G2

Douglas P.

Business Intelligence (bi) / Trainee

Enterprise (> 1000 emp.)

8/4/2025

"Powerful and Intuitive Tool to Transform Text into Value"

4.5/5

What do you like best about SAS Visual Text Analytics?

What impresses me the most is the visual interface based on pipelines, which demystifies complex NLP processes. The ability to build concept extraction models, sentiment analysis, and topic categorization interactively greatly accelerates development. The native integration with the rest of the SAS Viya ecosystem is a huge differentiator, allowing the insights extracted from the text to be easily used in dashboards in Visual Analytics or as variables in predictive models. Review collected by and hosted on G2.com.

What do you dislike about SAS Visual Text Analytics?

The cost of licensing is, without a doubt, the biggest downside, being a considerable investment. Additionally, the customization of more advanced rules (using LITI syntax) has a steep learning curve and may seem less flexible for those coming from an open-source programming background with Python. The consumption of computational resources can also be quite high when processing large volumes of data. Review collected by and hosted on G2.com.

What problems is SAS Visual Text Analytics solving and how is that benefiting you?

The main problem it solves is our inability to analyze at scale the large volume of unstructured text data we generate, such as comments on social media, open survey responses, and call center transcripts. Previously, this "voice of the customer" was a major blind spot.

The benefit is direct: we transform raw feedback into actionable business intelligence. We can, for example, quickly detect the impact of marketing campaigns, identify product flaws mentioned by customers, and understand the main reasons for satisfaction or dissatisfaction in a systematic and objective way. This gives us much more agility to react and improve the customer experience. Review collected by and hosted on G2.com.