Format clocks evaluation

At Voizzup we love working with technology to help #radio stations learn and improve. That’s why we have been working on a new service to check the health of format clocks.

Until now a station had to produce demos, design questionnaires and make decisions based on the perception of a small sample of listeners. It was time consuming, expensive and results became quickly outdated.

Nowadays your listeners are continuously providing you with feedback as they listen to aired content from their smartphones. At Voizzup we have developed data collection and analysis algorithms that aggregate listener’s behaviours for every section, on every hour, 24/7. And we turn all that data into valuable insights that help you make decisions based on actual reactions, consistently processed and always up-to-date.

With Voizzup you can answer almost every question that crosses your mind, at any time. Does the main topic perform better on the first or the third quarter-hour? How do commercial breaks affect the TSL? You might also wonder which sequence of elements could be more engaging for your audience.

The times of blind gambling are over, nowadays you can simply air several options for a couple of weeks, while measuring and tracking their performance. And then evaluate the results to make a decision. Embrace the freedom of evolving formats from the cold winter days through the blossoming spring. Remember that you are not stuck to a fixed decision for a whole season any longer. Today you could get updated information from your listeners for every broadcasted hour. Use it to free your creativity and put your ideas on air!

Want to learn more about it? Please contact or check our service page on


Data-driven Music Test for radio

Continuous testing vs. traditional music research

Traditional music research

For decades, we — music radio programmers —  have tested our music libraries through Auditorium Music Tests and Call-outs. Every decision was based on a reduced panel of listeners, telling us — through a dial or a questionnaire — how they would react if the songs presented to them in the form of 8 seconds hooks were played on-air, so we could estimate the impact on our total audience.

Estimations based on the perception of a tiny portion of the audience. But it made sense, it was all we had.

Let’s examine some situations, probably very familiar to those of you who work in music radio programming:

What’s that smell of smoke? Oh, it’s just another burnt song!

  • For months we’ve been playing this song, a super-tester. AMT after AMT the song has been always on the top, showing very healthy levels of passion. (From 120 persons in the auditorium, 86 said they liked the song. 45 said the song was one of their favourite)
  • After one year and a half playing the song in relatively high rotations — we and the rest of the stations in our market — the burn suddenly increases. (23 people say they are tired of the song and they would stop listening if the song is played. However 68 persons still say they like the song)
  • Is a 19% burn acceptable? Many listeners still like it… Which indicator should overrule? Should we stop scheduling the song, or reducing the rotations should be just fine? What do we do?

Men Are from Mars, Women Are from Venus

  • New artist, new song. It was hot in US, so we decided to give it a chance. After 120 spins we take it to call-out for first time and the results show the song doesn’t perform very well among women. (Out of the 80 persons interviewed , 48 said they don’t like the song. From those 48, 27 are women)
  • If 67% of our female listeners don’t like the song, should we just forget about it? Not appropriate for our format? Should we keep playing it and give it another try in two weeks? What do we do?

Nothing. Nada.

  • Similar situation. We receive the first results of a new track which we’ve given 105 rotations in the last two weeks. The only thing relevant that we see in its first results is that the unfamiliarity is pretty high. (From 80 respondents in the call-out, 56 say they don’t know the song. 12 persons like it. Other 12 don’t). 
  • Should we increase its rotations to make it more recognisable? Do we, on the contrary, lower the turnover giving it a less aggressive and more sustainable rotation? Should we leave it as it is and hope it gains more familiarity soon as more stations play it? Or we just stop programming it and let other stations make it grow? What-do-we-do?

Data-driven music test

In previous articles I’ve extensively expressed my belief that data analysis enables a leap forward in radio programming and research.

Probably the most tangible and definite application of data analysis in radio would be a data-driven music test.

It addresses three issues existing in traditional music research:

  • It doesn’t require a laboratory environment, it captures reactions from the audience during natural listening.
  • It’s not based on perceptions or responses obtained through a test dial or a questionnaire. The existing mobile apps of the radio stations can easily convert listeners’ smartphones into devices capable of capturing their actual reactions. 
  • An ATM usually consists of sessions with 60 respondents. Perhaps some more in a call-out. Oppositely, listening data can be captured from significant proportions of the audience, specially in some radio formats, like CHR. We are talking thousands. 


Continuous data capture, real-time testing

In that scenario with no lab environment, with no need to recruit a sample and having the capacity to capture spontaneous reactions from thousands of listeners during natural listening, the continuous and real-time music test is a reality.

As I often insist, the innovation is not in the technology, that is just an enabler. The transformation here is actually on the evaluation cycle. Every song is tested entirely, every time is played. 

This continuity in music testing facilitates the assessment of risk at all times. That helps us feel safer, but more important, invite us to be bolder.

When describing traditional music research methodologies I presented three scenarios. I think it’s a good exercise going back to them and think what would be our approach through data-driven music research. You’ll see that just one new condition changes everything: we are measuring actual tune-outs every time the song is played, so we can see a trend spin after spin.

My name is Tommy Ferraz. I’ve been music programmer, programme director and group programme director in radio for almost two decades. In addition I’m founder of Voizzup and this is our Continuous Music Test:


Will Beats 1 kill traditional audience research in radio?

“We do no market research. None. It isn’t the consumers’ job to know what they want. It’s hard for consumers to tell you what they want when they’ve never seen anything remotely like it.” — Steve Jobs, 1998

Market Research at Apple

In several occasions Steve Jobs expressed his disbelief in market research. Based on statements as firm as the one above, we can assume  Apple doesn’t conduct much research.

I recently wrote an article to present Apple’s Healthkit as analogy of audience research in radio, that might reflect how — perhaps — the tech giant feels about market research:

  • Medical/Audience research is conducted with too low periodicity.
  • Medical/Audience research sometimes uses small panels or too limited samples.
  • Medical/Audience research is based on subjective perceptions.

Beats 1 and traditional research in radio

With the announcement of Beats 1 we are talking radio now! As Jimmy Iovine introduced Apple Music, he already denoted no intention of relying on research. Why?

They don’t want to

Apple positions its music service as the art of curation. Human. Expert. Emotional. When talking about Beats 1, Iovine literally said:

“Not based on research” — “Only music that is great and feels great” — “Only one master: music itself”

They don’t need to

Despite the fact that we could argue that Beats 1 is like any other online radio in the planet, Apple insisted in one idea: it’s the first live worldwide radio station.

However, from my point of view, that’s not what makes Beats 1 unique. This is — let me quote again — :

“All the ways you love music. All in one place” — “And that place is almost in a billion hands around the world already” — “One app, one single app”.

That idea is so impressive that is hard to assimilate. Millions of listeners on the same app. No other way of listening. Apple doesn’t need audience research because they have something way more powerful: data analysis. 

I know, data analysis sounds boring. Please, keep reading. It’s much more fascinating than it sounds. It means being able to know what each of those listeners (remember: millions, all around the world) is doing. Minute by minute. Second by second. 

Listeners will play and stop. They will change the volume. They will share. They will favorite. They will buy. They will unlock screen. They will change station — there will be more non-live stations in addition to Beats 1 in Apple Music— . Trillions of clicks. And each of them will be telling Apple a story. 

Julie Adenuga, Beats 1 host, in Apple Music promotional video

Julie Adenuga, Beats 1 host, in Apple Music promotional video

Radio programming of the future

If you are a programme director like me, a producer or you host a show in radio, I guess you are at this point already imagining the endless possibilities. Let’s fantasize together. (I let you know something in advanced, I’m starting with the most predictable applications and I leave the mind-blowing ones for the end.)

Artificial intelligence and customization

  • With every play, exit, volume change, share or buy Apple might be learning about the behaviours and tastes of each individual user.
  • Based on that, many features could become intelligent and start offering a very personal service to the customer: more precise recommendations, automated curation of music and/or spoken content, collection of missed contents, connection with users with similar tastes, etc.

But I say Apple might. We need to be cautious here. The Californian company was very reiterative putting the focus on the human touch. They said algorithms cannot make emotional decisions alone. That doesn’t mean they won’t use any though.

Engaging audience faster than ever: air, measure, learn

Yep! This is my favourite part. Apple talks about curation, experts, passion for music, the power of connecting millions around the world. Apple is talking about amazing content. About great programming. About engaging radio. Welcome to our business!

And this is where the magic of this new way of doing audience research and radio programming resides. It impacts the creativity of the team at the radio station and — therefore — the passion of the audience:

  • A great new track from a brand new artist is played for first time… and Beats 1 sees hundreds of thousands of listeners getting the volume up at the same time. Isn’t that magic?
  • Zane Lowe is interviewing one the hottest artists at the moment and… boom! He suddenly asks her that tricky question that nobody expected him to dare to ask. His producer: “Hey look, volumes rising again! The average time spent listening of today’s show has been 5 minutes longer than usual!
  • The producer of Julie Adenuga’s show has ammunition to boost her motivation: “I know you are looking forward to playing this, but we need to save it until we are on the crest of the wave. Give me 20 million listeners in the next 10 minutes and you can play it!
  • With every new finding, new questions come.We did great today, but why specially in China?
  • The faster Beat 1′s hosts learn, the more confident they feel. More confidence, less fear, more audacious hosts. The dream of every Programme Director or radio Producer!

Beats 1 can measure every listener’s reaction to everything they air. A short air-measure-learn cycle means better knowledge on how to engage the audience. Faster learning translates into more passionated listeners.

And your radio station, what about it?

Radio colleagues, dreaming is nice, I know. I have good news for you: This way of accelerating the learning on how to engage your audience, is not an imaginary future only accessible to Apple and Beats 1. It’s real, and it’s available for your station. Today.

My name is Tommy Ferraz. I’m one of the founders of Voizzup. And this is what we do.


Find out if you are keeping your listeners engaged!

You don’t need us to tell you how crucial time spent listening is for your share, therefore for your advertisement revenue.

We don’t discover anything new if we say it’s all about audience engagement. Give your listeners one opportunity to get bored and they will just leave.

You, Programme Director, Morning Show Producer or host, know how persistently you and your team need to pursue one single goal: keeping your listeners engaged. And you do so by making sure your programme contains interesting topics, relevant information, entertaining content, funny segments, authentic personalities, current stories or even controversial subjects. In every quarter hour segment. Anything but leaving your listener indifferent. Or even worse… turned off.


Some stations end up using quite unconventional tactics to address engagement issues, like 90.3 AMP in Calgary, Canada.

These guys had the great idea of offering twice as much music per hour so the listeners don’t get bored… by cutting the songs in half!

Genius eh? (Is it? really?) But what if your station is news&talk? Well, you can always cut your personalities in half. Wouldn’t that bring your station some hype?

At Voizzup we are quite atypical, but probably not that much. We prefer focusing on the qualificatives that we used in a couple of paragraphs above: interesting, relevant, entertaining, funny, authentic, current, controvert… We think the most effective way for double-checking you are all those, or some, is measuring.

What do we need to measure?

This brings us back to the initial point: Voizzup measures listeners engagement.

And how do we measure engagement?

Well, we could tell you that we measure every listener interaction with the existing mobile app of your station while each of them listens naturally. We would say as well that we don’t miss a single click (play, pause, volume up or down, share, etc) so the information we extract is essentially qualitative.

But we prefer showing you. This is what we call Engagement Map. Brief explanation: reach per minute in white, increases of attention in red, decreases of attention in blue.

Have fun moving the cursor to the most and least engaging moments of the show!

Engagement News & Talk from Voizzup on Vimeo.


CHR: Safe is risky

Safe is risky. It is in business, in sports, in love… And it is in radio as well, especially in one format: CHR.

If you are a CHR Programme Director you already know playing safe is not an option:

  • You can’t play those songs that always perform well. Your station needs to introduce brand new music, and be the first.
  • Your morning show hosts can’t keep talking about what was trending in Twitter a couple of days ago. They need to surprise the audience, doing the unexpected.
  • You won’t beat your competitors with old-school promotions. You need to give your listeners an “oh-wow”, one that is worth talking about.

How does it feel playing with fire every day? How do you overcome fear to fail? Feel free to comment.

Voizzup introduces Lean Audience Research: air, measure, learn. We turn every on air content into a measured experiment, accelerating learning cycles and managing risk.


Lean Audience Research: air, measure, learn

A few weeks ago one of the most relevant gatherings of radio professionals, Radiodays Europe, was held in Dublin, Ireland. For two and a half days more than hundred speakers shared their thoughts on the current state of our industry. Above all, experts and attendees talked about change.

Greatest ever period of change for radio

Helen Boaden - Head of BBC Radio - said that “Radio is facing seismic shifts in deep-seated listening behaviour”.

Hours of radio listening per week drop while time spent in mobile devices keeps growing. A new profile of consumer is rising, expecting all kinds of media “on their own terms” including on-demand radio. Global giants like Google or Apple (in addition to Spotify, Pandora or TuneIn) are entering a traditionally fragmented nation based industry, making competition more intense than ever before.

Jacqueline Smit - CEO of 538 - expressed similar thoughts. Media industry is changing fast and technology is directly involved in this change which, in Jacqueline’s opinion, is a constant.


For Helen Boaden, although this shifting scenario affected young audience first, it is spreading to all age groups. These challenges for radio are not restricted to a specific demographic anymore. Jacqueline Smit, former head of Consumer and Online at Microsoft, was more explicit:

“I don’t believe in demographics, I believe in behaviours”.

Both Helen Boaden and Jacqueline Smit are convinced that, for radio to overcome constant change, the mindset of the industry requires a profound transformation. In Helen’s words: fail fast and efficiently, learn as quickly as possible, stand up and keep going. Or how Jacqueline Smit stated in her presentation: do, learn, optimize. This process reflects the basic steps of Lean Startup: build, measure, learn.

As a startup, Voizzup breathes Lean. We were really excited when we heard the directors of two relevant radio organisations align so clearly with our lean principles.

We proudly say, Voizzup is Lean Audience Research:

  • Our design methodology helps stations formulate the right questions by removing preconceptions in order to prevent looking in the wrong direction.
  • We turn the rotative nature of radio (songs, segments, benchmarks, topics) into measured experiments and learning cycles.
  • Our technology enables observation of listener behaviours, collecting huge amounts of data from every single listener’s interaction with the player of the station.

It was the lack of data what surprised Jacqueline the most when she moved from Microsoft to radio. Qualitative data rather than quantitative, she explained. Radio builds personal relationships with listeners. It’s about emotion and passion.

Therefore knowing when listening sessions start and end is not enough for Voizzup. We get excited every time data shows how listeners react with passion when their football team scores. We find fascinating seeing reflected in data how listeners’ attention intensifies when the host makes them laugh. We believe these examples illustrate data turning into insights.

The ideas expressed by the Head of BBC Radio and the CEO of 538 support that a new research for radio is both necessary and possible.

And you? Would you share your thoughts with us?
Contact us if you would like to learn more about Voizzup’s Lean Audience Research.