machine learning models are well-suited to detect in real time.

Once engagement states can be inferred, adaptive interfaces can adjust how and when value-added prompts are presented. Here, AI can directly mitigate the flow-state issue. Instead of interrupting users indiscriminately, the system can learn when a user is likely to be more receptive to value-added activities versus when the user would perceive such prompts as disruptive. For example, during periods of deep flow, the interface might temporarily suppress value-added activities or defer them to moments when the user naturally slows down, completes a level, or exits a task sequence.

Over the long run, this kind of adaptation helps align user experience and firm value creation. Instead of maximizing flow at any cost or pushing value-added activities too aggressively, AI enables a balance between sustained engagement through gamification and economically meaningful behaviors. Importantly, this setup also reduces heterogeneity issues. Some users thrive in flow-heavy environments, while others respond better to extrinsic incentives, which are often provided for value-added activities. AI enables firms to learn these patterns at the individual level and adjust trajectories accordingly.

Q: Could you please tell us whether any unexpected findings or emergent patterns arose during your analysis that surprised you or challenged your initial assumptions about how gamification drives engagement?

A: Yes, several findings genuinely surprised us and led us to rethink some common assumptions about gamification and engagement.

One unexpected result was how strong and robust the effects of reward proximity were for both types of rewards. We anticipated that getting close to a game reward would primarily increase game engagement, and that proximity to value rewards would mainly affect value-added behavior. Instead, we found strong cross-effects between the two reward systems. Being close to a value reward also increased game engagement, and being close to a game reward increased value-added engagement. This finding suggests that reward proximity creates a general motivational state rather than activating narrowly targeted behaviors. That was something we had not expected at the beginning.

Another unexpected insight was that more engagement was not always better. Before running the analysis, we expected that higher game engagement would monotonically translate into higher value-added engagement. While this was true on average, the moderation by flow revealed a clear nonlinearity. Once users entered a deep flow state, additional engagement led to diminishing and even negative marginal returns for the firm. This finding forced us to move away from a simple “maximize engagement” narrative and to arrive at a more nuanced view where the quality and direction of engagement matter as much as its intensity.

Finally, we were struck by how systematically these patterns emerged in a very large and granular dataset. The effects were not driven by a small subgroup of users or by short-lived novelty effects. Instead, they reflected stable behavioral regularities over time. This consistency increased our confidence that these dynamics are not idiosyncratic to a single app but point to broader mechanisms at work in gamified digital environments.

Source: Jens W. Paschmann, Hernán A. Bruno, Harald J. van Heerde, Franziska Völckner, and Kristina Klein (2024), “,” Journal of Marketing Research, 62 (2), 249–73. doi:

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