Bubblegum Burst

What is Bubblegum Burst?

Crash games like Aviator have become hugely popular because they are simple to understand and fast to play. A multiplier climbs from 1x and you decide when to cash out.

The key tension in every crash game is greed versus discipline. The multiplier can crash at any moment, so the longer you wait the bigger the reward but also the bigger the risk.

Many players use a fixed cash-out target, such as 1.5x or 2x, and exit automatically every round. This removes emotion from the decision and keeps losses predictable.

What is Bubblegum Burst?

Calvin took notice of Bitcoin in the early days, immediately identifying its vast potential for his “first love”, the iGaming industry. Little did I know just how significant Bitcoin would become for CalvinAyre.com, Calvin Ayre as a person and myself as a professional. Fast forward to February 2021 and its time for CalvinAyre.com to hang up its hat. Bitcoin has actually become my calling. 

The Bitcoin ecosystem, now in the form of BitcoinSV, has advanced to a level where so many of the pain points within the gaming industry can be solved with Bitcoin technology. For this reason, from today, I’m moving over to CoinGeek.com full time with a laser focus on raising awareness of BitcoinSV within the gaming industry and highlighting the innovative minds and relevant BitcoinSV-powered solutions currently existing in the market.

Looking back on my 11+ years with CalvinAyre.com, I’ve made life-long friendships, attended countless industry events, interviewed hundreds of leaders, made thousands of contacts, built deep relationships with organizers, even had the honor of delivering a DAF award or two back in the day (who remembers???!!) but best of all, had the pleasure of working with some of the most incredible colleagues along the way, many of which who I classify now as dear friends.

About Bubblegum Burst

Within this shared model, there was a clear preference for personalised interventions over generic ones. 

Tailored, behaviour-triggered messages were seen as more effective than generic warnings, but many participants simultaneously expressed mistrust towards operators collecting behavioural data.

Finally, the study found that these needs and preferences varied widely by product type.