Everything starts with a briefing. Once the objectives are shared, we create a customized listening structure and identify the characteristics of data we are looking for in order to establish metrics and KPIs. Then the data grabbing process kicks off and the magic begins: an outstanding quantity of data is analyzed by our Learning Machines, instructed to extract only the most useful information. Following the processing phase, our analysts perform a strict quality control of the information collected, interpret it and create the final report.
TEIA is able to listen to people’s voices beyond physical and language boundaries, to scientifically isolate only what concerns your brand. This will make it easier to take decisions and measure their feedback. Because when you improve the efficiency of your company’s efforts, this translates into, or more simply, facilitates the achievement of business objectives through increased and synergistic use of the social media and digital ecosystems.
Once we shared the analysis objectives, we build together metrics and KPIs to be presented to our customers. They may consist of purely numeric or semantic parameters. As for the former, they include volumetric measurements, occurrence count and variation trends calculation. They are always related to their period of observation, or the past. Our analysis can extend back in time to the origins of the communication channels examined (for Facebook back to 2004, for Twitter to 2006). In this scenario, TEIA stands out for its data research capacity and Big Data processors. We know no geographical or language boundaries, as our researches involve, depending on requirements, Social Networks, Forums, Blogs, Reviews, Feedback, Comments and News.
In case of semantic metrics, we instruct our machines (Learning Machines) to comprehend text research. Our colleagues made of “binary codes” analyze comments, opinions, reports and, generally, any buzz generated by discussions according to survey drivers previously shared with the customers.
E.g. “This cookie is very tasty, but it has too many calories!”
What is the opinion on the product?
It depends on what we are looking for, perceived value on taste or genuineness. Every analysis is different, just like customers are looking for different things. Data could be the same, but their informative content could be different. The algorithms we use are specifically designed to detect such information in any form, including sarcasm.
TEIA always sheds a light only on what is useful to listen, and provides specific measures to build your social media-digital strategy.
Our technology allows for the definition of extremely complex Social Metrics and to navigate inside entire organic conversation threads, extracting any kind of information. Alerting processes are very close to human sensitivity, due both to the continuous tracking of individual Topics within the conversation threads and the detection of Emerging Topics. In such a scenario, we can cover the whole Social Business Intelligence chain along the five fundamental pillars of Brand Analysis and Protection, Product/Service Positioning, Customer Service, Campaign Monitoring and Profiling.
Sentiments are not opinions
We’re not going to talk about love, don’t worry. We will talk about the main difference between sentiment Analysis and Opinion Analysis.
Looking for new research methods
The ordinary market researches are meeting new investigation techniques to acquire new information which, otherwise, would have never been detectable.