Understanding your customer or employee experience requires two things: sufficient feedback opportunities for individuals to share their views and the analytical capability to interpret the responses, at scale. Does your business have both?
Traditionally, we have started our experience research work on a qualitative scale; using focus groups and interviews to identify key emotions, and later validating the findings with larger-scale surveys. However, in recent years, more and more customers are choosing to express their views on social media. It has put the power in consumers’ hands to rant (or rave) about brands, products and services. Similarly, more employers are running regular online surveys with colleagues, with some including internal team chat messaging apps like Slack and Microsoft Teams.
So as researchers, we now need ways to analyse the context and emotion of what people are saying at the scale of thousands or even tens of thousands of comments.
We’re using social media and emotional analytics (EA) software to do just that – it’s still in its infancy (in our humble opinion at least!), but it’s making a big difference to the speed and scale that we can operate at.
Rick Harris - Customer Faithful
Right now, we still believe that artificial intelligence (AI) tools rely on human investigators to truly translate context and emotion into actionable insights. That’s why all our customer and employee experience research projects now include social listening feedback, but only when curated by human oversight.
At Customer Faithful, we are developing a particular specialism of uncovering emotional insight from long-hand feedback; not simply a tweet, but a whole page of comment, perhaps posted to YouTube by an individual as a video diary, or by an employee within an annual survey. Own blend of software-enhanced interpretation conducted by qualitative-trained analysts is the best guarantee of quality there is.