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Step-by-Step Guide: How to Monitor AI Predictions
The video below covers how the Wrench.ai platform harnesses the combined power of natural language processing, machine learning, and AI algorithms to analyze your data. Dive into Custom AI Performance Reports to gain insightful predictions, assess model quality, and integrate with your existing data sources.
1. Leverage Combined AI Capabilities:
Utilize the blend of natural language processing, GPT, and machine learning models to get the best of AI technologies.
2. Access Custom AI Performance Report:
This report helps answer crucial questions like identifying potential customers, assessing those most likely to churn, and predicting the highest lifetime customer value.
3. Integrate First-Party Data:
Compare the insights from the Wrench platform with your own first-party data.
4. Evaluate Model Quality:
Examine the prediction's quality, accuracy, and area under the curve. These metrics are valuable for assessing the model's reliability.
5. Receive Data Insights:
The platform provides a breakdown of the data that influenced the prediction. This transparency allows users to understand the factors driving predictions.
6. Check for Top Indicators:
Look for frequently appearing factors in the predictions, such as the Wrench adoption curve or client data models.
7. Assess Value Added:
Confirm that the Wrench platform brings actionable and valuable data to aid decision-making processes and provides relevant messaging recommendations.
8. Deep Dive into Model Analysis:
For a more detailed examination of your model, delve deeper into its health and accuracy. Share these findings with your data science team for feedback.
9. Feedback and Customization:
Contact the Wrench team for feedback, custom lead scoring, and integration with platforms like HubSpot and Salesforce.
10. Request Custom Predictions:
Beyond customer predictions, you can request other insights like potential replies or demo interests. The platform will generate a similar report for these custom requests.
Stay informed, refine your strategy, and ensure that your data-driven decisions align with the insights provided by the Wrench platform.
The document provides a step-by-step guide for monitoring custom AI predictions using the Wrench.ai platform. Key steps include leveraging AI capabilities, accessing performance reports, integrating first-party data, evaluating model quality, and receiving data insights. Users are encouraged to assess the value added by the platform, conduct in-depth model analysis, and seek feedback for customization. Additionally, users can request custom predictions beyond customer insights to enhance data-driven decision-making.