Whenever a user finds themself starting out in a new game, a platform, or interacting with a product, the digital realm must provide the right reason for them to prolong their interest. The online environment is ruthless in this regard because of how easy it is to pivot away from it without any pressure, especially if there is no financial stake.
That’s why using mechanisms that create a hook is such a critical step. Out of all the would-be formats, the onboarding reward is usually the most important. The numbers say it, and the product and service design has gratified this principle in actual practice.
In this article, we will explore the ins and outs of these incentives. Structurally, we will start by pinpointing the markers of importance through available data, we’ll compare onboarding benefits with what is available down the line, and then explore the mechanisms that can shape them. Lastly, we’ll also use the gambling example to showcase its portability.
FTUE: How the first 24 hours make or break an experience
FTUE stands for the first-time user experience and is the onboarding process that a reward wants to incentivize. It refers to the moment when the user initially interacts with a product, to the moment when that initial session ends.
The FTUE essentially boils down to the first day when the customer has any contact. Data suggests that it’s essentially a triage for most of the digital products that users interact with, and the do-or-die importance of this first impression is vital for the viability of said product.
Per the data that we have from GameGrowthAdvisor, which assessed over 11,600 titles, the median retention of users after the first day of contact is 22%.
The top performers identified by this study, which are the top 10%, had a 40% retention rate, while the 1%ers qualified with about 65%. As such, not even the absolute best can retain much more than half of their visitors.
Such data basically tells us that most of the users who access a digital product like a mobile game don’t even return for a second day, let alone a week or a month. This strongly incentivizes a strong opening effort on day one of the onboarding process, which may explain why the top retention performers perform so much better than the median of 22%.
A comparative perspective between onboarding and backloading passes
You may remember the big pomp made by the introduction of the battle pass in Fortnite back in 2017. It essentially popularized the concept of a season pass, which created a system that confined rewards to a certain period, incentivizing players to be active during that timeframe. The entire system propagated in triple-A gaming throughout the rest of the decade.
The fact is that the model actually has its origins from Valve, which used its 2013 International Compendium to create a prize pool made out of digital booklets that cost $10 each. It also added levels to it a year later, only to eventually discontinue the system in 2023 after years of declining engagement.
We began with this tangent because, as the headline suggests, it is a reward methodology that we can use comparatively to assess the onboarding incentivization. It’s also a really interesting topic, especially since it represents a step down from the much-maligned gamblification of video games through loot boxes, as Daniel Joseph’s ‘Battle pass capitalism’ research article presents (for further reading).
So, to make things easier to compare side-by-side, let’s use a table to explain the differentiation that clarifies an onboarding reward’s structure.
| Onboarding Reward | Season Pass | |
|---|---|---|
| Recipient | It’s for new users only, regardless of industry or medium. Marketing makes it exceedingly clear. | It’s for everyone, as qualification is automatic for every user who enters the game’s overall system. |
| Frequency | One-time only. Once the user receives and uses it, the reward is permanently spent. | Refreshing. The season depends on development effort and can be framed as thematic (monthly angle, for example). |
| Objective | Its sole purpose is for the product to survive the FTUE moment and secure a day two. | Avoidance of user churn and reanchoring are the main tandem. The pass refreshes user interest by reframing a habit. |
| Reward Curve | Entirely front-loaded, since the entire reward is for the beginning of a user’s experience. It meets the all-in method requirement for FTUE triage. | Mostly back-loaded, but with a smoother transition. Rewards generally grow in value and claim difficulty as you progress, which incentivizes continuous engagement. |
| Cost | It’s free or attached to an initial cost that the product might have to pay by default. | It depends on the game or on the system. Some systems have a free and a premium path. The former can cost anywhere from $10. |
| Availibility | A short time, usually 1-7 days. | An entire season and completely resetting thereafter. |
| Implied Behavior | The product manufactures early momentum with the appeal of the reward and extends an olive branch of reciprocity (a user gets something for their commitment). | Completionism motivates going for all rewards, and sunk cost frames incompletion as failure, and scarcity frames lost rewards as unmissable artifacts. |
| Failure | The user never returns, and the FTUE defeats any chance of retention. | Churn before the user completes the season pass. It likely means they lost interest in the model or the rewards (a product design failure), indicating they won’t come back next season. |
The mechanism of the habit loop according to scientific research
Any product that wants to find itself viable to a customer, either in the medium or long term, wants to set up a habit loop. However, even that begins with a hook, and the entire sequence needs to be properly fine-tuned to work well.
Research gives us two major models:
- ‘The Power of Habit’ frames the Duhigg loop as cue → routine → reward. The mechanism sustains itself through craving, which is the vector that unites them all. To crave at first would be to follow a trigger that ignites that sensation, which then turns into a repeatable routine that leads to the craved result.
- Nir Eyal’s ‘Hooked’, which appeared in 2014, two years after Duhigg’s model, sees Eyal adding another element, and framing the loop as trigger → action → variable reward → investment. It mostly works the same, but the investment factor highlights how streaks, social competition, and progress trackers stimulate the idea of taking action after receiving the trigger.
So, in our digital product context, that would require the onboarding sequence to be part of the loop, each would translate in the following ways:
- The cue/trigger is mostly the mechanism that reminds the user. Push notifications are the easiest method, especially if timed daily. It can be something as simple as seeing the app’s icon, but it’s naturally less intentional. That’s why the onboarding process leverages the possibility of rewards via notification set-ups during this phase.
- The routine/action is what the player actually engages in. It’s the act itself, which a digital product usually turns into opening, claiming, and playing something. In the initial phase, the reward showcases or boosts the action that a routine wants to entrench in the user’s daily life.
- A reward, which can be an item, in-app currency or progress, is the valuable aspect that the routine seeks. It’s the premise that apparently drives the entire loop.
- Investment, in an Eyalian sense, would qualify as the abstract value the user is averse to losing. It’s also the most important driver in this hook, since it serves as a reminder/motivation behind tolerating the cues (notifications) and having an active reason to engage in the routine. If it starts during the onboarding process, it showcases the importance of the investment from the jump.
Fixed versus variable rewards
Either of the two models for the product hook establishes the interaction structure and methodology with the user. How about the nature of the reward, especially if the initial one (during the onboarding phase) is part of the settling period?
The split mostly discusses the schedule:
- Fixed-timing ones are predictable and allow the user to plan around them since they have a time marker within their day. Its main benefit is to allow the routine to establish itself with clear cues, but it can cause tedium if it becomes a habit with no impetus.
- Variable-timing rewards are unpredictable and unpinpointable, which means planning around them is impossible without a clearer sense of their timing. What they excel at is sustaining a pre-established routine and dispelling tedium. The flipside is that they can be frustrating if the lack of scheduling knowledge leads to missed action.
The Wolfram Schultz dopamine reward prediction error thesis shows, through neuroscience, that there is a dopamine response discrepancy between how we perceive the reward that we receive and what we predict.
A surprising reward produces a strong response, a predicted one produces no response, while a reward that is not perceived leads to a negative response, below the baseline that the predictable one would assess. That’s why losing a streak is such a powerful sensation compared to simply doing a routine action: it elicits an aversive response.
So, as we’ve established so far, there is a need for consistency through routine (predictable schedule), but our neuronal responses are strongest when the unpredictable happens through variable outcomes. The conclusion is that the best products integrate both:
- Fixed-timing ones set up the structure that includes the cue and the action, so they are reliable and capable of creating the routine. That’s why a front-loaded reward during the onboarding phase should be predictable and fixed.
- Variable-timing incentives are layers of unpredictability that do not completely break routine but mitigate the threat of boredom by reshuffling the sequence without altering its structure.
This one-two punch is the strategy that works in most successful products because it diversifies engagement avenues.
Examining the casino offer example
Two working theories that have competed is that a) video games gamblified itself and b) gambling copied the video game sector. The truth is that there has been a back-and-forth.
- Video games understood that gamblifying the reward mechanic boosts the willingness to pay for the chance to obtain a reward of varied value ratios via reinforcement;
- Gambling brought gamification by missions, challenges, progression bars, levels, and streaks from video games.
However, what we see with the gambling industry is that it has its own response to the hook methodology, and its initial offering generally operates as such.
Based on the welcome bonus guide from SlotsCalendar, we know that the model provides a reward in bonus money based on a deposit that matches a percentage:
- A 100% deposit up to $100 will give you $100 in credits that you can play alongside the $100 that you deposited. Put $20 in your account, and you get $20 in such funds.
- The thing is, it almost always implies wagering requirements. What the casino gives you is not real money in a real sense, but casino credits.
- A wagering multiplier (10x, 20x, 30x, 40x, etc.) applies to the bonus sum or the deposit + bonus amount, which creates a turnover sum: 10x for a $100 bonus means $1,000 or $2,000, depending on what the multiplier applies to.
- To clear this sum, you must make bets with the total amount of money that th turnover indicates. If you have a $1,000 sum to clear, you need to make 200 bets, each worth $5.
Gambling has quite a few reward mechanisms that resemble the season pass, with challenges, loyalty programs, and reload offers. However, the welcome bonus is the front-loaded bonus that virtually every casino uses as its way of facing the FTUE conundrum.
The interesting part comes from the way the hooks operate:
- The investment comes from two things: the deposit that you make, and the wagering requirements. You know that the bonus is not complete, so losing it by not clearing that turnover becomes a loss-aversion mechanism.
- There’s a possibility to generate real revenue, which means that, down the line, the product itself may need to bear the cost of engagement, which is the inverse of other digital products, even if the overall mechanism is the same.
Closing remarks
That’s about it for the entire dive. Digital product rewards understand that the initial contact with the user is the single most important and brutal decider, and that the rest of the loop depends on whether the hooking mechanism can establish a routine that does not become too habitual.
Naturally, the question is whether the user can retain a sense of responsibility and measure while they engage with the product. When discussing gambling, this responsibility is vital.