Data-science in Radio, “it’s just a tool, isn’t it?”
Data science in radio is just a tool. It doesn’t replace us in decision making, but amplifies our understanding of listening behaviours.
Data science in radio is just a tool. It doesn’t replace us in decision making, but amplifies our understanding of listening behaviours.
Notifications are tools. Like every tool, they can be brilliantly used, or hugely misused.
Is your radio organisation planning to apply data-science to on-air content evaluation? You have a bumpy road ahead. Let us save you time and struggle by sharing with you the most common problems and how to prevent them.
Whether your organisation is a tightly budgeted small radio company or a large multi-million dollar actor in the broadcast industry, the main reason that keeps you away from a successful data strategy might be the same one. It’s not about affordability, but readiness.
1. Know when your listeners are paying attention.
2. Seek Time ENJOYED Listening, instead of TSL.
3. Visualise your power and assume your responsibility on-air.
4. Put listener engagement measurement in the hands of the on-air team.
5. “Listempathise”
Just being able to see first hand, daily, the impact everything you say or do on-air has on your audience will make you more aware, more responsible, more confident, more creative.
The morning show “De Grote Peter van de Veire Ochtendshow” on MNM, the VRT station targeting young audience, will be conducting a pilot with Voizzup during the coming months for evaluating their contents daily, starting today.
Big-data guru, Bernard Marr, believes that big data and its implications will affect every single business and change how we do business, inside and out. Let’s do the exercise of applying Marr’s observations to radio.
Data-analysis in radio enables a new way of programming based on experimentation. Voizzup applies it to continuously checking the health of the format clocks of your radio station.