By responding directly with this data-driven hook, TUI managed to completely turn the opinion around. People appreciated TUI's approach and this was immediately reflected in a large number of positive messages (which made the sentiment more positive). A sentiment analysis is a good example of a way in which you use the power of social data to draw a conclusion about the effect of a campaign.
Sentiment analysis for TUI seen in Coosto. The turnaround from negative to positive sentiment shows that the consumer appreciated TUI's hook.
This sentiment analysis first finds a dataset of messages via social media. In the case of TUI, these are all messages about the TUI brand, but also related words such as Arke and for this campaign 'lead lion'.
Then an automatic system (in this case Coosto) looks hongkong cellphone number at the words from these messages and to what extent they say something about the opinion of the author. For example, the message below is given a positive sentiment based on the word combination 'Nice reaction'. This positive sentiment indicates that the author in question has a positive attitude towards the campaign and therefore TUI.
All well and good, you might think, but what does TUI gain from this? First of all, it gives TUI marketers direct feedback that the efforts made are being received positively. In addition, analyses can then be made of the positive and negative messages. In order to prevent the lead lion from being won more often, organisations such as TUI can look at trends in the negative and positive messages. Lessons learned from these trends can be used to optimise future campaigns. The same can of course also be done for competitors and the greater brand reputation.