Today I have been playing with the Qlik Connectors that come free out the box with Qlik Sense SaaS. There is a whole range of additional functionality you can delve into and use to maximise your businesses potential.
One of the most important things we can monitor is customer satisfaction. To showcase how the connectors could benefit your business, I have used the Qlik Sense Twitter Connector as well as the Sentiment140 connector to search for tweets about the NHS. I have then used the Sentiment connector to classify these tweets as positive, negative or neutral.
The twitter connection itself only requires authentication against an account and then to pass it through the search terms you wish to look for
Once this is done, the wizard will generate the script for you and you can then pass the tweets to the sentiment analyser connector to work out if each tweet is positive or negative. The message contains the tweet you want to analyse. For my dashboard, I have built a loop to pass through each tweet as needed.
Once this is done, we can then build visuals. So, what are the outcomes for NHS tweets? With only a snapshot of data, the time analysis does not give a huge amount of information, however I can now use the connector to incrementally load new tweets and classify these, building up day on day. I can see the most prolific tweeters about #NHS and how many followers these users have.
I can also see the most tweeted hash tags in this period that contain our search term ‘#NHS’ to see what are the most talked about topics.
And of course, we can see the sentiment breakdown of all the tweets in this period. The sentiment analyser will try to classify each tweet and give a score. As you can see, most of the tweets came back as neutral, but we can click and select any segment and view all the tweets in this selection.
So, the burning question is what was the major talking points today. The negative is made up of retweets about Dido Harding talking up a Head of NHS role, whereas the Positives were made up by thank you NHS tweets.
We could use this same process for any business to track and make sure that customer satisfaction is rising and communicate directly to the negative tweets to combat any negativity.