Unhappy with your sentiment accuracy? Let’s talk data quality and “trusted” AI

Accurate sentiment is the holy grail of social intelligence. It’s up there as a key KPI for business leadership. But there’s a problem - sentiment data isn’t reliable. In fact, at least 35% of all sentiment data is mis-labelled*. Astounding to think that these key KPIs are not in fact, accurate.

We hear from social listening professionals every day that Sentiment is a key KPI for their leadership, but that the sentiment they’re getting “out-of-the-box” can’t be trusted.

What’s the solution? Well, today, you’d naturally think better AI but not all AI is created equal. Not all AI can be trusted. To get to better sentiment accuracy we don’t just need better AI we need quality data. No one really likes to think about data quality (it’s the unsexy part of a social listener's job) but when our leaders are making decisions off the back of our analysis, we need to be damn sure it’s accurate.

So without further ado…

In this webinar, Converseon and their client Delta, break down the issue and explore:

👉 How to measure and understand data accuracy

👉 What we can do to improve it

👉 What that means for sentiment analysis

Our webinars have the best experience when you attend live. But, if you’ve got a conflict in your diary, register anyway and we’ll send the playback after the event.

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