Text analytics isn’t straightforward – but we’ve got it sussed.
Consider the phrase “barely audible”. For many of our automotive clients, this phrase is categorised as a negative:
“I plugged my phone into the bluetooth system and it was barely audible”. Ie, the Bluetooth system wasn’t enabling the customer to hear their phone = a negative comment.
However, for one of our newest clients, whose business is electronic white goods, this phrase needs to be categorised as a positive:
“I switched on my new dishwasher and it was barely audible”. Ie, the dishwasher ran very quietly = a positive comment.
So how does the Feedback Ferret text analysis machine, that has been taught automated rules, understand whether the phrase “barely audible” is a positive or a negative?
It’s all thanks to the “machine + human” approach. Through rigorous quality control and ongoing updates to the coding of phrases, humans intervene in the automated process to develop and evolve the machine to correctly code ambiguous phrases.
With accuracy rates around 93%, our clients are often astounded by how the Ferret understands complex phrases that appear in their customer feedback.
By Piers Alington, Managing Director