We are excited to announce the launch of our new Review Sentiment features that will revolutionize the way you analyze and understand customer feedback. Our newest features utilizes Natural Language Processing (NLP) to provide you with insights into the key topics and sentiment of individual customer reviews.

With the introduction of new and improved AI tools into the technology space, we saw the need (and want) for features revolving around the power of sentiment analysis. These tools improve upon our review response workflow, and aim to support businesses in responding efficiently to their reviews across multiple sources.

Details

Natural Language Topic Detection

‍Each review is first analyzed to determine the relevant topics present in the custom comments. Reviews contain multiple distinct topics based on the feedback shared.

Sentiment Scale

‍We've constructed our sentiment analysis is based on a five-point scale (instead of the traditional 3-point scale) to allow for a more nuanced understanding of your customer feedback. To make this analysis even more visually appealing and easy to understand, we have color-coded the scale. The colors range from red (very negative) to green (very positive), with shades of orange and blue representing negative, neutral, and positive feedback. The sentiment rating is then applied to each topic and recorded with the reason identified (found in the tool-tip).

What's Next?

Although we are thrilled with the scope and scale of this release, we are even more excited about how clients will be able to use this data. Three additional enhancements are planned for the near future.

First, we need to provide tools for multi-lingual brands to decide how they wish to organize their topics clusters. Second, we are building tools to facilitate the aggregation of topics into core business aspects (think general business categories like "service," "pricing," and "product") based on industry. Third, we are building out robust reporting capabilities so businesses of all sizes can evaluate sentiment scores across topics for individual locations or custom groups.