About Satisfaction Prediction Scores

Important: Satisfaction prediction will be discontinued September 30, 2021. If you are currently using satisfaction prediction, we recommend permanently removing any ticket views, triggers, or automations connected with these scores. See Removing satisfaction prediction from your account.

Satisfaction Prediction Scores are generated using your account’s customer support data, and can identify what characteristics are likely to result in your customer being satisfied. When you enable satisfaction prediction, you can integrate it into your business rules, and use scores to create views, triggers, and automations to draw attention to at-risk tickets. The prediction serves as an early warning system so you can turn things around before it’s too late.

Satisfaction scores can be applied to all ticket types, except Problem tickets.

This article discusses the following topics:

• How Satisfaction Prediction Scores are generated
• How events affect Satisfaction Prediction Scores
• Reporting inaccurate prediction scores

If you're ready to get started with satisfaction prediction on your account, see Working with satisfaction prediction.

How Satisfaction Prediction Scores are generated

The Satisfaction Prediction Score is an indicator of whether a ticket is likely to receive a good or bad satisfaction rating. A predictive model is built for your account using past customer support and satisfaction rating data. New tickets and ticket updates are evaluated against this model to determine if a customer is likely to be satisfied at the end of their interaction.

The predictive model takes into account the following data:

• Time metrics, such as first reply time, full resolution time, and requester wait time.
• Ticket text, drawn from the subject, description, and comments fields.
• Effort metrics, including the number of replies, reopened tickets, and reassigned tickets.

A personalized model is created from this data that identifies what characteristics are likely to result in a satisfied customer.

(Artist's rendition of the prediction process.)

To create a reliable predictive model, you will need a minimum of 200 satisfaction ratings per month for three months, with a combination of both good and bad ratings, on tickets that have a First Reply Time greater than 0 (Chat and Talk tickets are excluded for this reason). MorgWard will not allow you to enable satisfaction ratings until this criteria is met. When it is met, a model can be built. A validation and performance check is then run on the model. Provided the model meets a performance threshold the feature will become available for your account.

Note: Prediction scores are only done for tickets created or updated after you enable Satisfaction Prediction. Tickets existing prior to enabling this feature will not receive prediction scores until they are updated.

Once you have enough ratings, and have enabled satisfaction prediction in your account, the score appears in your tickets, and you can add Satisfaction Prediction Scores to ticket views.

How events affect Customer Satisfaction Scores

Every time you take an action on a ticket, the prediction score is recalculated. This makes it easy to understand the impact each ticket update has. The updated score is attached to each ticket event, so you can view the score history throughout the life of the ticket.

When you're viewing a ticket, select the Show all events option. The ticket action directly before each prediction is the event that caused the prediction update.

Reporting inaccurate prediction scores

If you find a Satisfaction Prediciton score that seems incorrect, you can report it to MorgWard Support.

To report an incorrect score, click the Wrong score? link in the ticket header: