Live Social Listening as a Measure of EngagementRelevant topics Research, Archive
Social media usage is still rising. In addition to more and more users (321 million new users since 2019), the time spent has increased: we’re spending more than 40 percent of our waking hours online. As the public is online, so are your customers, and your business should as well.
Listening versus Social Listening
The growing use of social media comments replaces real-life contact and thereby constrains listening to your customers in person. Instead, you have to engage in a new activity for which the term social listening is introduced: listening to your customers on social media. It entails monitoring social media channels for any sentiment, feedback, direct mentions, or discussions of your company, product, competitors, or market-related topics. The field of social listening is growing, not only because more and more is shared on social media but also because the methods to analyze them are developed increasingly.
However, a disadvantage of most researches in social listening is that the information is obtained after the event has happened. One of the latest developments on social media platforms is live streaming. It allows you to engage with your customers in real-time via live comments. Listening to live social media content generated by online consumers offers a great potential source of information because it allows mass participation and is in real-time.
Are you listening - Live?
Zhang, Wang, and Chen (2020) proposed that comment volume over time within consumer reactions to live videos might be an indicator of viewers' engagement. Content shapes the topics and emotions that are shared in live comments, and these shared sentiments most likely will result in highly synchronized commenting patterns in case the content successfully engages consumers. On the contrary, when consumers are distracted, the commenting will be less synchronous and less voluminous.
They introduced the metric called Moment-To-Moment Synchrony (MTMS), which measures the synchrony in live comment volume over time and the temporal variations in movie content.
Synchrony was already proposed before as a metric for engagement. For example, synchrony in brain activity while watching film trailers is shown to relate to attention, recall, and box office revenue. See our earlier article.
Zhang, Wang, and Chen (2020) investigated 507 movies from a Chinese video platform and evaluated viewers' appreciation with the upvotes given by the viewers and the public movie rating from Douban Movie (the Chinese IMDb).
They showed that MTMS could predict 40% of the variance within the Douban Movie rating and 49% of the variance within the number of upvotes given by viewers. This was especially true in the last quarter of the movie, which revealed that movies that stimulate a longer discussion tend to be liked more.
While this seems very promising, there are some considerations before you blindly implement this measure as an indicator of live video performance. The effect was not tested for social media videos but real movies. Additionally, performance indicators that might be important for your business are most likely not comparable to an IMDb score. Nevertheless, MTMS reveals consumer appreciation which might positively impact your brand image!
To start implementing MTMS, you will need computing power to be able to process some features of the videos and evaluate how they impacted MTMS. With live comments, this is even harder since you are extracting the comments live and would want to calculate MTMS fast enough to be able to adapt your video. However, even an analysis done after the live event will reveal the engagement of your consumers and thus enable you to enhance certain aspects in the next video!
- Synchrony in the commenting volume of movies can predict the rating of the movie.
- This is because engaging content gets our sentiments 'in synch' and thereby the comments.
- Analyzing this for your content videos might improve the engagement of your customers.
Most likely, you'll recognize that vague feeling when talking to a customer support chat service, that the "person" you're chatting with might actually be a computer.
Indeed, the market size of chatbots is expanding: starting at $250 million in 2017, it will be more than $1.34 billion in 2024 (Pise, 2018). A chatbot is an automated speech generator that can respond to both written and auditory text. More than 21% of US adults and even more than 80% of generation Z (born between 1996 and 2010) use voice/text bots for information search and shopping.