Summary

 

  • Despite its importance, putting the customer at the center of retail decisions remains a challenging task. 
  • A lack of customer-centricity can lead to decreased loyalty, higher churn, pricing issues, and overall profitability struggles.
  • Utilizing a retail intelligence platform allows teams to break data silos, gain comprehensive insights, and adapt to changing consumer expectations. 
  • These benefits help teams effectively identify profitable customers and understand how to better merchandise to their customer base.  

 


Introduction

 

“The customer should be at the center of all business decisions.” Being customer-centric is something every retailer has heard about in one way or another throughout their career. However, while this idea seems obvious, putting the customer at the center of everything you do and truly understanding your customer can be more challenging than one might think. 

With increased digitalization and hyper-personalization, consumers are changing, and companies need to adapt quickly to meet these evolving expectations. Retailers often struggle with knowing not only what makes you money, but who makes you money. 

 

Is Every Customer Profitable?

 

Becoming customer-centric is vital to success in retail. For example, some customers buy your product at full price and never return a thing, while others are much more problematic. Uncovering who is who and understanding the difference between revenue and true profit lies in knowing your customers. 

However, merchandising to your best, most profitable customers can be difficult, as data often exists in silos, making it challenging to connect insights and see the full picture of a customer or overall performance. When data is disparate, real-time customer data is not accessible to team members who are making crucial product decisions daily, and there is no repeatable process to understand customer behavior. 

A lack of customer-centricity impacts your business negatively in terms of: 

  1. Maintaining customer loyalty
  2. Increasing customer acquisition
  3. Decreasing customer churn
  4. Relying on discounting from incorrect original pricing
  5. Predicting changing customer behavior
  6. Managing excess inventory levels
  7. Building successful assortments that satisfy all customer segments
  8. Growing overall profitability

 

Achieving Customer-Centricity With Retail Analytics Software

 

To overcome these challenges and take a customer-centric approach more easily, you can utilize a retail intelligence platform to break silos and automate previously manual data analysis. 

With access to connected data and comprehensive metrics, you can better understand all aspects that make up your customers, uncover who is profitable versus not, and strategize how to serve them best.

Merchandising to your best customers allows for: 

  • More personalized experiences 
  • Improved market share
  • Better brand image and price integrity
  • Increased full-price sell-through
  • Reduced discounting
  • Minimized excess inventory
  • Fewer returns 

In practice, this might look like using data-driven insights from AI-powered software to uncover what products are driving customers to your site. Then, expose top-performing products on key homepages/landing pages, and bury products with broken SKUs or poorer performance to enhance site merchandising

You can also create and monitor customer segments based on key metrics such as customer profitability, orders, and lifetime value. Access to these metrics allows you to personalize promotions by tailoring an assortment, pricing, and discounting strategy to each customer segment. 

 

A Real-Life Example – Woolworths

 

One real-life example of a company utilizing retail intelligence technology to become more customer-centric is Woolworths. The team partnered with EDITED to ensure it put the customer at the heart of all decision-making processes and identified over ten new assortment growth opportunities to satisfy consumer demand within the first year of the partnership. 

Woolworth’s team also improved its returns by using EDITED’s data to understand its customers and develop more customer-centric strategies – i.e., having the right product at the right price for the right customer, at the right time, in the right location, and in the right quantities. 

 

Conclusion

 

Gartner states, “Retailers that don’t implement critical artificial intelligence (AI)-led merchandising processes now to support the business’s transition to customer centricity will not survive.”

By partnering with EDITED’s Retail Intelligence Platform, retailers can effectively use data to take a customer-centric approach and better understand not just what makes them money, but who makes them money, and how to best merchandise to them. 

Learn more about how EDITED can help your company put your best customers at the center of your business in this webinar or by scheduling a meeting here