When using Scup, you can tag and perform analyses on the sentiments of mentions, videos, and posts collected from your monitoring, contributing to the qualitative as well quantitative analysis of data collection.
It's important for whoever is monitoring to understand the content of the mentions collected, the action of classification and tagging allows this to happen, because once these actions are implemented, it'll be possible to analyze what's being commented on the most in terms of the brand or product being monitored.
What is tagging?
It's a kind of "label" attributed to a mention.
What is a sentiment analysis?
Performing a sentiment analysis specifies whether the mention is positive, negative, or neutral.
Why use tags or sentiment analyses?
When you do a sentiment analysis or tag mentions from your listening, you begin to work with information in a qualitative manner, which is of great importance to the interpretation of what is being said about the brands and products being monitored. You can get a sense of the audience's opinion of the company's products, services and brand. The quality of information can contribute greatly to the understanding of those involved, as well as the prevention of crime.
It's easy to register tags; just go to Settings> Tags > Add Tags. Here, you'll be able to create multiple tags at a time by clicking the (+) on the add tags page.
Tips for working with Tagging and Sentiment Analysis:
- Before starting the work of classification, keep in mind the strategic objective of project.
- Create a document that includes the monitoring information for the team to consult.
- Determine the tags and a description of which subjects can be tagged with a particular tag. Example: Trash tag (everything that is not related to our brand)
- Use keywords to determine the subjects that can be classified by each tag. Example: Delivery tag (delivery time, early delivery, delay, time taken).
- Keep your team focused on the actions of monitored brands and companies in order to determine the best tag in each case.
- In the case of short-term campaigns, use a specific tag for each event so as to obtain more accurate analysis. Example: Fair 1 tag, Fair 2 tag.
- In large campaigns that implement a large volume of automatic rules, creating rules to facilitate team work can help in the work of both sentiment analysis and tagging.
- For example, when a user mentions two products in the same comment and there are specific tags for each product in your plan, create an order of priority among the products: which of these data needs to be more closely observed at the moment? Normally, the products that are mentioned less often should be at the top of the priority list since they should be given special attention.
- The division of tags into groups also facilitates the analysis of data such as: time, who, influencers, feedback, etc. Example: purchase time, usage time, cancellation time.
- When dividing comments among your team, you can create tags for each employee and divide them by creating rules.
- For the purpose of classification, determine what will be considered for each sentiment analysis. Example: will action feedback with the expression "thank you very much" be considered positive?