
Training without likes – but with performance: mobile phone free zone!
Constantly reachable in everyday life, constantly distracted during training—the smartphone has long since become a constant companion. But especially when it comes to sports, many people are increasingly seeking real time out: fewer distractions, more focus, and higher performance.
This is exactly what digital detox in training is all about – a clear “no” to push notifications and a “yes” to concentration, movement and structure.
Digital Detox: What does that actually mean?
Digital detox means consciously avoiding digital distractions – especially your smartphone. Especially when exercising, your phone can become a distraction: constant notifications, reaching for a music app, a quick glance at Instagram… and suddenly your focus is lost.
Focus instead of feed: Why you should leave your phone behind
Without distractions, your training is:
- more effective – you stay in the flow
- structured – fixed intervals, clear process
- more conscious – you feel your body instead of just the vibration alarm
Training without a smartphone brings calm, focus, and more presence – but it's often not possible to do without technology entirely. A clear timer is especially important for interval training to ensure structure and quality of training.
The solution: A timer that doesn’t vibrate – but pushes you
With the Kondimaster Timer you can bring structure to your training – without the need for an app.
⏱️ No screen swiping. No Wi-Fi. Just you, your timer, and your workout.
Whether in the gym, during boxing training or outside in the park – the timer ensures clear time limits, loud signals and 100% focus.
Train like before – but better
Imagine: You train without distractions, without constantly looking at the display.
You hear the starting sound, you feel your pace, you keep going.
Digital detox is not a limitation – but a gain in concentration and real performance.
📢 Read more in our press release on openPR:
👉 Click here
📦 Discover now: Click here for the timer models