So you’ve decided to get going with a data driven Customer Experience program. Now what?
The shopping habits of millennial's are a perpetual source of anxiety for retailers. Within the past week, The Economist discussed how established companies can win over these customers, and Deloitte released the results from their 2018 Millennial Survey Report. The crux of the matter is that many retailers are finding it difficult to connect with millennial shoppers. Even when able to sell to them, they are often unable to sustain the relationship. Findings from Centriam’s Retail Study confirm this: millennials are more price sensitive, less likely to repurchase, and 40% more likely to be detractors.
Maggie had a problem. In addition to her "day job" as marketing director for a regional telecom, she had been assigned a pilot project to gather more customer experience data. She knew she could send out more surveys but was wary if that would have any lasting impact. After all, had her company made any changes after five years of reviewing the annual customer satisfaction survey?
Editor’s note: We have already discussed in our CX Lab about the importance of making things easier for customers. We have expanded this conversation to include millennials, as a reason for digital investments by banks, and as an argument for simpler surveys. But as we talk to more and more CX professionals, we are finding a strong hunger for more examples of how to simplify experiences for customers. So today we offer you another example: real-time location sharing.
As outlined in our Community Banking Customer Experience Blueprint, designing an action plan for customer follow-up is the third and final step to launch your customer experience initiative. This blog will discuss key considerations to achieving successful customer winbacks.
Centriam’s Data Science team recently authored a new white paper on the massive opportunities for modern machine learning algorithms to improve customer experience. This paper argued that newer methodologies such as gradient boosting, deep learning, and multi-arm bandits dramatically outperform regression, text analytics, A/B testing, and other methods commonly used today. In line with Centriam’s findings, McKinsey recently reported improvements of up to 62% using deep learning and other modern methods compared to existing predictive analytic methods. Imagine if you could increase your save rate, upsell attachment, or survey completion rate by 62%!
As you begin building a customer experience (CX) program for your bank or credit union, a common first step is gathering feedback from your customers. We’ve found that surveying customers about their interactions across major touchpoints is an easy place to start.