Users today expect fast, easy, reliable, and personalized customer service experiences from the companies they choose to interact with. In a world of ever expanding choices, it is vital to meet the expectations of your users across all interactions, on both your application and with agents. Boosting customer satisfaction has obvious benefits like improving brand loyalty, increasing sales opportunities, and reducing call center costs.
So how do we begin to surface the customer experience users crave? It starts by analyzing and understanding user interaction data, or signals. These signals contain powerful insight into what information is most relevant to your users, how and where they are expecting to find it, and the language they are using to signify their intent. Taking clues from this data, we can then start to make targeted, data-led improvements to both agent-assisted and non-assisted (self service) support with the overall goal of increasing customer satisfaction and improving key business metrics.
In this webinar we’ll cover:
- Why leveraging customer service user interactions is so impactful for fostering customer satisfaction
- Using machine learning and deep learning techniques in a data-led, purposeful manner
- Improving agent effectiveness by giving them the information they need at their fingertips
- Enabling customer self-service to deflect calls and reduce call center costs
- Making your customers happier and boosting customer loyalty