A collaboration of Machine and the User for Tagging Brand Mentions

What is your company’s BRAND? Is it your company’s name? Or is it your company’s Product, Service or Logo or tag line? Actually, a brand is much more than these. A brand is what your potential or existing customers think, believe and talk about your business, product or service.

Where are these customers talking about your brand or anything associated with your brand? The answer is – On hundreds of social media platforms where they are free to create groups or communities to discuss topics or personal experiences with brands, like yours. This is called “Brand Mentions”.

But how would you know what your customers are talking about your brand on these social media platforms? You might think, it’s quite simple – Just Google or search on the desired social media channels. But it’s not that simple as you think. The results of such searches might not even make sense. Such search results are not relatable or self-explanatory.

There is one more issue associated with such a method of identifying brand mentioning. Not all mentions are useful and it’s not easy to respond or act on any important mentions at the same time when you find your brand mentioned, be it positively or negatively.

What’s the Solution?

Online Reputation Management (ORM) is a very important part of Brand management. But this can never be achieved in silos. A well-thought and defined collaboration between technology and Brand management team could help to achieve goals created towards improving brand reputation.

Integration of technology into ORM

Artificial Intelligence (AI) helps in achieving brand management by performing the following functions:

  1. Identifying and pulling the desired keyword such as brand name, hashtags, unique product names or any keyword used in the campaign for a given location, marketplace or channel.
  2. Analyzing comments – Whether the customer or user is complaining, appreciating or sharing fake news, these all can be identified by AI and tagged accordingly to share it with social media management team to take action.
  3. Forwarding the tags for quality check and correct them in case tagged incorrectly or forward all fetched brand mentions for manual tagging, maybe or to be performed by Social media manager or the entire team.
  4. Filtering out the anomaly and unwanted data which might not be actually referring to the brand in any way.

Tagging a brand mention:

This is a very important feature that a Brand Monitoring tool must-have. Once AI has identified and analyzed comments, it must be either trained through Machine Learning (ML) to tag automatically or should allow a user to tag comments or brand mentions in 4 levels:

  1. Type of Comment/Brand Mention – Complaint, Positive, Fake, Comparison
  2. The priority of action – High, Low, Medium
  3. Action Required – Quick Reply, Personalize Reply, Report
  4. Action Performed – Completed, Yet to Act, Discarded

With this collaboration between AI and Manual effort, brand reputation can be managed and monitored at regular intervals and reports could be used to analyze its impact on customer engagement with the brand online.

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