GIRLS IN DATA + PIONEER + CHARTMETRIC +

11/08/2020

Your Brief

Billy Eilish is a pop megastar, with billions of streams across platforms and a huge social media following. And she’s just dropped a new single! was released on July 30. Your task is to recommend what platform(s) she should focus on to promote this new release. In order to help you think through this problem, you will have access to Chartmetric’s data on , Instagram, TikTok, her YouTube channel, and her YouTube video views. You can also go to (www.chartmetric.com), sign up for a free account, and search for her to get some recent stats. But you also have loads of content to to draw upon on these platforms, as well as your own experience of how you and your friends discover music. Use all of this information as you think through this problem. There is truly no right or wrong answer here – only the story you choose to tell, and how you combine the facts available to you with your own creativity in order to tell a compelling one. Bear in mind that careers in data aren’t just about crunching numbers – often, the best insights are those that combine simple quantitative analysis with great storytelling. We’re excited to hear your recommendations.

Getting Started

The first step in any analysis is exploring the data, usually through visualization. We can see the data much more clearly when it’s on a graph rather than a spreadsheet. You may graph the data yourselves using a tool of your choice, but we’ve also provided a number of visualizations for you, below. Study the graphs carefully, both individually and together. What do they tell you about Billie Eilish’s career to date? Consider what they tell you about the quality of the information available as well. If something looks “funny” or surprising, have a look at the spreadsheet data to help you figure out what might be going on. Include your observations on data quality in your analysis of each graph. You will come across multiple Challenge Questions throughout the brief. Pause to consider them and write down your observations before moving on.

Spotify

Spend some time on Spotify exploring Billie’s music. What kinds of playlists is she on? Do you listen to any of these? You may be interested to know that BAD GUY has been streamed 1.5 billion times, while LOVELY (with Khalid) has racked up 1.1 billion streams, WHEN THE PARTY’S OVER is at 939 million, and another 628 million. On Aug 5, NO FUTURE was at 18 million. How does what you learned about her Spotify presence help to explain the graph below?

ARTIST_NAME FOLLOWERS TIMESTP 82828 Billie Eilish 15449 2016-11-26 82829 Billie Eilish 15526 2016-11-27 82830 Billie Eilish 15643 2016-11-28 82831 Billie Eilish 15740 2016-11-29 82832 Billie Eilish 15843 2016-11-30 82833 Billie Eilish 15945 2016-12-01 82834 Billie Eilish 16028 2016-12-02

1 ARTIST_NAME FOLLOWERS TIMESTP 82835 Billie Eilish 16111 2016-12-03 82836 Billie Eilish 16187 2016-12-04 82837 Billie Eilish 16299 2016-12-05

30000000

20000000 FOLLOWERS 10000000

0

2017 2018 2019 2020

TikTok

Spend some time on TikTok trying to understand Billie’s presence on the platform, both as a content creator and as someone whose music is used in content. (Unfortunately, we only have data for how Billie’s music is used on the platform, not her official TikTok account.) Explore some of the hashtags for these songs and others like #billieeilishchallenge. How do your observations help to explain the graph below?

ARTIST_NAME TRACK TIMESTP NB_POSTS Billie Eilish idontwannabeyouanymore 2020-06-08 416100 Billie Eilish idontwannabeyouanymore 2020-06-09 416000 Billie Eilish idontwannabeyouanymore 2020-06-10 415800 Billie Eilish idontwannabeyouanymore 2020-06-11 415500 Billie Eilish idontwannabeyouanymore 2020-06-12 415200 Billie Eilish idontwannabeyouanymore 2020-06-13 415000 Billie Eilish idontwannabeyouanymore 2020-06-14 414800 Billie Eilish idontwannabeyouanymore 2020-06-15 414500 Billie Eilish idontwannabeyouanymore 2020-06-16 414100 Billie Eilish idontwannabeyouanymore 2020-06-17 413800

2 900000

TRACK bad guy idontwannabeyouanymore lovely 600000 my boy

NB_POSTS when the party's over you should see me in a crown

300000

Jan Apr Jul

Instagram

Spend some time on Billie’s IG. What kind of content does she post? How often does she post? What kind of engagement does she get? Does any of that help explain this graph?

ARTIST_NAME FOLLOWERS TIMESTP 8339 Billie Eilish 22156 2017-03-07 8340 Billie Eilish 22322 2017-03-08 8341 Billie Eilish 22466 2017-03-09 8342 Billie Eilish 22583 2017-03-10 8343 Billie Eilish 22892 2017-03-11 8344 Billie Eilish 23191 2017-03-12 8345 Billie Eilish 23372 2017-03-13 8346 Billie Eilish 23553 2017-03-14 8347 Billie Eilish 23725 2017-03-15 8348 Billie Eilish 24495 2017-03-16

3 60000000

40000000 FOLLOWERS

20000000

0

2018 2019 2020

YouTube Videos

Explore Billie’s videos on YouTube, both her official music videos as well other content. For instance, you may want to watch her video on body shaming (https://www.youtube.com/watch?v=ZlvfYmfefSI), or this one of her surprising her fans (https://www.youtube.com/watch?v=uyyQlWNesGM). Notice that you can filter her videos for certain time periods and rank them in different ways. How does what you learned help to explain the graph below?

ARTIST_NAME DAILY_VIEWS TIMESTP 17689 Billie Eilish 17674048 2019-07-14 17690 Billie Eilish 18459967 2019-07-15 17691 Billie Eilish 18844114 2019-07-16 17692 Billie Eilish 18901320 2019-07-17 17693 Billie Eilish 18944697 2019-07-18 17694 Billie Eilish 20234367 2019-07-19 17695 Billie Eilish 20163242 2019-07-20 17696 Billie Eilish 18808721 2019-07-21 17697 Billie Eilish 19672413 2019-07-22 17698 Billie Eilish 19906008 2019-07-23

4 25000000

20000000 DAILY_VIEWS

15000000

10000000

Jul 2019 Oct 2019 Jan 2020 Apr 2020 Jul 2020

YouTube Channel

Search for Billie’s YouTube channel and explore the content there. How does what you observed help explain the graph below?

ARTIST_NAME SUBSCRIBERS TIMESTP 50666 Billie Eilish 11860720 2019-04-25 50667 Billie Eilish 11971853 2019-04-27 50668 Billie Eilish 12122774 2019-04-29 50669 Billie Eilish 12267148 2019-05-01 50670 Billie Eilish 12413372 2019-05-03 50671 Billie Eilish 12574591 2019-05-05 50672 Billie Eilish 12696028 2019-05-07 50673 Billie Eilish 12750001 2019-05-08 50674 Billie Eilish 12803789 2019-05-09 50675 Billie Eilish 12931710 2019-05-11

5 30000000

25000000

20000000 SUBSCRIBERS

15000000

Jul 2019 Oct 2019 Jan 2020 Apr 2020 Jul 2020

CHALLENGE QUESTION

Can you draw any conclusions about what platform she should focus on from what you’ve learned? How else could you look at the data to help you develop your thinking further? Since the question we want to answer is focused on what Billy should do in the future, we may want to take a closer look at what has happened in the last year. We can filter the data to include only records for 2020, and graph that.

6 Spotify 2020

32000000

30000000

28000000 SUBSCRIBERS

26000000

Jan Apr Jul

7 TikTok 2020

900000

TRACK bad guy idontwannabeyouanymore lovely 600000 my boy

NB_POSTS when the party's over you should see me in a crown

300000

Jan Apr Jul

8 Instagram 2020

68000000

64000000

60000000

56000000 FOLLOWERS

52000000

48000000

Jan Apr Jul

9 YouTube Videos 2020

25000000

20000000 DAILY_VIEWS

15000000

10000000

Feb Mar Apr May Jun Jul

10 YouTube Channel

32000000

30000000

28000000 SUBSCRIBERS

26000000

Jan Apr Jul

CHALLENGE QUESTION

At this point, you are probably starting to compare these graphs to one another to help you understand how Billie is performing on each platform. Are there any further transformations that we could apply to the data to make this information more easily comparable? One way to approach this problem is to make the YouTube video views a running total (also known as cumulative sum), instead of a daily count, so that it matches the format of the other platforms.

YouTube 2020 Running Total

ARTIST_NAME DAILY_VIEWS TIMESTP DAILY_VIEWS_CUMSUM 17689 Billie Eilish 17674048 2019-07-14 17674048 17690 Billie Eilish 18459967 2019-07-15 36134015 17691 Billie Eilish 18844114 2019-07-16 54978129 17692 Billie Eilish 18901320 2019-07-17 73879449 17693 Billie Eilish 18944697 2019-07-18 92824146 17694 Billie Eilish 20234367 2019-07-19 113058513 17695 Billie Eilish 20163242 2019-07-20 133221755 17696 Billie Eilish 18808721 2019-07-21 152030476 17697 Billie Eilish 19672413 2019-07-22 171702889 17698 Billie Eilish 19906008 2019-07-23 191608897

11 4000000000

3000000000

2000000000

DAILY_VIEWS_CUMSUM 1000000000

0

Jul 2019 Oct 2019 Jan 2020 Apr 2020 Jul 2020

CHALLENGE QUESTION

Does having all the data in a similar format help you draw any further conclusions or ask new questions? What are some ways that we could continue to transform the data/visualizations to help us compare these platforms further? (Note: We will work with the running total of YT video views from now on, so that we keep a standardized format across the platforms. This way, we make sure to compare apples to apples.) One possible transformation is to combine all the data in one graph so we can look at all these lines overlayed on one another. To do that, we need to make the column names of each dataset the same, and also add a new label so we can distinguish each data source. For TikTok, we will filter for two tracks, BAD GUY and LOVELY, so we don’t have too many TikTok lines clogging up the graph.

Reformatting Data

Here is each dataset reformatted to contain the same column names and a new column identifying the source.

TIMESTP RUNNING_TOTAL SOURCE 82828 2016-11-26 15449 Spotify Followers 82829 2016-11-27 15526 Spotify Followers 82830 2016-11-28 15643 Spotify Followers 82831 2016-11-29 15740 Spotify Followers 82832 2016-11-30 15843 Spotify Followers

12 TIMESTP RUNNING_TOTAL SOURCE 8339 2017-03-07 22156 Instagram Followers 8340 2017-03-08 22322 Instagram Followers 8341 2017-03-09 22466 Instagram Followers 8342 2017-03-10 22583 Instagram Followers 8343 2017-03-11 22892 Instagram Followers

TIMESTP RUNNING_TOTAL SOURCE 202 2020-01-01 796300 Tik Tok Posts - bad guy 203 2020-01-02 796900 Tik Tok Posts - bad guy 204 2020-01-03 798800 Tik Tok Posts - bad guy 205 2020-01-04 800400 Tik Tok Posts - bad guy 206 2020-01-05 801800 Tik Tok Posts - bad guy

TIMESTP RUNNING_TOTAL SOURCE 17689 2019-07-14 17674048 YouTube Video Views 17690 2019-07-15 36134015 YouTube Video Views 17691 2019-07-16 54978129 YouTube Video Views 17692 2019-07-17 73879449 YouTube Video Views 17693 2019-07-18 92824146 YouTube Video Views

TIMESTP RUNNING_TOTAL SOURCE 50666 2019-04-25 11860720 YouTube Channel Subscribers 50667 2019-04-27 11971853 YouTube Channel Subscribers 50668 2019-04-29 12122774 YouTube Channel Subscribers 50669 2019-05-01 12267148 YouTube Channel Subscribers 50670 2019-05-03 12413372 YouTube Channel Subscribers

Combining data

Now we can combine all the datasets into a single one and take a look at it on a single graph.

TIMESTP RUNNING_TOTAL SOURCE 2016-11-26 15449 Spotify Followers 2016-11-27 15526 Spotify Followers 2016-11-28 15643 Spotify Followers 2017-03-07 22156 Instagram Followers 2017-03-08 22322 Instagram Followers 2017-03-09 22466 Instagram Followers 2020-01-01 796300 Tik Tok Posts - bad guy 2020-01-02 796900 Tik Tok Posts - bad guy 2020-01-03 798800 Tik Tok Posts - bad guy 2020-01-01 189500 Tik Tok Posts - lovely 2020-01-02 190500 Tik Tok Posts - lovely 2020-01-03 192300 Tik Tok Posts - lovely 2019-04-25 11860720 YouTube Channel Subscribers

13 TIMESTP RUNNING_TOTAL SOURCE 2019-04-27 11971853 YouTube Channel Subscribers 2019-04-29 12122774 YouTube Channel Subscribers 2019-07-14 17674048 YouTube Video Views 2019-07-15 36134015 YouTube Video Views 2019-07-16 54978129 YouTube Video Views

4000000000

3000000000 SOURCE Instagram Followers Spotify Followers 2000000000 Tik Tok Posts − bad guy Tik Tok Posts − lovely YouTube Channel Subscribers RUNNING_TOTAL YouTube Video Views 1000000000

0

Jan Apr Jul

CHALLENGE QUESTION

As you can see, YouTube videos have so many more views than the other platforms have followers, subscribers or posts that we can’t really see what’s going on. What are ways that we could transform the data further to make the picture clearer? We could try filtering out YouTube video views and TikTok posts. This makes sense because Spotify, IG, and YT Channel are all follower/subscriber counts, so they are more comparable to one another than video views or number of posts. Because they are the same kind of measure, they also have a more comparable range.

14 Excluding Observations

60000000

50000000 SOURCE Instagram Followers Spotify Followers 40000000 YouTube Channel Subscribers RUNNING_TOTAL

30000000

20000000

Jan Apr Jul

CHALLENGE QUESTION

Can you draw any further conclusions from this graph? Do you have any ideas on how you could transform the data even further to help you look at all the different sources on a single graph that actually makes sense? One method for achieving this is called normalization, which means transforming the measure variable – in this case, the RUNNING TOTAL – to be expressed as a percent change instead of an actual number. By showing the daily increase or decrease in followers/subscribers/views/posts as a percentage instead of an actual number, we should be able to compare all these sources better.

Normalizing Data

Let’s add a daily percent change calculation to the data and then graph it.

TIMESTP RUNNING_TOTAL PERCENT_CHANGE SOURCE 83857 2020-01-02 18170970 0.3071709 Spotify Followers 83858 2020-01-03 18220143 0.2706130 Spotify Followers 83859 2020-01-04 18275747 0.3051787 Spotify Followers 83860 2020-01-05 18332312 0.3095086 Spotify Followers 83861 2020-01-06 18388070 0.3041515 Spotify Followers

15 40

SOURCE Instagram Followers

20 Spotify Followers Tik Tok Posts − bad guy Tik Tok Posts − lovely YouTube Channel Subscribers 0 PERCENT_CHANGE YouTube Video Views

−20

Jan Apr Jul

CHALLENGE QUESTION

What do you think? Has this helped you compare the sources any better? Any ideas on how to get an even clearer picture of how these sources compare to one another? How about looking at MONTHLY percent changes instead of DAILY? We can aggregate the data by month, and then graph it.

Aggregating Data

TIMESTP MONTH_YEAR RUNNING_TOTAL PERCENT_CHANGE MONTHLY_PERCENT_CHANGE SOURCE 2016-11-26 2016-11 15449 NA NA Spotify Followers 2016-12-01 2016-12 15945 0.6438175 3.210564 Spotify Followers 2017-01-01 2017-01 18372 0.3495740 15.221072 Spotify Followers 2017-07-01 2017-07 66228 1.4832976 22.794527 Instagram Followers 2017-08-01 2017-08 92328 0.9071237 39.409313 Instagram Followers 2017-09-01 2017-09 147662 0.8041834 59.931982 Instagram Followers 2017-10-01 2017-10 201138 0.8084200 36.215140 Instagram Followers 2020-08-01 2020-08 361900 0.0000000 1.117631 Tik Tok Posts - lovely 2019-04-25 2019-04 11860720 NA NA YouTube Channel Subscribers 2019-05-01 2019-05 12267148 1.1909320 3.426672 YouTube Channel Subscribers 2020-01-01 2020-01 24400000 0.0000000 6.086957 YouTube Channel Subscribers 2020-02-01 2020-02 25800000 0.3891051 5.737705 YouTube Channel Subscribers 2020-03-01 2020-03 27200000 0.7407407 5.426357 YouTube Channel Subscribers

16 30

SOURCE Instagram Followers 20 Spotify Followers Tik Tok Posts − bad guy Tik Tok Posts − lovely YouTube Channel Subscribers YouTube Video Views 10 MONTHLY_PERCENT_CHANGE

0 2020−022020−032020−042020−052020−062020−072020−08

That’s a much clearer picture, isn’t it? That’s it for now! We’ll end our graphical exploration here, but of course, there’s a lot more you could do. Feel free to jot down ideas and share them.

Further Considerations

As your formulate your ideas on what platform(s) Billie should focus on for MY FUTURE, you may want to consider some business factors. For instance, Spotify streams generate a lot more money for the artist than YouTube or TikTok, and IG doesn’t generate any money at all. However, all of these platforms can offer a big audience boost to Billie, which in turn can lead to more paid streams. We suggest not working on all this in one go – let your ideas “bubble up” and come back to the graphs and the content over time to explore them further. Have fun! Can’t wait to hear what you think about Billie’s social and streaming strategy for this new song.

17