Artificial intelligence (AI) plays a critical role in processing data at scale but is still not adept at understanding the nuances of human conversation. To overcome these limitations, we combine AI and human intelligence. Algorithms are used for certain preprocessing tasks and our Crowd of human contributors filter noise for the conversation that’s high risk, high value, and urgent.

The DataEQ Crowd is a proprietary crowdsourcing platform comprising trained and vetted local language contributors from around the world. Contributors are remunerated for executing micro-jobs that include the verification and categorisation of social media posts and other short-form texts.

Structuring your online conversation yields a robust customer satisfaction metric known as Net Sentiment. Net Sentiment is an aggregated and real-time metric that is a critical component in the quest for an authentic and complete voice-of-customer measurement framework. It is calculated by subtracting the total volume of negative sentiment from positive sentiment.

Leading customer-centric organisations are using Net Sentiment to benchmark against both competitors and past performance, and as an alternative to traditional lagging metrics like Net Promoter Score.

DataEQ applies four meta tags to our data: Risk, Purchase, Cancel and Service. These ensure that you prioritise the most valuable customer interactions. These tags save you time and money. They direct you to the conversation, from within all of the social media noise, that’s high risk or requires an urgent response.

Risk - Mentions that pose an immediate risk or relate to a regulatory framework (e.g. Consumer Duty)

Purchase - Mentions from a prospective customer who wants to purchase your product or service

Cancel - Mentions from a customer looking to cancel their service or not buy from you again

Service - Mentions from a customer that requires service or describes their experience