Will Streaming kill Movie Theatres?

Email: njp1g18@soton.ac.uk

ID: 30126304

Movie theatre chains and independent cinemas have seen sharp plummets in footfall and revenue during the COVID-19 pandemic. With the AMC movie chain experiencing a 35% decline in stock price. But due to the hesitance and fear within many audience members, these traditional business models maintain their fragility to a tumultuous climate. With the advent of high-speed internet and cloud service technology, the emergence of streaming services has drastically changed the landscape of content watching. Netflix generated $24.9 billion within 2020, which is a 23.8% increase year-on-year. It was reported that during peak times, 37% of network traffic within the United States was used for Netflix content streaming. With this innovative business approach, Netflix also endeavoured to change the way audience view their content, introducing 'binge-watching' into the mainstream in 2013 with "House of Cards". Given that Netflix has changed the way users engage with their content, the television industry was in for a big shakeup. With up to 33 million Americans cutting their cable in 2018 alone. The move from legacy models to streaming of many households develops an investigation into the grounds of the further decline of movie theatres

How have streaming services and movie theatre chains grown?

To understand the effects streaming services have on the general audience, an investigation into their global growth rate is warranted. The grouped-bar chart below details the progression of the Netflix userbase among all the regions they serve. This graph was formed from quarterly subscriber reports.

From the bar chart above. It cannot be disputed that Netflix has had a steady growth in membership from the first quarter of 2018 to the second quarter of 2020. With an average percentage growth of 100.7% across all-region. Growing the fastest in the Asia-Pacific Region with a growth rate of 204% from Q1 - 2018. You can hover over the bars to visualise these progressions yourself. The United States and Canada region remains the largest market for the streaming giant with 72 million subscribers in Q3 - 2020 and experiencing a steady rise of 19.7%.

As streaming services become more adopted and widespread they are at greater chance of manipulating and adapting the audiences to new forms and speeds of media consumption. An analysis of what factors affect the rate of Netflix's growth are warranted. The comparative line graph below imposes various metrics onto the rising trend of global Netflix users. The amount of content available on their streaming service is an important metric for the company to watch over, as the copious amount of content on their service for on-demand viewing is the company's unique selling point. Netflix also curates and develop original content for their viewers. A correlation between the amount of new content developed and the rise in subscribers would show how fruitful this strategy is. by Interact with the drop-down menu below to visualise different metrics.


Netflix truly start to kick off their content production in 2016. The two variables are correlated, suggesting that the streamer can sustain and bring in a wider audience. The decline of TV also shows a strong negative correlation with the increase in streaming activity, the Dish TV Network, an American Television service provider, falling by 5.62 million users within 6 years. This decline could be foreshadowed in the film industry, the toppling of a legacy entertainment model causes other models to fall into doubt.

The Pearson's R2 Correlation was measured for the relationship between user growth and new original content. A value of 0.74 hinted at a strong positive correlation between the two metrics. The linear regression model can be used to infer results from the trend. For example, with 750 new original content released within a quarter, an expected return of 292 million total users should be expected. Based on the correlation we can infer that streaming services produce more content to keep and attract more users to their service. This may have an adverse effect on cinemas, as cinematic content can be watched locally too. Pearson's R2 was also taken for the relationship between TV decline and user growth, 0.92 shows an extremely strong negative correlation.

To determine if the box office is truly being affected by streaming services, the bar and line graph above provides quantitative trends based on the number of ticket sales and the global yearly box office throughout the last 26 years. By taking a sample of 26 years any decline in cinema attendance can be correlated with the birth of the streaming platform in 2007. The graph shows slightly declining ticket sales, presumably due to the increasing ticket prices - this can be inferred as the global box office still rises substantially during this period. The primary catalyst for the downfall of movie chains is the COVID-19 pandemic. This period saw the industry lose 81.8% of its year-on-year growth. This calls into question the rigidity of this business model and whether this industry will maintain consumer trust as the audience comes out of lockdowns. The graph above is interactable. Hover over the bars to see percentage changes of global box office revenues year-to-year.

How has the COVID-19 Pandemic affected the way people view the movie-going experience?

The COVID-19 pandemic has had a sizeable impact on both the streaming and the movie industry. Even though, large datasets do not currently exist outlining the progress as it pertains to key lockdowns within the pandemic. Another important facet is audience perception. As audiences become less afraid as they progress through the pandemic, their opinions will differ accordingly in support of outings to events and movies. NLP was used on a corpus of publically available tweets to gather public opinion data to analyse such trends. The data was gathered using several different search terms. One set of three terms - "going to the movies", "watching a film in the cinema", "going out to the movies" in search of opinion on movie theatres and attendance, whilst the other set focused on streaming services - "streaming movies", "watching on Netflix" and "lockdown streaming". These phrases were all chosen to be inconducive to any biased result, whilst still gathering polarising public opinions.

The 3 pie charts above represent the share of fear against data showing other opinions. This visualisation visualises the change in fear within the general audience when discussing going back to the movie theatres. There were 299 tweets showing fear and unpleasant speech during 2020. With a substantially larger discussion occurring on this topic during the pandemic and an increased level of risk. The unwillingness of the general population can be justified. To visualise what this fear has done to the box office, the next graph outlines the sentiment as it trends throughout the COVID-19 pandemic period.

The polarity is the measure of sentiment from [-1,1], signifying unpleasant to pleasant speech. The average of each tweet within each month was taken and plotted as a trend above. The bar and line graph above displays a noisy trend, with no clear patterns or features to be distinguished. However, there is a sharp decline during 03-2020, this is the period where lockdowns were first introduced to sizeable regions. The box office revenue is represented as domestic United States revenues, as monthly box office revenue was not recorded globally. Sentiment managed to hold after this period for around 2 months. During this period the box office reached all-time lows of $52015. As public sentiment improved further improvements could be seen at the box office, this may have been due to high profile blockbusters like Tenet 08-2020 or Wonder Woman 1984 12-2020 releasing around these times. The visualisation also shows that as the audience enter 2021, public sentiment begins to reach pre-pandemic levels, with the rest of the box office following slowly behind. This may be due to the anticipation of previously pushed film slates to previous years. So far only sentiment data regarding movie theatres have been visualised. To observe any correlations that streaming service sentiment has on public opinion on movie theatres, the following scatter plot was made. This scatters plot visualises the average sentiment of each subject within each month. There is no clear relationship to be shown here, with Pearson's R2 of 0.14.

From the results and the visualisations in this investigation, it can be perceived that streaming is not severely affecting movie theatres in the same likes as the television industry. Major declines in box office performance were mainly the result of audience perception within an uncertain time.