Business Case performed by Vini Apoena in São Paulo, Brazil.
Working with celebrities seems like you're living in a different world.
But it's business as usual. Show up & show off!
Fernando & Sorocaba hired my services just for digital media management - but as you will see in the lines ahead, the opportunity was so big that I immediately asked for the presence of my favorite data scientist in the world with a challenge in my head:
"We need to predict a hit." - I throw for my Cuban scientist over a giant meeting table.
That's how we started it all.
Take a sip of your coffee & read it.
1. Support the ad-ops of Fernando e Sorocaba's latest release, Terapinga, a track of their new album, drawing structure to massive promotional activities & adding awareness & relevant playlist placements over major platforms like Spotify, Youtube & Deezer.
2. Sell tickets through digital channels by developing new technologies & procedures to help scale the number of total tickets sold - while keeping higher margins of profitability & predicting trouble-cities that could represent underselling threats to the Label.
3. Provide an enhanced understanding of the impact for each product (tracks) the Label drops on the market, helping improve budgeting by consolidating new sets of data & comprehensive dashboards for quicker decision making.
4. Predict the next Fernando e Sorocaba's hit. Using their actual data over video & streaming platforms, while restricting personal bias to extract relevant insights that could better orient the Artists and Record Label in their strategy of what to do next.
While promoting entertainment products or services, you will see the brand with 2 types of consumers that will determine the demand. Innovators & Imitators.
Despite the plain obvious dynamics, the visual conceptualization of this thesis will be decisive to generate new adopters. Country Music in Brazil accounts for 50% of public preference. It's a lot of people. Start the concepts by profiling these buying personas is essential to save us time & resources.
Before setting the answers, we settled the questions by asking all stakeholders which kind of information could make their decisions more confident & assertive?
Check some of their questions:
Why same-category tracks seem to perform above others?
Which are the regular characteristics that influence a hit?
Can we predict a hit & allow safer investments to Labels?
Does paid media works to push track's popularity?
Why some type of campaigns works better than others?
What’s the state-of-art channel mix?
Releasing tracks from competitors on the same day impact popularity?
How to maximize my return over investment?
If we raise the promo budget by 10% it will impact the popularity?
What would be the ideal budget for a release week?
Does category influence budgeting?
A more dashing pricing model on iTunes will be able to deliver more sales?
Did the forecasted revenue meet the actual earnings?
What are the more profitable venues for the Label to promote a show?
A region's economic demographics impact the ticket-sales capacity?
Are local TV & radio networks capable of enhancing the total ticket sold for a show?
What’s the predicted impact of a promoted track?
What to expect when it turns to the return on the investment that is being made?
Can we set up different revenue systems?
Where are the most-likely-to-spend listeners?
That's a lot of questions. All very relevant. Our strategy must cover them all.
The algorithm would be built to predict which cities have more chances of sold-out with the mathematical formula (bass) using long-term revenue data & live sets of evidence from social media, comparison with other category artists & direct communications to build a comprehensive landscape that is set to increase profits for both the Artist & Label.
Our partnership with Facebook helped us reach a level of visibility that, without them, would be impossible to reach. Our data visualization was able to deliver instant insights based on the volume of reactions per region, enabling a comprehensive paid media plan to exist, adapt & deliver real value to all the stakeholders.
They were also essential to help us build a straight connection with ticket-selling platforms so we could deploy our API's into their systems & have full access to all the relationship points with the prospect-buyers. This is a basic service to advertisers - even though more than 75% of this industry has standard tracking procedures installed, 47% of internet users use ad-blockers.
Numbers will not add up without the proper tracking, which must be settled to trespass user-oriented blocking systems - all that while complying with local GDPR Laws. It's not an easy task. It needs to be entrusted to technical people.
PowerBI fitted into our demands. To turn the data more visible, we were able to collect & display different types of consumer behavior in the music industry. The main idea was to not restrict the analysis only including country music data.
Overlaying sentimentalized points of contact over location brought us the first “heat map” with national coverage ever seen by the Label. We pushed further by adding other types of data vectors as advertising spending, radio audience, household income, demographics, trends & etc.
All the briefing sessions involved the agencies working in deploy the infrastructure that was drawn on the strategy & written on the tactical project book - a comprehensive document that I design to help employees over execution & with general questions about the intention of the systems we were developing. Weekly meetings, together with a kanban level management set the mood for everybody to have delivered their best.
1. Terapinga became the 71th Most Played Music of The Year. It collected a massive audience of over +23 million streams on Spotify, together with 31 million views on Youtube.
2. We restrict the experiment to attend 1 venue in the city of São Paulo. The Artists booked an entire space that was positioned to sell tickets just through digital channels & mapping all touch-points over social & paid media. The experiment sold a total of 2.665 tickets exclusively by digital channels with a 2,7x return over investment & delivering a 5,9x frequency that was essential to built leverage.
3. The dashboards settled to follow each of the promoted tracks were part of a larger Knowledge Program that I designed to help both Artists & Label reach a better understanding of the digital landscaping, their competitors & actual position in the recently transformed entertainment business.
4. We predicted to the Label that Bom Rapaz was on the way to be the next big hit from Fernando & Sorocaba. With findings from a growing listening pattern that wasn't notable at first, our data scientists projected that the track would overcome Terapinga as the lead single for the Album with 95% accuracy.
Which actually happened. It was way bigger than Terapinga. The track collected +54 million streams on Spotify, together with +190 million views on Youtube. It became one of their biggest career hits & it was paid-pushed ever since the first thesis started to be defined.
The data set that turned this project viable also delivered a relevant contribution to the Brazilian entertainment scenario & left an audacious mark, showing that the digital transformation is just beginning for this industry.
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A special thanks to my Cuban Scientist, Eugenio Caner from the Murabei Company for helping me collecting all the data necessary for this business case to be written.