This post lays out why artificial intelligence is a game changer in CX, takes a look under the hood at how AI is applied to CX, and explores use cases for how leading edge companies are already reaping benefits from AI applications in customer experience.
Providing an exceptional customer experience consistently is hard. Measuring customer experience and tying it to tangible business outcomes is harder still. This post discusses which customer experience metrics to use and how to improve them to quantify, monitor and enhance your customer experience by taking a journey-driven approach.
This post takes a detailed look at the importance of churn, the different types of churn, reviews different ways to calculate customer and revenue churn and, most importantly, discusses new ways to reduce churn using journey analytics.
The debate on the importance of customer experience is over. Nevertheless, CX leaders are finding it difficult to make the quantitative link between customer behavior and business outcomes, so they can move beyond relying on gut feel and qualitative data to prioritize decisions. In this post, I’ll describe how customer journey analytics can help you improve customer experience and make it actionable by directly tying customer experiences to hard metrics like revenue and profitability.