Keatext is a CX analytics solution that provides AI-based predictive recommendations to improve customer satisfaction.
Get recommendations from your customer responses like reviews, open ended surveys, and contact center tickets to support data-driven decisions and be a more customer-centric organization.
Bring forward decisions with impact: Zero in on opportunities to increase ROI and identify strengths and weaknesses from your customer data
Monitor every stage of the customer journey: Build a complete view of what drives customer satisfaction and discontent
Automate how you generate customer intelligence: Uncover customer insights you can act on without any heavy lifting
Key features
The application is cloud-based and requires no advanced setup or training to start getting insights.
Keatext is trusted by companies in over 10 industries including Lenovo, Intuit, and Intelcom. By using the platform, clients not only improve their customer experience KPIs but help their organization become more customer-centric.
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Based on our record, Pandas seems to be more popular. It has been mentiond 198 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience. - Source: dev.to / 13 days ago
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method. - Source: dev.to / 7 days ago
Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail.... - Source: dev.to / 2 months ago
Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts. - Source: dev.to / 5 months ago
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 5 months ago
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OpenCV - OpenCV is the world's biggest computer vision library