Companies that bring new products to the market should take into account the actions of competitors. No brand exists
outside the context of the market. Moreover, potential customers have more and more alternatives to meet their needs
every day. How can you understand how your promotion Services for viewing content campaigns worked in such a situation? Were you able to
interest the target audience? In this article, we will tell you how to analyze the promotion of a product and competitors,
using Brand Analytics social media stories, using the example of comparing the premieres of domestic TV series.
To study the information field around the brand and analyze the effectiveness of promotion Services for viewing content
, we created an industry monitoring topic – we used keywords for all major players and the online cinema industry as a
whole. This allowed us to obtain enough data for analysis.
Social media stories in Brand Analytics helped us determine which news items in the context of TV series premieres in the fall of 2024 were discussed by users. For this purpose, the system has a report of the same name, “Stories,” which automatically collects all stories based on social media discussions. The content of stories can be tracked both in real time and for a specific period, and the dynamics of story development can be studied on a graph.
Read more about Brand Analytics Social Media Stories in the article
To quickly identify discussions of specific series in the message flow, we used tagging, and BrandGPT helped us identify the most discussed series of the fall. The analysis period was from October 21 to November 3, 2024, when platforms were most likely actively promoting current premieres before the start of screenings.
We share a step-by-step plan on how to compare promotion with competitors and evaluate the effectiveness of news items – with social media stories.
1. Identifying competitors: which series of the autumn season 2024 have caught Services for viewing content the attention of social media users
Services for viewing content online launch thousands of different products — not only TV series, but also movies and
sports shows. The content is actively discussed by social media users. If the same news item is mentioned in the public
sphere 3 or more times, the Brand Analytics system combines such messages into a story, and AI writes a simple and
clear title for such a story. All stories for the analysis period can be viewed in the “Stories” report.
The AI assistant of social media analyst BrandGPT helped chad business email list to determine which online cinema premieres were actively promoted in October-November.
How a social media analyst can use the smart AI assistant BrandGPT – read in the article
We asked BrandGPT the question “Which series were users discussing?” Of course, during the period of interest to us, the audience discussed not only premieres. Here are the series that, according to BrandGPT, were in the spotlight of social media users in October-November 2024:
For our analysis, we used only messages about series working in partnership to tackle sexual harassment premieres, that is, about the content that online cinemas have just launched for showing:
- “The Dashing Ones” – premiere October 24, 2024;
- “Give Me a Show” – premiere November 1, 2024;
- “Hammer of the Witches” – premiere November 2, 2024;
- “Crime and Punishment” – premiere November 2, 2024;
- “Plevako” – premiere November 7, 2024.
2. We mark the message flow by competitors – we add tags by premieres
In order to select for analysis only the stories by premieres, uae phone number we created the corresponding tags for them. For this, we used keywords by the name of the series. In order to leave for analysis only the stories by the series we need, we set tags by the names of the premieres. After adding tags to the monitoring topic, all messages where a particular premiere was mentioned were automatically marked
The “Stories” report helped us assess how the audience perceived news items and what exactly users discussed in the context of premieres. We selected stories for analysis only for the compared premieres — using a filter by tags.