This blog post contains excerpts from the whitepaper Using Artificial Intelligence for Effective Customer Retention, by Retail Pro and AppCard. Download the whitepaper to learn more about how artificial intelligence can help retailers improve customer experience and retention.
The era of customer experience
In the past 4-5 years, the retail industry has undergone major changes and retailers are acknowledging that it is 6-7 times more costly to acquire a new customer than to retain an existing one. This same research shows that boosting customer retention rates by as little as 5% can increase profits up to 95%.
With such incentives at hand, brick and mortar retailers are urged to leverage eCommerce-like data collection and analysis to create a unique customer experience that will keep customers coming back for more.
But this is often easier said than done.
The evolution of customer loyalty
For years, retailers have looked for ways to influence customer behavior, from the early days of paper punch cards to sophisticated, big box SAP and SAS based CRM and ERP systems.
Some retailers pinned their hopes on daily deal sites like Groupon and LivingSocial, only to find out that customer acquisition is significantly more expensive than customer retention and once acquired, they have virtually no useful information about the newly acquired customers.
Since then, loyalty programs have evolved from basic check-in solutions to more sophisticated check-in solutions that were able to communicate with customers via mobile app, text or SMS messages, and email.
While such solutions garnered some initial traction, retailers still yearned for a greater understanding of their customers, including SKU-level transaction details.
Top 2 customer experience challenges faced by today’s retailers
Retailers face two critical challenges in their quest to leverage data for better customer experiences: increasingly demanding shoppers and technology limitations.
- Generation E (Expectations)
Customers—particularly Millennials—have become more informed, less tolerant, and increasingly demanding.Their ever-increasing ability to shop around, research, compare, share, and explore alternative products, prices and options forces retailers to truly know their customers and understand their shopping motivations.Regardless of whether the shoppers are Baby Boomers, Generation X, Millennials or even Generation Z, retailers must realize that all of their customers belong to Generation E (Expectations), where they expect to build a relationship with their favorite brands and be appreciated for their business in exchange for their loyalty.
- Tech limitations
The retail industry’s technological landscape is comprised of web developers, CRM and ERP providers, payment processors, network providers, and many more. But the technology upon which nearly all brick and mortar retailers are still fully dependent is their Point of Sale (POS) systems, which are often highly fragmented and cumbersome. With thousands of different POS providers in the market, and no true standardization, many retailers struggle or fail to integrate multiple data sources and retail channels (Mobile, eCommerce, In-store).Furthermore, while the POS gives retailers access to critical KPIs like daily sales numbers, top selling products, and returns by cashier, but retailers need the ability to associate transactions to an individual customer in an actionable way. This level of insight is integral for retailers to provide a truly personalized customer experience.Related Article: How to use POS data to achieve personalized marketing like the big guys >>
To continue reading more about the challenges and opportunities for improving the retail customer experience, download the whitepaper now. In this whitepaper, we’ll cover:
- The evolution and challenges of loyalty in the era of customer experience
- Leveraging tech to personalize the retail experience for Generation E(xperience)
- A successful rewards program is within reach – fewer coupons, more sales
- The importance of data-driven, personalized marketing