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            Evaluate How Well Your Bots Understand Your Customers

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            Evaluate How Well Your Bots Understand Your Customers

            The Model Management page shows metrics on the quality of your bot’s intent model and individual intent details. Use the information to fine-tune intents and improve how well your bot understands your customers.

            Required Editions

            View supported editions.
            User Permissions Needed
            To build and manage Einstein Bots:

            Customize Application

            OR

            Modify Metadata

            OR

            Manage Bots

            Your bot is only as good as the data that you feed it. To ensure Bot quality, we recommend visiting the Model Management menu often. Our models rate intents based on an F1 Score, which is a statistical term that shows how accurate the model is at predicting correctly.

            The F1 score is defined from 0 through 1, with 1 being the highest possible score. The higher your intent’s F1 score, the more likely that the bot predicts correctly every time it has a conversation. F1 scores combine two metrics:

            • Precision—the number of correct positive results divided by the number of total positive results
            • Recall—the number of positive results divided by the number of total expected results

            To improve your intent’s F1 score, we provided recommendations on the Model Management Page.

            Note
            Note If your model pre-dates the F1 score integration in Einstein Bots, the model requires a rebuild to integrate your data into the new score. In that case, a prompt indicates the need for a rebuild.
            1. From the Bot Builder menu, click Model Management.
            2. To view intent model metrics, display the Model tab.
              An image of the new model management dashboard.
            3. To view the recommendations, click an intent name.
              An image of the recommendations per intent.

              Adding utterances and clarifying intents are great ways to improve F1 scores. It’s also important to frequently integrate new customer data from conversation transcripts to keep the bot current. A minimum of 20 utterances is required to build the model, but more utterances make the model more accurate.

            4. To act on the recommendations provided, click Edit Intent to go to the intent details for that dialog.
              To visualize the accuracy of your intent model, you can use the Einstein Intent Assessor AppExchange tool.
            5. To view model performance in other languages, click Download Model Metrics. Bots with multiple languages have both aggregated metrics and language-specific metrics.
             
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