Monitoring

Tone analysis is the process of understanding and identifying the emotional tone or attitude expressed in a message.

The primary purpose of tone analysis is to gain insights into the emotional state of the writer to understand how they're feeling about a specific subject or topic.

Leveraging the platform's tone analysis capabilities allows users to be proactive in customer experience management, and can help users anticipate and address customer needs based on the emotions expressed within their communications.

Label sentiment is typically only appropriate for customer feedback related datasets. This is because they contain many more identifiable expressions of sentiment than other datasets, which tend to be much more neutral by nature.

For all other use cases (e.g. email inbox analysis and automation), tone should be used because the emotional tone expressed in a message may not simply be a positive vs. a negative sentiment. It could be a complex spectrum of emotions, better represented by a scoring system. The majority of communications in these datasets are also neutral in tone, which is not captured by label sentiment analysis.

Communications Mining's tone model is trained to look for specific expressions of sentiment, both positive and negative, and aggregates them up into an overall 'tone score' between -10 and 10.

This score then becomes a filterable / queryable property for each message, and can be aggregated up at different levels in Reports.

Additionally, the tone score is used as a contributing factor in generating Quality of Service (QoS) scores.

Step 1: Ensure that you have the right permissions to enable QoS ('Quality of Service')

Step 2: Turn tone in the dataset. This can be enabled in the dataset's settings page at any time.

The platform combines the overall sentiment, i.e. tone, and impact of intents in every message to automatically compute a configurable Quality of Service (QoS) score for each message. It also enables real-time QoS dashboards and alerting based on predefined thresholds.

This functionality has many useful applications, including (but not limited to):

The QoS feature helps to ensure that customers are provided with the highest quality of service, whilst identifying priority areas for improvement. It allows managers to measure agents’ performance, prioritise their work and drive timely interventions.

The platform automatically calculates a Quality of Service (QoS) score between -10 and 10 for every message. It does this by combining the predicted tone score (also -10 to 10) with the combined impact scores across label predictions (weighted by prediction confidence).

Label impacts make up the majority of the QoS score, with tone representing ~10% of the score.

Step 1: Ensure that you have the right permissions to enable QoS ('Quality of Service' AND 'Pre-trained labels' where applicable)

Step 2: Turn on pre-trained labels, on key QoS intents that are applicable to your use case. These can be made trainable or non-trainable.

Step 3: Turn on tone analysis (tone is incorporated into the QoS score). This can be enabled in a dataset’s settings page (accessible via the top navigation bar), on the 'General' tab.

Step 4: Change the label impacts. Every label can be assigned an impact score from -10 to +10 (many are typically left at 0).

You can change the QoS label impact by clicking into a label's settings (via the Explore tab, on the taxonomy bar on the left-hand side), and adjusting the QoS slider on a label.

We can use QoS within the following Communications Mining product features:

The platform provides real-time alerting capabilities, allowing users to define issues that impact their clients, processes and service quality, and be alerted each time they occur ( e.g. risk events, client complaints, long-running issues, breaks, etc.). These notifications are currently available on the platform only (API integration will be available soon).

This functionality has many useful applications, including (but not limited to):

The Alerts feature gives users the visibility into the recurring or high-risk issues within their communication channels. It also enables them to monitor unresolved issues and once the issue is fixed, mark them as resolved.

Alert Centre (within the admin console) houses both the Issues and Alerts pages. Once set up, alerts trigger issues when their criteria are met, and these are tracked in the Issues page.

Active issues will track how many times an alert was triggered whilst the issue remained unresolved. When an issue has been investigated and addressed, it can be marked as resolved. If the alert is triggered again in future, a new issue is created.

Step 1: Permissions: Users need Alerts Admin to create, modify and delete alerts and View Alerts to view alerts and issues raised by them. Please ensure that the appropriate permissions have been assigned.

Step 2: Go to the Alert Center (accessible via the Admin console). Alerts are created and updated in the Alerts page within Alert Centre

Step 3: Link your alert to dataset(s). Alerts are linked to a primary dataset (to determine label filters available) and then any number of additional datasets that you have access to within the tenant

Step 4: Select your alert type. Current alert types are for volume changes, or changes to average quality of service scores

Step 5: Select your filters. All the usual filters can be applied to determine which messages are in consideration for each alert

Alert previews: When setting up alerts, users can preview how many times the alert would have been triggered in a past time period, e.g. 6 months

There are 2 types of alerts available: alerts linked to email volumes and alerts linked to average quality of service scores.

To create an alert, click on the New alert button in the Alerts page.

For each alert, you need to specify:

Now you can define the alert's conditions.

Our Alerts functionality enables you to customise individual alert's conditions based on your business needs and objectives.

Firstly, you can choose between the volume based or QoS based alerts:

Secondly, you can indicate your desired level of increase or decrease; and specify the exact value / percentage:

Thirdly, you can select your preferred time period:

Finally, you can define your ideal comparison benchmark:

Our objective is to create an alert that gets triggered each time the average QoS score drops by 0.3 within a single day, compared to the long running average.

This particular alert would have triggered one issue in this period; and the issue is still ongoing.

All existing alerts can be edited or deleted, by clicking on the pencil or bin icon next to its name.

We can use QoS within the following Communications Mining product features:

The platform will show you all identified issues, triggered by alerts, in the Issues page by default. However, you can filter on the Active or Resolved issues. Active issues is often used to track all unresolved issues, whereas Resolved issues enables you to keep an audit trail of all past issues.

Active issues can be marked 'resolved' once investigated and fixed. Resolved issues can be re-opened if needed.

Additionally, each issue contains relevant alert details, as well as all messages that match the alert. These can be accessed by clicking on the respective arrow icons.