Perspectives

Unlocking customer growth: Driving high value actions through personalization and retail media

Personalized customer experiences though retail media personalization

Retail media presents a significant growth opportunity for retailers, but customers increasingly demand personalized experiences. But retailers can effectively deliver personalized customer experiences while leveraging the benefits of retail media. This report explores how retailers can deliver a customer - centric experience and learn from strategies from leading brands who are successfully integrating personalization with retail media to enhance customer loyalty and drive resilient growth.

US retail media ad spend is forecasted to exceed $100 billion by 20271 showcasing how retail media networks are emerging as a lucrative revenue source for retailers. As a result of this rapidly expanding advertising landscape, some retailers are quickly embracing retail media networks often as a siloed strategy for customer targeting.

While retail media may present a huge revenue opportunity for brands, an outsized focus on monetization has potentially had a negative impact on the core customer expectation for personalized experiences.

In a 2024 study on how customers and brands defined success in personalization2, Deloitte found that 80% of consumers surveyed prefer brands that offer personalized experiences and reported spending 50% more with such brands. While 92% of retailers surveyed believe they effectively offer personalized experiences, only 48% of consumers agreed.

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Retailers may find it quite challenging to strike the right balance between commercial viability and maximizing growth, especially as retailers often develop retail media offerings, advertising targeting strategies, and KPIs for retail media success siloed from the personalization strategy for the customer experience which can result in two key challenges:

  1. Retailers should ensure customer experience remains prioritized so that incremental revenue potential doesn’t come at the cost of customer satisfaction and retention.
  2. Retailers should prove their ability to accurately and relevantly engage their core customers based on likelihood to purchase, cost to maintain, and total market penetration potential.

To tackle these challenges, retailers should consider adopting an integrated strategy that aligns their technology, people, and processes in a way that establishes customer experience as the threshold for optimal retail media revenue potential. This is especially critical considering retailers expect to allocate 59% of their marketing budget to personalization.

Through a more strategic focus on personalization as top priority, retailers can be better suited to authentically account for and respond to customers’ identities, lifestyles, and real-time needs in a way that can provide mutual value for both the business and the customer.

Personalization involves understanding who your customers are and what they need to deliver a personalized experience that is unique to them.

Retail Media Networks are a collection of in-store and owned digital platforms that retailers leverage for targeted marketing or advertising using first party data.

Four phases approach for delivering valuable, relevant, and integrated customer experiences

To maximize the benefits of personalization in retail media networks, brands should aim to transform the customer experience in a way that focuses on needs and value and defines success through resilient growth and customer loyalty.

  1. Establish a data infrastructure that tracks customer behaviors across all channels
  2. Identify your top customers to understand their high-value actions & behaviors
  3. Design an experience that promotes high-value actions by balancing customer personalization against company profit
  4. Scale your solutions through an omnichannel approach

Phase 1: Establish a data infrastructure to track customer behaviors across all channels.

By establishing a solid Customer Data Platform (CDP) infrastructure for the substantial amount of first-party data they collect, retailers’ media networks have an unknown potential to create personalized experiences. One of the largest predictors of a retailer’s ability to tap into this potential is how effectively they manage balance in customer identity resolution between creating a singular view of the customer that still is dynamically responsive in different decision-making processes.

When such a solid identity resolution strategy then meets real-time data, well established CDPs can better implement predictive models that enable retailers to interpret customer feedback, developing addressable market segments, and predict potential needs.

Dollar General Case Study

Dollar General (DG) has a customer base with 80% of stores serving communities of 20,000 people or fewer, so the company strategically connects its marketing strategy to the organization’s broader mission of Serving Others, including serving the financially and geographically underserved.

To do this, Dollar General has prioritized first-party data to offer more personalized and tailored customer experiences that increase value while serving customer needs. Senior Director of Digital and Marketing Engineering, Paul Bucalo, emphasized the importance of quality data, saying, “Instead of amassing large quantities of data, we focus on acquiring quality data that provides a contextual understanding of our customers that we can adapt to predict trends and future behaviors.” This strategic data infrastructure offers a deeper understanding of DG’s rural customer base that sharpens the accuracy of its marketing efforts, translates online engagement to offline action and maximizes customer value.

Dollar General's robust data infrastructure consists of two zones: a Data Warehouse and a Customer Data Platform. This configuration supports the management of 'slow' data for in-depth analytics and segmentation, while 'fast' data is used for real-time personalization during customer interactions. Leveraging capabilities like custom machine learning models alongside best-in-class marketing technology, Dollar General can dynamically adjust customers’ shopping experiences. These models allow Dollar General to contextualize a shopper’s rich history with Dollar General throughout their experience to enhance customer engagement and satisfaction.

Dollar General’s data infrastructure underscores its dedication to a customer-centric approach. Charlene Charles, head of Dollar General Media Network operations, says "We’re here to earn our place in the customer journey by delivering a relevant shopping experience that saves time and money.” This strategic use of data not only reinforces Dollar General’s commitment to value and service but also strengthens customer loyalty, driving the company's growth and success.

Phase 2: Identify your top customers and understand their high-value behaviors.

With a dynamic understanding of the total market composition, retailers can then benefit from adopting an approach that looks to identify the drivers of customer lifetime value to identify the beneficial actions or behaviors that would grow a customer's value over time. This is usually accomplished by using machine learning to segment customers based on their current and potential value, then profile these segments to create a predictive score for high-value actions taken before an ultimate purchase (or other desired outcome).

High-value actions can vary among segments.

  • For new customers, these may include account creation, profile completion, first purchase, or email sign-up.
  • For existing customers, it could be increasing order frequency or buying a new product category.
  • For loyal customers, high-value actions might include participating in loyalty programs or providing reviews and feedback.

Identifying which actions are most meaningful for deepening your customer relationship can not only serve to improve targetability on the media network, but it can also meet the customer more authentically where they are in their relationship with your brand. This can especially help brands avoid being overly assertive in the early stages of relationship development.

ConvergeCONSUMER Case Study

Deloitte’s ConvergeCONSUMER has developed a way for companies to quickly identify their unique customer cohorts, understand each cohort’s current and predicted value, see their defining traits and motivators, and predict what propensity they have to take certain actions.

How? By combining “outside-in” consumer data with a brand’s first party consumer data, Deloitte uses a combination of unsupervised clustering models and predictive models to assign customers into data-driven segments and calculate hundreds of propensity scores for each customer (e.g., propensity to purchase, propensity to churn, propensity to click on a campaign etc.) GenAI tools are then applied to name segments, summarize key insights, and make strategic recommendations on how and when to engage with customers.

This capability has recently been used by a global chain, where unsupervised learning was used to define their unique customer segments and then recommend the actions to take with each segment. For example, one segment largely ordered through offline channels, but showed potential to switch to online, also demonstrating a clear preference for specific menu items/categories, at a specific day and time of the week, etc. Combined, this allowed for more precise marketing tactics to be used to drive higher average order value and increased purchase frequency through self-service channels.

Phase 3: Design an experience that promotes high-value actions by balancing customer personalization against company profit.

With their CDPs more effectively pinpointing high-value actions, retailers can better tailor experiences that resonate with individual customer preferences at scale. Understanding what unique customer profiles make up a brand’s total market potential—including who they are, what they aspire to, and their current lifestyle needs—is crucial. This deep level of insight can form a meaningful foundation for the creation of a shopping experience that not only meets but anticipates the customer's desires, guiding them towards impactful actions that benefit them as much the brand.

To maintain effectiveness and relevance, retailers should adopt a continual learning model of execution that consistently tests and refines personalization strategies against both conversion and satisfaction. This iterative process helps ensure that the strategy remains aligned with both customer needs and business objectives, thereby enhancing the overall retail journey.

The Home Depot Case Study

The Home Depot has found a way to balance personalization and profitability by going all-in on the customer through their “Know me, Meet me, Speak to me, Value me” strategy. This strategy prioritizes customer relevance by recommending only the most pertinent products and promotions, and then including product recommendations through Orange Apron Media only when it is the most appropriate choice for the customer. The Home Depot’s Director of Personalization, Erin Thorne, explains “We want to be successful on both sides. We want to identify the customers and what they need, and we want to give suppliers an opportunity when it makes sense to us, them, and the customer.”

The Home Depot uses first, third, and zero-party data combined with data science to tailor a personalization experience for each customer based on their needs, projects, and environments. The Home Depot uses their customer understanding to help ensure that every interaction with the customer is meaningful and specific. This approach moves The Home Depot away from traditional sequential targeted advertising, focusing instead on a comprehensive understanding of each customer's specific needs and the contextual factors influencing their shopping behaviors.

With this framework established, The Home Depot looks for overlaps between customer-centric personalization and relevant sponsored content. Sponsored products are only promoted if they are the most relevant to the customer’s needs. This selective promotion strategy helps ensure that Home Depot effectively meets customer expectations while providing suppliers with exposure at the most opportune moment in the customer journey.

This commitment to relevancy can not only secures customer loyalty but also helps ensure that supplier offerings are in direct response to actual customer demand, supporting a dynamic and responsive retail environment.

Phase 4: Integrate marketing processes, data, and technology through a consistent omnichannel personalization experience

Ultimately, advancing retail media personalization, in a way that also drives financial performance, will likely require a keen lens toward how to deploy a customer-centric design at scale. Success in operating at scale will most likely rely on the effective adoption of an omnichannel strategy, helping ensure a cohesive and seamless customer experience across all touchpoints, both physical and digital.

Often critical to this phase is the full integration of marketing processes. Leading retailers meld traditional marketing methods with advanced retail media channels, creating a streamlined and comprehensive approach. This helps ensure that marketing efforts are harmonized, maintaining consistency across all customer touchpoints.

In this regard, the right technological infrastructure essential. Retailers should work to help ensure that all their channels are consistent and linked, facilitating effortless transitions for customers across various platforms. This integration can not only elevate the customer experience but also provides retailers with a complete perspective of the customer journey, enabling more informed strategic decisions.

Macy’s Case Study

Macy’s has advanced its retail strategy by implementing a comprehensive omnichannel personalization approach that integrates customer data, marketing, and technology. This strategy helped transition Macy’s from traditional marketing channels to a more integrated, customer-focused model, enabling personalized engagement across multiple touchpoints.

Central to this strategy is Macy’s ability to analyze data, produce relevant content, and orchestrate experiences that resonate with individual customers. By synthesizing customer data with real-time behavioral insights, Macy’s segments audiences and personalizes customer journeys across all touchpoints, helping ensure content is consistently aligned with each customer’s preferences and actions.

Macy's also tracks the impact of these personalized customer journeys, utilizing key performance indicators (KPIs) such as engagement rates, conversion rates, and customer satisfaction. This continuous evaluation provides Macy’s with real-time feedback and insights, enabling the continuous refinement and optimization of their marketing strategies and customer interactions.

The success of Macy’s personalized approach is demonstrated by its targeted offer program, which has delivered nearly half a billion customized offers and achieved a personalization rate of 50% to its Star Rewards loyalty program3. This strategic focus has helped significantly boost customer engagement, loyalty, and conversion rates across various channels.

By shifting to a journey-centric marketing approach, Macy's not only elevates the individual customer experiences but also fosters deeper relationships with its customers. This strategy can enhance customer lifetime value and solidifies Macy's position as a leader in the competitive retail industry.

Retail brands are at a critical juncture where they can harness the power of personalization and retail media networks to drive growth, but this should be done with a specific goal of delivering a meaningful customer experience. An effective customer experience will most likely require leveraging first, third, and zero-party data to deeply understand and cater to customer preferences, helping to ensure that every interaction is both relevant and drives down-funnel conversion. Retailers should seek to synchronize their technologies, personnel, and processes to deliver a cohesive omnichannel experience that aligns with consumer expectations. Examples from Dollar General, Macy's and The Home Depot demonstrate that such strategic alignments not only help enhance customer satisfaction but also enable retailers to maximize the opportunities presented by the expanding retail media landscape. Achieving this balance is critical for resilient growth and building lasting customer loyalty in a competitive market.

Endnotes

1 eMarketer, “Retail Media Ad Spend Will Reach Over $100 Billion by 2027,” November 17, 2023
2 Deloitte Digital, “Personalizing Growth: It’s a value exchange between brands and customers,” June 11, 2024
3 Deloitte Digital, “Reimagining Retail With Personalization,” June 11, 2024

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