Myth 1: I’m using all of the data we have available to us to study churn.
Truth:
While most companies believe this to be true, they’re only thinking about their structured data, forgetting about the unstructured audio being captured by the contact center. The behavioral events contained in the audio provide the missing insight about the customer experience not found in traditional data.
Myth 2: Pricing is always the key driver of churn.
Truth:
Through the analysis of the customer’s experience, interaction analytics has uncovered many drivers of churn for today’s top companies. Unresolved issues often top the list, whether they be service or technical in nature.
Myth 3: Having a save queue is sufficient for addressing churn.
Truth:
A save queue is a great step in providing customers with the correct support, but it is inefficient if you haven’t first studied the types of interactions that will be sent there and equipped agents to deal with them appropriately. Do they have the most effective offers to present to customers, can they overcome technical issues, do they have the correct authority to resolve issues?
Myth 4: I am creating the best predictive models possible by utilizing big data techniques.
Truth:
Predictive models are only as good as the information you put into them, and if you’re ignoring the unstructured data that’s available in your audio, you’re leaving out a big piece of the puzzle. Companies have experienced up to a 30% lift in the accuracy of their models when they add in this resource.
Myth 5: Churn only matters in an oversaturated market.
Truth:
While companies in markets such as telecommunications have a definite focus on churn, all businesses can benefit from having a solid understanding of what drives customers to withdraw their business and what can be done to save them. This is especially true in markets such as healthcare, which are on the cusp of seeing increased competition as changes such as the Affordable Care Act take hold.
