At zenloop, Smart Labels are the key to understanding your customer's written feedback at scale by automatically labelling the comment based on a set of pre-defined keywords.

Benefits to using Smart Labels

  • Cluttering and analysis of feedback is fully automated

  • Easily see and filter for particular labels

  • Prioritise topics based on how often labels for them appear

  • Track the NPS development per label

  • Direct feedback to the right people in your organisation

The Smart Label Flow

1. Language detection → AI recognises the comment language.

2. Parser → The comment is checked for grammar and analysed for meaning. In other words, the parser digests the comment and extracts the message.

3. Removing of stopwords → AI removes unnecessary stopwords (aka filler words) but only to a degree that ensures the meaning of the comment is kept.

4. Stemmer → The stemmer further simplifies the comment by bringing the words to their base form. For example, delivery or delivered becomes deliver.

5. Keyword matching → The keywords from your Smart Label Dictionary are matched to the keywords in the comment.

6. Labelling → When matched keywords are identified, the comment is labeled.

Smart Labels vs Keywords

As the feedback is being processed, the comments are matched with the respective Smart Label using keywords.

For example: the label "price" could contain keywords like "sale", "specials", "value", "cheap" and "expensive". If we find the word "sale" in an answer, we then tag that answer with the label "price"

There is no limit to how many labels can be answered to an answer, but we will only show each label once per answer.

Smart Label Languages

We currently offer Smart Labels in English, German, French, Dutch, Italian, Spanish and Russian.

You can utilize a few, or all, of the languages but each dictionary must be maintained separately.

Smart Label Sentiment

The sentiments of Smart Labels indicates how your customers feel about the topics in the response.

The Smart Labels can carry a positive, negative or neutral sentiment.

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