How Brandwatch is Building Game-Changing New AI Features Powered by GPT
By Oliver ShawApr 20
Learn about how Brandwatch is revolutionizing the industry with game-changing new features powered by GPT.
One of the most acclaimed aspects of the Brandwatch interface is the tool’s suite of robust and pretty charting features, which gives you the ability to display your data from a broad range of criteria and in a wide variety of presentations.
However, never one to rest on our laurels, we’ve been working away in Brandwatch HQ to make the chart component even better and, as of last weekend, we have released some fantastic improvements that mean even greater flexibility when it comes to visualising your data.
The new chart component controls have a slightly different layout, allowing for more dimensions to be plotted.
For example, rather than just volume, you can now also plot metrics such as total Twitter followers, Retweets, Kred Influence or Kred outreach.
Furthermore, our charting component now also allows for more flexibility with what can be plotted.
Our users will already know that Brandwatch has powerful automated and manual categorisation capabilities but, now, those categories can be put to even more good use, as we have added the ability to chart categories against categories (and tags against tags!)
For example, take the popular UK TV show The Only Way is Essex. We took mentions of the programme from the past seven days and categorised them according to chat about some of the popular ‘faces’ of the show.
Then, we searched for the words ‘love’ and ‘hate’ and categorised these accordingly:
That’s a whole lot of love. But, what if we want to see how each of the characters fares in the love/hate debate? Now, by charting category by category, this is possible:
We can now see mentions of ‘love’ and ‘hate’ for each of the characters, which shows that one character – Gemma – definitely divides opinion the most, whilst another – Chloe – is the most loved of the show’s ‘stars’.
However, if we change the Y Axis to ‘Twitter Followers’ rather than volume, we can see a slight change, suggesting that those tweeting their dislike of Arg and Mario reached more followers.
The same can be done with tags and we’ve also added in the option to chart non-categorised mentions against categorised ones, should you want to see those mentions that do not fall into any of your categories.
This is obviously a very basic example, though hopefully this will help you glean the kind of charting possibilities that are now available.
If you have any questions about the new charting component, please contact your account manager or email [email protected]
You can also view the full update document by clicking here.
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