Apportioning Knowledge Article deflection success by category

[Chris Armstron1]

Hi All,

We're using the Knowledge article deflection metric.

Formula: customer has viewed a knowledge article and not raised an incident within the next 24hrs = 1 deflection

We can see that there appears to be quite a lot of successful self-service taking place. It's recently sharply increased because we've added AI search to our Virtual Agent so that it provides knowledge articles in the conversation, leading to more customers seeing the articles.

However, we would expect to see a reduction in calls to the IT Helpdesk as a byproduct of increased self-service success - But we cannot see an overall reducing in call volumes. Our management is keen to see this as a tangible benefit of self-service - reducing calls. We would like to be able to view knowledge article deflection on a more granular level to see if there are smaller correlations between increases in deflection for individual topics, such as iPhone, printing etc. 

Is anyone aware of a way to find this information without additional customisation or configuration of the product?

Kindest regards,

Chris

[Carly6]

It might also help to better understand the calls that are coming in - are they New issues or Known issues? If mostly New, then self-service may have little impact on call volume. And then predictive support may be a potential focus.

PAR also helps in finding if support is updating KBAs with customer context for Known issues to make sure they're findable by customers.

Using similar formula to yours for "search success", we also have a high success rate. So then another question is, do we understand customer intent? Were they going to raise a Case to begin with? Or were they just looking to see if something was possible, expanding their own understanding of how the product works, etc. And that I don't know if you can really determine without a survey.