Tutorial: From Data to Insights for a CX (NPS) Survey
Harnessing Inqqa AI for Enhanced Customer Experience Insights
Explore how Inqqa AI simplifies the extraction of insights from open text fields within customer experience datasets.
Harnessing Inqqa AI for Enhanced Customer Experience Insights
In the rapidly shifting field of customer experience (CX), leveraging sophisticated analytics tools to glean insightful conclusions is paramount. Inqqa AI emerges as a significant resource for CX experts, particularly those handling Net Promoter Score (NPS) data. This advanceda platform efficiently transforms vast data quantities into comprehensible insights, thereby improving the decision-making capacity of customer experience specialists by offering a more nuanced interpretation of customer feedback trends.
The journey with Inqqa AI begins with the necessity to upload the dataset, which swiftly identifies open text fields and essential background information, used later as filters for thorough sentiment analysis and understanding. A typical dataset, often containing over 5,000 full responses, gets dissected into sentences to distinguish multiple themes or topics within each response. This breakdown is essential, providing users with a concise overview and enabling a comprehensive dive into data, thus allowing professionals to concentrate on important areas effectively. Although the segmentation and analysis are automated, users have the flexibility to refine and categorise the data manually for more accurate outcomes in AI-driven insights.
Unleashing the power of reporting and analysis starts with uploading a dataset and selecting relevant languages for comprehensive natural language processing operations. Users can commence their free trial and follow comprehensive how-to videos and tutorials offered by the platform, ensuring a broad understanding of its functionalities.
The platform’s user-friendly interface permits analysts to classify and group similar sections, generally within a 15 to 20-minute period. Topics like ‘price’ or ‘customer service’ can be tagged, with Inqqa AI clustering related segments for more efficient exploration. This approach narrows the focus to the most relevant topics for reports or presentations, significantly reducing the workload associated with manual data processing. The accessible design ensures that even those with limited technical know-how can navigate the platform effortlessly, enhancing workflow efficiency and deriving meaningful results.
Beyond manual scrutiny, Inqqa AI includes an automated option through a GPT model, suggesting relevant labels and themes, thus boosting intelligent agent use in AI-driven tasks. Although this feature offers speed and adaptability, some result variability might occur. Hence, a combination of automated suggestions with manual adjustments is recommended for a consistent and comprehensive analysis. This hybrid approach allows analysts to benefit from both speed and accuracy in data labelling, supplying a full view of the dataset that assists in strategic planning and decision-making processes.
Post-analysis, Inqqa AI offers numerous possibilities for visualising and sharing data insights. Users can create bar charts to highlight significant findings or export themed datasets for further exploration. The platform facilitates insight sharing through immutable links, promoting seamless collaboration, and enhancing AI workflow automation to preserve data integrity. This effective sharing capability positions Inqqa AI as an invaluable tool for CX professionals aiming to elevate their analytical outputs. Furthermore, the ability to export data, including identified themes and statistical samples, allows for offline analysis and reporting, making Inqqa AI ideal for comprehensive data analysis and a versatile option for various analytical requirements.
For those keen to explore Inqqa AI’s capabilities further, the platform provides a wide range of how-to videos and tutorials. These resources are intended to help users maximise the tool’s potential, ensuring the effective extraction of valuable insights from their data. Additionally, the platform’s learning hub offers concise how-to videos focusing on specific functionalities, simplifying navigation and tool usage. The combination of detailed tutorials and quick guides ensures users, whether beginners or experienced, can fully exploit the platform’s features, thereby enhancing their analytical skills. The extensive resources guarantee that users are well-prepared to tackle any data challenges they may face, boosting their ability to contribute to business growth through informed decisions.
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