Born Out of The Need For Simplicity
Sonar was created with simplicity in mind, a platform where users could directly go to what metrics mattered and instantly draw data-driven conclusions. The problem was, a few years back, tools in the market were too complex, slow and focused on global markets - treating all markets the same. This made the results somewhat generic and fail to paint an accurate picture of what was going on digitally in a specific market. In Asia especially, markets, cultures and businesses are extremely dynamic, making this kind of approach obsolete. We knew we had to create something different which was in tune with each local dynamic, yet could be applied on a regional even global scale.
We built a simple, no-nonse platform with a strong backend that covers markets individually starting from local language, social channels, interaction habits to industry specifics. The key is in localization, strong backend and a fast intuitive user interface - getting the right data, lighting fast with unsurpassed accuracy.
Our first commercial release came out in January 2014 to a few selected believers. The response was encouraging. From that moment we started working closely with our early adaptors, finding out what data they need, when they need it and how it should be delivered. Understanding the market is key, while “fitting” the market is a whole different story. After various tweaks, upgrades, backend optimizing, the platform started to gain traction in 2015 - at the same time the need for digital monitoring came more apparent to brands and agencies. Digital budgets had to be justified, which was easy with banners, search and social ads in which ROIs were clear. How would you value “earned” conversations and conversions? posts and activities that you didn’t pay for? How would you go a step further and value conversations that mention your brand but don’t tag your account?
Indonesia, one of the largest social media nations in the world, was our canvas. Being located in Indonesia, we had the luxury to analyze an immense amount of conversations, language forms, different industries and platforms. From this massive canvas, we built an extensive language library which consists of over 3 million articles and tens of terabytes of conversations which currently powers our sentiment analysis database, which only grows by the day. Most importantly, we’ve finally came up with a model that can be replicated to other languages and markets we like to call the “agnostic perception model”.
In digital, it’s all about perception. This where we are and will continue to push the boundaries on.
An Industrial Approach to Sentiment &
Sonar’s key feature is it’s ability to detect, analyze and calculate sentiment in specific language. Currently, Sonar supports sentiment analysis in Bahasa Indonesia, Tagalog, Bahasa Melayu, Arabic and English. We realize that things can get a little complicated when it comes to classifying audience perception over a different industries; as a term in medical and pharmaceutical brands could be positive and a negative or neutral in transportation, for instance.
Our modified NLP approach to sentiment analysis is broken down by industry to solve this issue, which takes into account not only words, terms and entities but also the originating industry the brand or anchor keyword it is tied to. We dub this an industrial approach to audience perception.
Here’s a list of the industries we cover:
Discover Audience Interests & Demographics
The key to a successful conversation is understanding who your are talking to and what they’re interested in. By tapping into their interests, connections occur on a whole different level. If you’re a brand trying to convert your target market into loyal customers or planning to launch a new product or service into an unknown market, market interests and demographics become a vital part of information you definitely need.
In collaboration directly with Twitter, Sonar provides social profiling of author groups based on the following example parameters:
A group of Twitter authors that mention the same keyword
A group of Twitter authors that discuss a topic negatively or positively
A group of Twitter authors from a specific location or city
These user groups can also be defined by any rule set, Twitter handle or pre-defined group within a topic. For a sample of a Sonar interest report, please read our blog post: