[Case Study] Netflix: Evaluating the Effectiveness of Trailers

Disclaimer: This Emotion Ai Study has been performed as an Internal Case Study on publicly available material, websites, content, etc. that are open to public use or are present on public platforms to showcase the Company’s emotion ai technology. This study has been performed by internal respondents or company employees with explicit consent taken and in no way, shape or form reflects the preferences of actual customers and is meant for illustrative purposes only. For any further information or clarifications, please write to sales@thelightbulb.ai

About Netflix

Netflix is the ultimate destination for entertainment enthusiasts. Launched in 1997 as a DVD rental service, Netflix has since evolved into a global streaming powerhouse, catering to over 200 million subscribers in more than 190 countries.

With a vast library consisting of award-winning original series like “Stranger Things” and “The Crown” to critically acclaimed films and exclusive stand-up specials, Netflix never fails to deliver an immersive and captivating viewing experience.

But what sets Netflix apart is its mastery in the art of crafting captivating trailers. It’s through these expertly crafted teasers that Netflix has mastered the art of building anticipation, creating a buzz, and ultimately contributing to its massive success.

Recognizing the significance of these trailers, Thelightbulb conducted an internal case study, analysing four of Netflix’s trailers using our emotion AI-powered Insight Pro product.

Case Study Objective

Our objective was to evaluate the effectiveness of Netflix web series trailers in generating a positive emotional response, retaining audience attention, and improving the audience’s perception of the Netflix brand. We achieved this by

• Analyzing the four prominent web series trailers using the Insights Pro’s facial coding and eye tracking tools for evaluating trailers’ impact on viewers.
• Measuring the audience’s emotional responses like happiness, surprise, anger, fear, and disgust towards each trailer utilizing facial coding.
• Identifying which parts of the trailer attract the most attention from the audience using eye-tracking technology. ​
• Measuring the impact of each trailer on the audience’s perception of the web series.

Our research offered valuable insights into the effectiveness of these trailers, allowing the brand to utilize the factors working in its favour and enhance its trailers’ effectiveness to better resonate with its target audience.

Process of Case Study

To get a sense of effectiveness in capturing the target audience’s attention and the emotional impact of Netflix trailers, we used advanced tools like Facial Coding, Eye-tracking and Surveys to collect data for evaluation from participating respondents.

Here’s how we did it:

• Screening– To ensure that the needs of the client were met, the respondents were asked a series of questions.
• Tasking– The respondents were given a common link to visit the stimuli (webpages, videos, pictures, etc.) to record their responses.
• Response– The respondents’ facial expressions, eye movements, and voices were captured by recording their webcams and microphones.
• Surveying– Respondents were asked detailed questions related to their experience using rating scales, MCQs and/or open-ended questions.

Next, we dug deep into the data using our Insight Pro product on multiple fronts:

• Facial coding– Measuring the respondent’s emotions while browsing a website which can influence their behaviour & interactions with the website.
• Gaze Plot– Recording & analyzing user browsing patterns to understand how viewers behaved while watching the ad.
• Heatmaps– Viewing colour-coded representations of popular areas to identify areas where users are spending the most time and highlighting elements that need improvement.

Facial Coding Metrics

Our facial coding metrics are going to play a crucial role in analysing the emotional impact of trailers on viewers. Let’s have a look at all those metrics we measured using facial coding.

• Attention Score / Engagement Score:​ This is a proprietary metric and a function of all emotions demonstrated (with intensity) + head position and eye gaze relative to the screen (algorithm-based calculations).
• Reactions: ​ This is a measure of the intensity of emotions (positive/negative) displayed by the Respondent. This can be considered as a proxy for Involvement​
• Neutral Attention: ​This is when the Respondent displays high levels of attention but low levels of emotions (intensity/emotiveness)
• Distraction:​ This is a corollary / reverse metric of Neutral attention and is signified by head/eye positions relative to screen ​

Emotions that facial coding can detect include contempt, anger, fear, joy, sadness, neutral and surprise.

Trailers Chosen for the Study

Trailer 1: Squid Game

Trailer 2: Stranger Things (S4)

Trailer 3: Wednesday

Trailer 4: Bridgerton (S1)

 

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