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.
Machine learning. Artificial intelligence. Big data. Deep learning. These terms have saturated the modern business lexicon and permeated the zeitgeist. What is your experience with these buzzwords? You’ve certainly read about them and likely talked about them, but have you implemented them? Are you leveraging them to improve your customer experience? Would you like to learn where to begin?
We founded Centriam with a simple vision: help companies get more value out of data to become more customer centric. I strongly believe that organizations who put effort into understanding customer behavior and act on those insights will have a tremendous competitive advantage over the long run. So our goal has always been to develop tools and solutions that drive a customer-centric culture and enable companies to build deeper customer relationships to improve customer experience.
When it comes to improving customer experience, not all retailers are the same. Different business models, customer bases, and product selections prevent a one size fits all approach to providing great customer service. In their recent article titled “The Great Retail Bifurcation: Why the retail “apocalypse” is really a renaissance”, Deloitte divided retailers into three groups—price-based, balanced offering, and premier—to help explain differences in retail business performance post-recession.
You are serious about customer experience (CX). You want to collect feedback. You need to learn more about your customers’ pain points and needs so you can increase their loyalty and retention over time. Great! With a high-level strategy in hand, one of the first technology decisions to make is deciding which customer feedback tool to purchase. The most common practice is to utilize a traditional survey tool since there are many to choose from and they are inexpensive. So you pick one, sign up, upload a list of emails, build your survey, send it out, and wait for the responses to come in. And on to the second survey and so on. Mission accomplished. Well … maybe.