Exceeding Expectations: Four Ways Data Quality Promotes Customer Loyalty
Customer loyalty is at the heart of any business and its brand strategy. Positive customer experiences help retain customers, increase the chance that those customers will buy further products or services from the business, and improve the likelihood that those customers will recommend the business to others. Studies consistently show that the revenue generated by maintaining and enhancing customer loyalty and retention far exceeds that from new prospects.
Yet customer dynamics and expectations continually change at the same time that advanced analytics and machine learning are changing how organizations compete for customer attention and loyalty. Digital transformation is driving significant changes across industries from retail markets to the hospitality and transportation industries and even to financial services including banking and insurance. This transformation is even blurring traditional vertical boundaries where “up to 40% of revenue in the next decade will come from new services”1 that span across a business ecosystem.
A “B2Me” focus (beyond the traditional B2C or B2B view) that delivers individualized or “hyper-personalized” experiences through digital channels is central to this change as new brands disrupt traditional industries. Whether through social and digital outreach, dynamic real-time information, “B2Me brands are in the business of experiences versus just a product or solution.”2
Initiatives to support such transformation and individualized focus to gain and retain customer loyalty are only as effective as the data that underlies these efforts. To connect with customers and offer products and services of interest, businesses must know their customers including where and how to connect with them; how these customers have already engaged with the business; what these customers may be interested in; and how to continually improve the experience of these customers.
This eBook looks at four ways to leverage data quality to facilitate and enhance opportunities to improve customer engagement and loyalty in
support of B2Me personalization and digital transformation. We will explore the criticality of data quality techniques to:
- Capture accurate information in multiple channels upfront
- Connect the right data about the right customers together
- Enrich content downstream with timely and relevant insights
- Utilize the right sets of data to inform advanced analytics and machine learning
1 Atos Look Out 2020+, “Building the intelligent business platforms of tomorrow”, June 2018.
2 Chitra Iyer, “How Hyper-Personalization Takes CMOs from B2C to ‘B2Me’”, MarTech Advisor, May 22, 2018.