Marketers want to get deep insight to their social data - but the increasing use of emojis are skewing data results. Now New York based social listening platform Synthesio has introduced a way for brands to capitalise on the new trend.
The company now supports emoji and emoticon analysis in 17 different languages. This will allow brands to capitalize on usage of emoticons and emojis as forms of expression online, and provide insight and data to strengthen text analysis across datasets with fewer gaps.
Detecting sentiment on both emoticons and emojis will boost accuracy given the number of people that now use emoticons and emojis instead of text to express emotion.
Geolocation data of users using each emoji and emoticon will help brands understand where certain emojis and sentiment are occurring and tailor their messages to those geographies.
Popular emojis and emoticons have been scored and factored against sentiment to provide insight into the feelings behind what people are talking about.
Brands will be able to identify and understand the new popular "visual-languages" of posts using emojis and emoticons to communicate.
This addition gives marketers a further level of insight into what their audiences are talking about online - as well as how they feel about what they are saying.
The company recently announced the launch of Reveal. This dynamic drag-and-drop interface for raw social data allows users to build dynamic pivot tables in order to custom-analyze their business' social KPIs.
Users can navigate their way through datasets to identify trends and hotspots. The tool will allow them to customize their social data and metrics to fit their business needs and get the most out of their social data.
Matthew Zito, Chief Strategy Officer at Synthesio said: "With the incredible volume of analytics and data that marketers and C-Suite executives are receiving about every aspect of their business, it's important that all kinds of data can be mashed together.
There are times when users need to dive even deeper into their own data in a way that they can't through standard, out-of-the-box Social Intelligence metrics."