Products.
Armed with a deeper knowledge of who your true audience is and what captivates them, you can see substantial increases in revenue and admissions. In many cases, we can triple your product sales or more.
COMP ANALYSIS
How we do it:
Instead of starting with numbers, we use emotion to get to the heart of the issue. Emotions such as exciting, heart-warming, fun, or scary.
Then, we develop a reaction profile.
Calculate the relationship between your comps.
Identify which titles are the best comps and set aside those less effective.
We identify the market potential for all possible audiences, so you can build a strategy to maximize your potential audiences and increase your revenue.
With our unique approach to audience analysis, we provide the keywords that viewers use to describe the titles in each cluster, so you know which words to use (and which to avoid).
Whether you’re in development, production, post, or have already released your title, our Comp Analysis can help you find the right comps by using real audience reactions to existing titles. That can help you identify your core audience, understand the dominant themes and result in better audience targeting, strategy, and marketing.
Rediscover Your Audience.
Advanced Features
- Analysis and summary of viewer reactions
- Identification of Nanogenre® themes
- Performance analysis of comp titles
- Comp similarity analysis
- Identification of alternate comps
- Title clustering by distance
- ViewerVoiceTM marketing analysis, including dominant themes, viewer-keywords, Nanogenre collection performance, and words that increase or reduce audience size
- Learn more
DATA LICENSING
VIEWERVOICE™ REACTION PROFILE
All of our analytics are based on the viewer's voice. We've developed an algorithm to determine which words are the most important to distinguish one title from another. These Reaction Words, like gripping and adorable, are full of passion and meaning – capturing your viewers' reactions and interests. Reaction Words also expose fundamental relationships between titles. We use these words and relationships to build our ViewerVoice Reaction Dataset.
USING THE VIEWERVOICE REACTION DATASET
CLUSTER MAPPING
Based on our analysis of viewer reactions, we map the three-dimensional distance of titles to each other and cluster them into groups.
For our comp analysis product, we use these groups to calculate expected revenue and discover the words audiences use to describe each group of similar titles.
Three-dimensional map showing distance of titles to each other within their group cluster, based on ViewerVoice reaction analysis.