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Text prediction analysis charts

Learn how to understand the performance charts on the Analysis tab of a text prediction. Monitoring predictions is a source of valuable information about the messages that come through your conversational channels.

Use these insights to address the needs of your customers, for example, by reacting to a spike in support requests. Find out how you can improve your prediction to get more accurate results.

Overview

The Overview tab contains the following charts:

Prediction calls
This chart shows how many times over the selected time frame the prediction analyzed text in the selected languages. The x-axis shows the dates on which prediction calls were made, for example, the last seven days. The y-axis shows the prediction call counts for different languages. When you hover over a date, you see how many times the prediction analyzed each language.
Prediction calls and throughput
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Throughput
This chart shows the average execution time of a prediction run (throughput) for all prediction runs over the selected time frame and for the selected languages. The x-axis shows the dates for the selected time frame. The y-axis shows the throughput time in milliseconds. Each line in the chart represents a prediction language.
Most frequent topics
This chart shows the ten most frequent topics. Each bar on the y-axis represents one of the topics. The x-axis shows the topic count. The blue part of a bar shows the number of times that the prediction detected the topic (success count). The green part of a bar shows the number of times that feedback is given for the topic (error count). The bars are sorted from top to bottom based on the highest error-to-success ratio.
Top entities
This chart shows up to the ten most frequent entities that the prediction detected over the specified period. The x-axis shows the number of entities. Each bar on the y-axis represents one of the entities. The bars are sorted from top to bottom based on the highest entity counts.
Sentiment distribution
This pie chart shows the aggregated number of times that the prediction detected each sentiment over the specified period. The slices of the pie correspond to the three sentiments: positive, negative, and neutral.
Average number of words
This chart shows the average number of words in the text that the prediction analyzed for the selected languages over the specified period. The number of words equals the number of tokens in the text. For example, in the text I want a home loan., the number of words is 6 (punctuation marks are also tokens).
Average number of words and characters
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Average number of characters
This chart shows the average number of characters (document size) for the text that the prediction analyzed for the selected languages over the specified period. The number of characters is calculated by using the text.length() query. For example, in the text I want a home loan., the number of characters is 19.

Topics

The Topics tab contains the following charts:

Topic distribution
This chart shows the topic distribution over the specified period. The x-axis shows the dates for the selected time frame. The y-axis shows the topic count. The lines in the chart correspond to the top ten most frequent topics.
Topic distribution
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Topic feedback distribution
This chart shows topic feedback distribution over the specified period. The x-axis shows the dates for the selected time frame. The y-axis represents the number of times that the prediction received feedback for a topic (feedback count). The lines in the chart correspond to the top ten topics with most feedback in that time frame.
Topic error rate
This chart shows the topic error rate over the specified period. The y-axis represents the error rate, which is calculated as (error count/topic count) * 100. The x-axis shows the dates for the selected time frame. The lines in the chart correspond to the top ten topics with the most errors in that time frame. When feedback is given for a topic and the feedback topic and the detected topic are not the same, then an error for that detected topic is recorded. If the feedback topic and the detected topic are the same, then no error is recorded, and only the feedback count is updated. The following table shows an example of when errors are recorded:
Detected topic Feedback topic Topic for which an error is recorded
Action > homeloan Action > changeAddress Action > homeloan
Action > homeloan None Action > homeloan
Action > homeloan Action > homeloan None
None Action > changeAddress Action > changeAddress
Most frequent topics
This chart shows the ten most frequent topics. Each bar on the y-axis represents one of the topics. The x-axis shows the topic count. The blue part of a bar shows the number of times that the prediction detected the topic (success count). The green part of a bar shows the number of times that feedback is given for the topic (error count). The bars are sorted from top to bottom based on the highest error-to-success ratio.
Most frequent topics
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Topics with highest percentage errors
This chart shows the ten topics with the highest percentage of errors. The x-axis represents the count of topics. The y-axis shows bars that represent the topics. The blue part of a bar shows the number of times that the prediction detected the topic (success count). The green part of a bar shows the number of times that feedback is given to the topic (error count). The bars are sorted from top to bottom based on the highest error-to-success ratio.

Sentiments

The Sentiments tab contains the following charts:

Sentiment over time
This chart shows the sentiment distribution over the specified period. The x-axis shows the dates for the selected time frame. The y-axis shows the number of times that the prediction detected a particular sentiment. The lines in the chart correspond to the three sentiments: positive, negative, and neutral.
Sentiment over time and sentiment distribution
text-pred-sent-over-time-distr icon
Sentiment distribution
This pie chart shows the aggregated number of times that the prediction detected each sentiment over the specified period. The slices of the pie correspond to the three sentiments: positive, negative, and neutral.
Sentiment feedback distribution
This chart shows the sentiment feedback distribution across the specified period. The x-axis shows the dates for the selected time frame. The y-axis represents the number of times that the prediction received feedback for a sentiment (feedback count). The lines in the chart correspond to the three sentiments: positive, negative, and neutral.
Sentiment error rate
This chart shows the sentiment error rate over the specified period. The y-axis represents the error rate that is calculated by (error count/sentiment count) * 100. The x-axis shows the dates for the selected time frame. The lines in the chart correspond to the three sentiments: positive, negative, and neutral. When feedback is given for a sentiment and the feedback sentiment and the detected sentiment are not the same, then an error for that detected sentiment is recorded. If the feedback sentiment and the detected sentiment are the same, then no error is recorded, only the feedback count updated. The following table is an example that shows when errors are recorded:
Detected sentiment Feedback sentiment Sentiment for which an error is recorded
Positive Negative Positive
Positive Positive None

Entities

The Entities tab contains the following charts:

Entity distribution
This chart shows the entity distribution over the specified period. The x-axis shows the dates for the selected time frame. The y-axis represents the number of times that the prediction detected a particular entity. The lines in the chart correspond to the top ten frequent entities over that time frame.
Entity feedback distribution and overall feedback rate
text-pred-feedb-distr-rate icon
Entity feedback distribution
This chart shows entity feedback distribution over the specified period. The x-axis shows the dates for the selected time frame. The y-axis shows the number of text prediction runs that received feedback for entity outcomes. If feedback is recorded for one or more entities that were detected by a single text prediction run, the feedback count for that run is 1.
Overall feedback rate
This chart shows the overall feedback rate over the specified period. The x-axis shows the dates for the selected time frame. The y-axis represents the feedback rate that is calculated as (feedback count/prediction count) * 100. The prediction count is the number of prediction calls with entity detection selected.
Top entities
This chart shows up to the ten most frequent entities that the prediction detected over the specified period. The x-axis shows the number of entities. Each bar on the y-axis represents one of the entities. The bars are sorted from top to bottom based on the highest entity counts.

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