In IVR Experiments and Predictive Content, we can optimize the language used by computer-operated phone systems that your customers may interact with. This can help you get customers to the right solution the first time with effective IVR scripts that provide proactive information and guidance. Customers will be more empowered to address issues through self-service or get help from the right agent for the problem. We see results like high first-time resolution and reduced call center volumes.
Learnings from IVR Experiments and Predictive Content
By running an IVR Experiment or Predictive Content, you could learn:
Which descriptive elements in your IVR scripts have the greatest impact on customer behavior, like emphasizing ease of use or touchscreen features, so you can direct customers to self-service options
The CTAs on your customer’s IVR journey that drive the most action, even if the differences seem minor (e.g., “key 1” versus “say 1”)
The top-performing emotions for IVR versus bottom-performing emotions.
Commonly Observed KPIs
We often observe KPIs for IVR Experiments and Predictive Content such as:
Engagement
First-time resolution
Customer satisfaction rates
Cost.
Use Case Example
A leading U.S. health insurer turned to Persado for help with a proactive campaign to promote digital customer self-service for simple issues, so that the business could preserve human agents for more complex calls. Persado generated an IVR script that played for customers while they waited for a call center agent. The script suggested self-service options to submit a claim, find a doctor, print their insurance card, and other common actions. Customers who accepted the offer to use self-service received a text message with a link to the mobile app. Our message emphasized ease and simplicity with language like “fast and simple” and “one-time.” An additional 39% of customers clicked “Yes” to use the self-service options, and 67% percent more downloaded the app, compared to the insurer’s control message. This single message produced $1.7 million in savings for the customer service operation.