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?
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%!
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?
Scott Brinker's most recent Marketing Technology Landscape famously touts 5,381 different software solutions. Software choices are obviously growing, but this abundance of choice fuels confusion. This bewilderment is further fanned by aggressive marketing and an alphabet soup of technology acronyms.
Data-driven decision making. We all aspire to it. Whether it’s in Customer Experience management, targeted marketing, deciding which candidates to hire, choosing a new car, or picking the teams in your March Madness office pool.