Explore how successful your text predictions are in predicting topics, entities, and sentiments in the messages that come through your conversation channels, such as, emails and chats. Gain insights by reviewing the statistics for your text predictions.
- Open the text prediction:
- In the navigation pane of App Studio, click Channels.
- In the Current channel interfaces section, click the icon that represents a channel for which you want to configure the text prediction.
- On the channel configuration page, click the Behavior tab, and then click Open text prediction.
- On the Analysis tab, select the outcome that you want to
- To view a summary for all the outcomes, click Overview.
- To view the statistics for topic detection, click Topics.
- To view the statistics for sentiment detection, click Sentiments.
- To view the statistics for entity detection, click Entities.
Each tab contains charts that show performance measures that are relevant to the selected scope. For more information about the charts that are used for analysis, see Text prediction analysis charts.
- In the Language field, select the language
- To see the results for a specific language, select that language.
- To see the results for all languages that are configured in the prediction settings, select All.
- In the Time frame field, select the period that you want
The following periods are available:
- Last 7 days
- 7 days of daily data.
- Last 30 days
- 30 days of daily data.
- Previous month
- Daily data for the previous month. For example, if today is 15 March 2021, then the charts show the daily data from 1 February 2021 to 28 February 2021.
- Last 3 months
- Last 13 weeks of weekly data. The charts show 13 dates and each date corresponds to the Sunday of that week. All days that follow a Sunday are captured in the data for that Sunday. For example, the data for 1 March and 6 March 2021 is aggregated and stored in the 28 February date as weekly data.
- Last 12 months
- Last 12 months of monthly data. The charts show 12 dates and each date corresponds to the first day of the month. For example, the data for 5 March and 15 March is aggregated and stored in the 1 March date as monthly data.