How AI Can Help Customer Feedback Analysis
by David Hunt Data Geek and Analytics FanaticAI and analytics are so inter-related in today’s data frenzy
enterprises that companies are taking the correlation of these two terms to a
different level. Advantages of using AI to analyze customer feedback are that
it’s faster, more accurate and more scalable than manual tagging. And these
factors have many knock-on effects such as more actionable insights, faster
responses and resolutions, better customer experiences, lower churn rates, and
higher profit margins, to name a few.
Scalability
AI-powered customer analytics enables customer
support agents to focus on more important tasks, whether that’s delivering more
personalized responses to customers or creating reports that can be shared with
stakeholders. It also means that you can analyze all customer feedback in
seconds rather than in weeks or months.
Real-time Analysis
We all know the drill. Monotonously scrolling through survey
responses, reviews, social media comments, tagging them, resolving them, maybe
skipping a few, taking a coffee break, back to scrolling – then before you know
it it’s time to sign off and you’ve only got through 200 hundred more pieces of
feedback. This is where machine learning can help. Once you’ve trained your
machine learning model, you can let it run automatically in real-time, 24/7.
Leaving teammates to focus on the results and deal with urgent issues
immediately.
Consistent Criteria
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Created on Nov 27th 2020 03:34. Viewed 262 times.