Struggling to meet rising customer demands for personalization, seamless experiences, and tailored product offerings? Discover how Generative AI (GenAI) can offer a transformative solution to meet these needs, enhance customer engagement, and drive growth.
The personalization gap: What the data reveals
Our June 2024 personalization research¹ of 500 business executives who are responsible for personalizing the customer experience at US business-to-consumer companies, plus 1,000 adult consumers who had interacted with a brand online or through an app in recent months, shows that:
of surveyed brands have a content management system, highlighting the need for better content solutions
of surveyed brands have already invested in GenAI to support personalization efforts
of surveyed brands planned to spend on GenAI in 2024 to enhance their personalization strategies
Transforming consumer-sector companies with GenAI
Today’s retail leaders are under increasing pressure to adapt and adopt cutting-edge strategies to meet customer needs. Enter GenAI. By integrating GenAI into their operations, retail and consumer brands can drive growth and improve customer loyalty. But which GenAI use cases can offer the highest return on investment? Which use cases are mature enough to get the green light for implementation at scale? Which pose the most risks and the greatest opportunities?
We spoke with Deloitte Digital’s leaders in GenAI implementation in our retail and consumer brands business to better understand which GenAI opportunities are driving real growth and what’s key to unlocking their full potential at scale. Here’s what they had to say:
1. What are some high-value areas where GenAI can accelerate the retail and consumer products (RCP) domain?
Content creation and supply chain optimization: GenAI can offer savings in production, creative consulting, and media planning. For example, we recently worked with a leading consumer apparel brand to successfully scale and adapt already-existing creative assets using GenAI, demonstrating substantial efficiency gains and cost reductions. By leveraging GenAI, organizations can streamline their content creation processes and accelerate their time to market for new campaigns. When creativity is amplified by GenAI, that is when it becomes the true engine of growth and differentiation for content creation in the RCP space.
Next best action recommendations: Add GenAI that empowers sales associates with tailored recommendations that enhance cross-sell and upsell opportunities. By analyzing customer data, product lines, seasonal trends, and other contextual factors, GenAI can provide actionable insights that help sales teams offer the most relevant products to customers. This personalized approach can not only increase sales but also reduces barriers to purchase, creating a smoother and more engaging shopping experience.
Real-time business intelligence: When GenAI uses natural language processing to transform complex sales data into actionable business intelligence in real time, retail leaders can leverage these insights to refine product assortments, optimize customer segmentation, and enhance channel strategies. By harnessing faster insight-tasked AI engines built from a company's own customer data, businesses can swiftly adapt to market changes and make informed decisions that drive growth and improve customer satisfaction.
Granular demand forecasting: GenAI can enable the shift from broad, generalized predictions to highly specific, granular insights—essentially, “mass to micro.” By focusing on individual consumer behaviors, preferences, and local market conditions, organizations can achieve more accurate and actionable demand forecasts, leading to better inventory management and targeted marketing strategies.
2. What are the essential factors to successfully scale GenAI implementation in RCP?
Organized data and minimum viable data architecture: Organized and quality data are key for unlocking GenAI's value. For GenAI to deliver meaningful results, brands must start with a quality dataset, ensuring it’s clean, accurate, and relevant to the intended use case. This means prioritizing data hygiene: removing duplicates, correcting errors, and validating sources before GenAI models are deployed. Though the data must be quality, it doesn’t have to be perfect to start realizing benefits. The concept of minimum viable data architecture allows organizations to begin using GenAI without waiting for perfection. This approach enables quicker deployment and faster value realization.
Structured end-to-end process: Uncoordinated GenAI usage within organizations can lead to silos, fractured or duplicative processes, and risk and compliance issues. It is essential to have a structured end-to-end process that aligns and integrates all GenAI initiatives into a cohesive workflow that optimizes the benefits of the technology across the customer journey. This integrated strategy maximizes the impact of GenAI investment and helps prevent potential legal, regulatory, privacy, and bias issues.
3. How should leaders plan for new technologies like agentic AI and for further GenAI investments?
Build organizational fluency first: Before allocating resources, educate teams on how agentic AI and GenAI differ in capability and application. Agentic AI excels at autonomous decision-making and complex workflows, while GenAI drives content creation and customer engagement. Help leaders understand how each technology maps to specific strategic priorities—whether that's operational efficiency, customer experience, or innovation acceleration.
Align AI investments to strategic outcomes: Connect GenAI and agentic AI use cases directly to your organization's broader strategic goals. Show how GenAI can accelerate product development or personalize customer experiences, while agentic AI can optimize supply chains or automate complex processes. Clear strategic alignment helps ensure AI investments drive measurable business impact rather than technology for technology's sake.
Prioritize strategic allocation of AI investments: Deciding how to share resources between agentic and GenAI use cases requires careful planning. Organizations need to determine their best use cases for each technology and identify the right investment mix. By strategically splitting AI spending based on business priorities and maturity, companies can maximize returns across their AI portfolios.
Establish robust risk management, guardrails, and quality assurance: As AI capabilities continue to expand, so do the risks. Leaders should proactively implement risk management frameworks and guardrails to ensure trustworthy AI use. This includes setting clear policies for data governance, bias mitigation, and transparency. Additionally, quality assurance through regular audits, human monitoring for accuracy, and validating model performance are a key to maintaining trust and reliability.
4. What's important for organizations to consider when scaling GenAI in RCP?
Start with small steps and build from there: When considering how to launch and then scale GenAI in the retail and consumer brands sector, it's important to focus on practical applications. Start with smaller, manageable parts of your processes that can be easily enhanced with GenAI. This will help get your tech and creative staffs upskilled and comfortable and pave the way for successful broader adoption throughout your organization.
Ensure data quality and integration: For GenAI to deliver actionable insights in retail, it's important to maintain high-quality, integrated data across customer interactions, sales channels, and inventory systems. This helps ensure that AI-driven recommendations and insights are accurate and relevant to consumer needs.
Invest in scalable infrastructure: As retail operations grow, scalable tech infrastructure becomes essential to manage increasing data from diverse sources like online sales, in-store transactions, and supply chain logistics. This scaling should support seamless GenAI performance and enable the business's rapid adaptation to market changes.
5. What are some recent examples of successful implementation of GenAI in RCP that you’ve encountered?
A leading chocolate company is using GenAI for next-best-action B2B sales recommendations, enhancing its sales strategy and customer interactions.
A consumer apparel company is using GenAI to enhance its content creation, delivery process, and creative operations to improve marketing efficiency.
A health and wellness retailer has recently invested in leveraging GenAI for retail pricing and promotion optimization.
Expanding opportunities to evolve consumer experiences
Integrating GenAI into consumer experiences can lead to more personalized, efficient, and engaging interactions that improve loyalty and top-line revenue. As customer expectations continue to rapidly evolve, GenAI offers one way to meet those rising demands while also creating more efficient workflows for employees and more actionable insights for executives.
About the authors
Ed Johnson is a principal with Deloitte Consulting LLP, focused on retail and consumer products. He serves clients on commercial topics such as commercial effectiveness, revenue management, and pricing and promotions strategy, and also works with them to apply analytics to commercial decision-making and to develop data-driven pricing and channel strategies, policies, and planning capabilities.
Jenny Kelly is the head of creative, content, and design for Deloitte Digital where she brings over 15 years of experience creating compelling content that connects audiences with brands. Jenny also leads our GenAI efforts for advertising and marketing, helping brands understand how GenAI can transform their business.
Tracey Arcabasso Smith, US head of design and a creative fellow at Deloitte Digital, focuses on the intersection of design and storytelling as a catalyst for organizational growth. Her creative work ranges from global brand campaigns to immersive digital experiences to short and feature films. She is dedicated to creative authenticity and meaningful connections between humans and business.
Rachel Whitt is Deloitte Digital's national content strategy lead and AI retail leader. She also serves as go-to-market (GTM) lead between the Experience Agency and the Commerce and Custom Solutions practice, helping to bring a creative, human-centered approach to cross-offering engagements. Wherever creative thinking, cross-channel solutions, strategic content, and digital experience are needed, Rachel brings a passionate, entrepreneurial, and user-first perspective.
How can leaders create trusted, AI-enabled customer experiences?
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How to choose effective GenAI investments for your business
Source:
1. Deloitte Digital, "Personalization: It’s a value exchange between brands and customers," June 2024, https://www.deloittedigital.com/content/dam/digital/us/documents/insights/insights-20240610-personalization-report.pdf.
