The Leading Sentiment
Analysis Enterprise System
Human Sentiment Analysis system for the enterprise, reducing existing automation inconsistencies while streamlining reporting and responses.
A turn-key solution for assessing consumer sentiment, providing brands with the most actionable insights based on their needs.
Comprising ‘human’ and ‘element’ Humanele represents the cornerstone of in-depth sentiment analysis - the complexities
of everyday conversations that get missed by algorithms and computer analysis systems, such as sarcasm, word variance
by demographics and images.
While algorithms and computer generated analyses are helpful and utilized for automation, digital platforms today are experiencing unparalleled changes that impact the true meaning of a conversation or comment string, undetectable by algorithms.
Humanele passes comment strings through real humans, en masse with an average turnaround time of 5-9 hours - irrespective of comment string size.
A platform’s intent dictates comment style, response mechanism, tone, intent and other varying conversational indicators.
The relevance of a platform to an organization’s overall sentiment portfolio has a great deal of dependence on obvious similarities between the platforms aim and the brand itself.
The average platform user, and the target market must be identified in order to create both appropriate responses and to understand the ‘why’ behind expressed sentiment.
Demographics impact how people express sentiment, what platforms they use, the tone used in sentiment, how aggressive/passive they
will be in comments and many more factors. To truly understand sentiment, a user base breakdown is required.
Using demographic information and extracted data not available via platform (such as ethnicity and sexual orientation), Humanele will deliver actionable insights. Using our holistic approach we provide the most accurate assessment of a user’s sentiment portfolio
Through the analysis of historical consumer data, Humanele is able to provide insights into platform and sentiment shifts. This data allows us to generate a predictive model for actionable marketing optimization and brand offerings, increase the chances of purchase and encapsulating that data for future strategic advertising trends.
Through partnerships with several data partners we are able to extract data from an array of enterprise sources using pre-existing relationships and/or assets.
Humanele maximizes sentiment analysis accuracy for when comprehensive reporting is paramount and automated systems will not suffice. Automated sentiment system advancements are approximately 67% effective, however the rapidly shifting digital landscape requires deeper and more granular analysis - made possible by Humanele.
Different demographics assign words different sentiment and meaning. While the word ‘ill’ may sound negative, to users of a certain demographic it is extremely positive - a distinction not possible through the use of an algorithm or machine.
Sarcasm is used excessively by some demographics, and sparingly by others. In order to detect sarcasm, the context of the post, demographics and platform intent need to be analyzed.
Symbols is another case of a specific demographic tool used to convey sentiment. Where some demographics will use the word ‘love’, others will use the image of a heart. Algorithms cannot pick up on these, and the strong sentiment expression is missed.
Naturally, the topic being discussed can widen the expressed sentiments, and narrow them.
Demographics impact how people express sentiment, what platforms they use, the tone used in sentiment, how aggressive/passive they will be in comments and many more factors.
Different events impact the likelihood of sentiment expression between multiple parties and across varying platforms.