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Insight

Next-Gen Luxury Retail: How to Leverage Data to Lead in Digital

The key to creating personalized experiences in luxury will largely be centered around the retailer’s ability to get data right

Luxury brands have a reputation for elevating traditional retail experiences – from pushing creative boundaries and setting the stage for the next big designer trends, to building vibrant in-store customer experiences with signature white-glove service and exclusive relationships between shoppers and sales representatives. 

In recent years, global luxury markets have seen the rise of digital, and with it, the emergence of two new generations – Millennials and Generation Z. Over the next five years, these groups will represent approximately 55 percent of luxury goods buyers and contribute 130 percent of market growth.

Unlike earlier generations, these digitally native shoppers are searching for a different type of white-glove experience – one that allows new ways to connect with brands that reflect their personality, taste and style; with seamless transition between online and offline channels.

To quote Alex Bolen, CEO, Oscar De La Renta:

“To engage with a brand in a uniquely personal way is the ultimate luxury.”

But what does a luxury experience really look like in the digital age?

As Gen Z and Millennial markets begin to mature, luxury firms can no longer rely on brand legacy and reputation to win new business or secure customer loyalty. Slow adoption of digital strategies often leaves retailers struggling to leverage the right data needed to create the personalized digital experiences new-age buyers crave.

Research shows that luxury firms are slower to adopt digital-first strategies, technology, and core data capabilities like personalization engines, customer data platforms (CDPs) and cloud infrastructure. As a result, luxury brands fall behind when offering elevated experiences online, and subsequently miss out on critical cross-channel engagement opportunities.

Designing for the future

Companies are encountering a variety of barriers to developing personalized experiences due to challenges surrounding data sourcing, analysis, and customer experience planning.

Key barriers for digital retail transformation include:

  • Limited data: Relying on limited data points may not provide an adequate understanding of a customer’s context to serve a personalized experience.
  • Silos in channel efforts: The overall customer experience may be neglected in favor of enhancing communication only in particular channels.
  • Underinvestment in data processing and analytic expertise: Personalization requires a strong understanding of data gathered through implicit and explicit efforts and large technology systems to process that data. Companies that are unable to invest in these efforts are challenged to serve personalized experiences.
  • Awkward interactions: Poor brand experiences may result from data silos and limited data exposure. For example, targeted programmatic or social media ads are shown to customers who have already purchased advertised products, or personalization elements like shopping cart history, shipping and payment preferences, or favorited items are lost when a person returns to the website.

Legacy brands are also faced with the threat of new luxury retail disruptors, which tout direct-to-consumer or subscription-based business models born in response to growing consumer demand for convenience and customization – a new type of “luxury” shopping experience. To compete, established brands will need to adopt progressive mindsets and incorporate data from multiple sources when designing new experiences -- bridging the gap between the coveted in-store experiences they’re known for, and bringing them online.

A dataful approach

At Publicis Sapient, we take a dataful approach when redefining luxury retail, leveraging qualitative and quantitative data to ground experiences in both intuitive and evidence-based thinking. With years of cross-functional experience and digital transformation expertise, we partner with retail organizations to bring a start-up mindset, agile methodologies, and iterative, data-led experiences to every customer touchpoint. 

We’ve found there are four strategic steps to help bring the new vision of luxury to life:

  • Step 1: Evaluation. A discovery process allows for assessment of existing data, processes, and strategy to identify gaps across channels. Competitors are also audited for strategy analysis. 
  • Step 2: Omnichannel opportunity identification. Build framework for addressing experience gaps and bridging the gap between online and offline channels. Identify, evaluate, and prioritize opportunities for personalization along the length of the customer journey from awareness to purchase to ownership across website, email, media, social, and mobile properties.
  • Step 3: Collaboration and workshopping. Review recommendations in collaborative workshop environments and gather feedback from all stakeholders, breaking down silos and improving transparency across the organization.
  • Step 4: Design and implementation. Integrated data science and creative teams work to bring and end-to-end vision of personalization to life. Progress and projects are measured and optimized over time based on consistent analytics and data monitoring.

Setting new trends

To serve personalized experiences, companies must create a unified, holistic view of their customers through an understanding of each individual’s past interactions with the brand across physical and digital channels. Customer data from multiple channels and sources needs to be pulled together, cleaned, integrated and analyzed to understand customers’ preferences and how to best target individuals in the future. These insights can then be applied to optimize existing experiences, and create new ones across channels.

AI and big data

One luxury apparel retailer turned to artificial intelligence and big data in order to personalize e-commerce experiences. First, data was consolidated to develop a single view of the customer. Then, data science teams developed two machine learning models based on customer likelihood to purchase, and product category recommendations. These models were used by the retailer to predict customer preferences, which were then reflected in personalized experiences across channels.

Going mobile

Luxury retailers are also personalizing mobile experiences to better serve customers’ shopping journeys. The Louis Vuitton mobile app, for example, features a visual product search. People simply take a picture of a Louis Vuitton bag – either at home or on the street – which the app analyzes and identifies. The app then shows shoppers how and where to purchase the bag, facilitating and expediting the shopping process.

Innovating email

For Gucci, data is used to give a fresh look and feel to email communications. Gucci personalizes the content and timing of an email’s delivery depending on the recipient’s degree of brand loyalty. In a past campaign, Gucci sent emails to high-value customers earlier than to other status groups, and personalized subject lines with the customer’s name and loyalty language, such as “We Invite You” and “Special Preview.” These simple personalized touches increased email open rates above average and successfully spurred customer engagement and interest in a new product line.

A new look for luxury retail

While the luxury retail landscape may be getting a new look in light of changing shopper needs, the shift towards digital poses new promise for coveted designer labels to continue to dominate as creative trailblazers – this time, with more cross-channel tools to leverage and make their own.

Retail digital transformation requires retailers to embrace innovation and increase their level of analytics maturity. Technology like machine learning and the CDP break down big data – opening the doors to better understanding customers and allowing for new, elevated experiences that align with the traditional expectation of luxury service. 

Maya Czajkowski
Maya Czajkowski
Customer Experience Innovation and Consulting, North America