For consumer packaged goods (CPGs), delivering personalized content across channels requires multiple iterations of product images, constant reshoots, tweaks, packaging design adjustments, and localization by region. This can be all-consuming for creatives, who are rebuilding or recreating imagery constantly to meet the moment.

Imagine if brands could leverage AI digital twins to create and integrate high-quality, personalized product content at scale—simply, cost-effectively, and in a fraction of the time. AI and 3D digital twins make it possible, proving AI investments deliver on reduced time and speed to innovation.

In a recent post, we discussed how AI isn’t just a tool—it’s the foundation for building competitive advantage. Let’s walk through three strategic areas where digital twins offer exceptional outcomes for marketing teams looking to deliver more.

1. Starting with product imagery

According to EMARKETER, content creation will be the top budget priority AI use case for chief marketing officers worldwide. Why? Producing product images today requires brands to spend a massive chunk of their budget to constantly reshoot and edit images. With digital twins, brands have the flexibility and scalability at low cost to create thousands of variants on a single product image, including labels, packaging, and language formats—all within a single file.

AI empowers not only productivity but creativity. Digital twins are hyper-realistic, enabling content managers to easily and endlessly modify or expand on a concept using a 3D product model with a few clicks. Creatives can reallocate time spent in operational “to do’s” to storytelling, strategy, and delivery by channel. Brands can even showcase products in both static and dynamic formats because AI models aren’t limited to one dimension.

Net-net: Digital twins for product images, videos, and interactive experiences simplify content workflows and allow you to:

• Generate endless product images or videos using a single digital twin.
• Refresh imagery for markets or seasons without reshoots.
• Reduce repetitive labor for creatives while shortening production timelines.
• Test creative concepts instantly without adding costs.
• Update visuals across brands seamlessly.

Making it real: Nestlé reduces associated time and cost by 70% with scaling digital twins

Recently, Nestlé—the world’s largest food and beverage company—collaborated with Microsoft, Accenture Song, and NVIDIA to build and launch a new AI-powered in-house service to create high-quality product content at scale.

With its new digital twin content supply chain powered by NVIDIA Omniverse on Microsoft Azure and using Microsoft AI solutions, content creators across Nestlé’s 45 content studios around the world can deliver high-quality creative assets at scale for e-commerce and marketing communications. Nestlé’s Integrated Marketing Services (IMS)—250 marketing experts in seven hubs—are working on scaling the digital twins and driving content localization.

Nestlé already has a baseline of 4,000 3D digital products, mainly for global brands, with the ambition to convert a total of 10,000 products into digital twins in the next two years across global and local brands.

Proving the value of AI investments in digital twins:

• 70% reduced time and cost associated with scaling digital twins.
• Faster content production for several brands, including Purina, Nescafé Dolce Gusto, and Nespresso.
• Better ability to position iconic brands in a fast-moving digital environment.
• Seamless updates for seasonal campaigns or channel-specific formats.

For Nestlé, these technologies are proving to be catalysts for creative ingenuity, revolutionizing creative workflows in design, supercharging content creation, and enabling nuanced personalization—positioning Nestlé at the forefront of marketing.

Learn more from this video about conversations Chief Marketing Officers had with Microsoft at the recent Cannes Lions Festival of Creativity event:

2. Digital twins enable game-changing one-to-one consumer experiences

Digital twins are generating realistic virtual experiences that not only enhance the shopper journey but also hyper-personalize each touchpoint to create memorable brand moments. AI has enabled interoperability between datasets to unlock online configurators, virtual reality product trials and visualizations, and in-store displays.

Net-net: Embedding AI in user experiences is allowing consumer and retail goods companies to enable:

• Try-ons for beauty products and fashion.
• Configurators for custom merchandise.
• Interactive, 360-degree product views.

3. Next level: Media and creative, together at last

The era of AI ushers in a world of “intelligence on tap.”

Imagine if AI-powered digital product twins merge product imagery and consumer insights to create visuals targeted to specific audience segments or even individual customers.

A combination of insights and digital twin content creation empowers marketers to optimize for better impact and even map future trends. The value of building digital twins goes beyond endless product image creation. CPG brands are now leveraging AI to connect real-time campaign insights to their content studios as a primary use case to prove value. Agents are being built to perform audience simulations, test images, content, and even segmentation strategy to drive higher return on ad spend (ROAS) or even predict impact.

Net-net: Use AI to connect media insights and content to:

• Simulate, refine, and test marketing scenarios and consumer responses.
• Increase campaign effectiveness with real-time, iterative feedback.
• Test and optimize personalized marketing strategies at scale.
• Model customer segments and predict campaign outcomes.

AI as a tool to amplify human creativity

As AI continues to evolve traditional processes and enhance productivity, marketers know human creativity remains a critical resource. With digital simulations and AI together, you can reallocate your valuable resources to more strategic, creative tasks; reduce costs and risk; and help your marketing teams optimize spend and focus on your number one KPI: growth.

Learn more

• Read the blogs:
  • How CMOs can personalize marketing and optimize spend with AI
  • More human-centered retail with AI
• Learn more about Nestlé’s end-to-end content supply chain powered by digital twins.
• Read the e-book: Transformative retail: Harness AI innovations to stay ahead.
• Explore Microsoft’s responsible AI principles.

Microsoft Cloud for Retail

Connect your customers, your people, and your data

Explore solutions

The post The next wave of AI for content creation includes digital twins appeared first on The Microsoft Cloud Blog.

Copilots, agents, and AI assistants that facilitate creativity and drive productivity are becoming table stakes for marketers. Most brands have now tested generative AI for tasks like brainstorming, summarizing emails, or enhancing visual content. In fact, 78% of AI users are bringing their own AI tools to work. But to leverage AI at a higher level and prove more value to the bottom line, CMOs need to embed AI deeper into their organization’s processes and across multiple functions. And that is no overnight task.  

Microsoft Cloud for Retail

Connect your customers, your people, and your data

Explore solutions

Here’s a three-stage roadmap for how some CMOs are rethinking business processes like content creation and customer engagement in a buy versus build framework that aligns AI investments with business outcomes. 

A new AI roadmap for CMOs 

The Buy-Extend-Build framework extends from basic AI adoption (Buy) to full-scale transformation (Build), guiding marketers as they move from table-stakes investments to market-making, revolutionized business models. 

1. Buy:
   The Buy stage delivers operational efficiency quickly but serves as a steppingstone, not the destination. These “built-in” solutions, like Microsoft 365 Copilot, require no customization and help the workforce get comfortable using AI as a precursor to bigger, more customer-facing AI initiatives. These strategies can be effective at helping marketers reduce menial tasks that weigh down creative forces. In fact, the global agency network dentsu uses Microsoft Copilot to do just that. According to Kate Slade, Director of Emerging Technology Enablement, dentsu, “Our recent analysis shows employees are saving at least 15 minutes, if not 30 minutes a day by using Copilot. We are seeing a noticeable shift in how they are using the technology, spending less time on meetings, emails, calls, or chats, using the time they get back to focus on deep work without interruptions and to invest in their teams.”  
2. Extend:
   As organizations start to mature and integrate various business processes, they need to compose their own solutions. This involves integrating generative AI tools, internal data, and models from Microsoft or open-source platforms to build brand-specific, intuitive user interfaces and personalized services. This approach enables marketers to drive more personalized experiences and precise performance measurements, allowing for faster optimizations through dynamic content changes based on campaign performance or new collaboration methods with agencies. Success at this stage requires continuous AI model training, fine-tuning, and maintaining relevant, high-quality data. The Extend stage can leverage generative AI to enhance shopper self-service, customer service, and automate internal content planning and execution processes. 
3. Build:
   At this final stage, brands unlock their highest growth potential by redefining business processes end-to-end. This requires advanced AI models, change management, reskilling, and new operating models. Partners, SIs, and customers collaborate to develop self-improving models. ‘Build’ initiatives leverage AI-powered solutions like Microsoft Azure OpenAI, utilizing automatic data feedback loops from various repositories. This includes linking operational data (such as sales and inventory demand) with the marketing tech stack and customer insights. By rethinking costly business processes, the Build stage drives a compounding competitive advantage—enabling continuous scaling and evolution with AI. This transformation impacts multiple business units, creating growth opportunities beyond marketing. 

Dynamic, adaptive content production 

As CMOs start to examine business processes through the lens of AI potential, they’ll find that different processes require a different approach (like Buy, Extend, or Build.) Some processes will differ by cost or resource needs, and will require a change management plan. Regardless, ‘Buy’ is considered foundational to unlock more AI value. But to go even further, CMOs will need to rethink decades-old challenges. And that requires some imagination. 

Imagine if content marketers could assign an AI assistant to complete multiple complex workflows autonomously—from automatically tagging metadata to changing the background on a display ad. Other agents could generate data-driven creative briefs for review applying copy grounded within brand guidelines, localized by region, or deliver intelligent optimization recommendations and insights based on campaign results.  

These are big, revolutionary concepts that require a combination of Buy, Extend, and Build initiatives. To help marketing evolve with AI, organizations need to break down common workflows and identify where AI can boost efficiencies versus where rebuilding is necessary. Not every task will need to be rebuilt. Most importantly, the vision needs clearly defined goals that impact multiple senior stakeholders so there is buy-in across IT and marketing, along with team assignments meeting specific timelines and goals. The result will be more than hyper-personalized touchpoints, higher Net Promoter Scores, or improved return on investment (ROI)—it will drive overall brand growth. 

Partners, marketing technology solution providers, and agency teams are often key to this effort. Many are already building solutions across business processes with composability in mind to fit the needs of the brand. For example, Sitecore is partnering with Microsoft to support revolutionizing content creation and development with Nestlé. Marketers often find themselves navigating a plethora of strategic brand and marketing documents, which is overwhelming and time intensive. On Nestlé’s AI transformation roadmap to revolutionize marketing processes, they co-created an AI Brand Assistant as a part of Sitecore Content Hub, to democratize and simplify access to brand and category knowledge, and supercharge creative partners, to ensure all AI-powered outputs—from color schemes and messaging to market trends—remain authentic and true to their brand.  

Building better shopping experiences with conversational AI  

Ecommerce has remained largely unchanged in the last twenty years. It offers shoppers search, product descriptions, scrolling, and sometimes a hit-or-miss chatbot for help navigating returns or simple questions. With the advent of conversational commerce agents—including virtual shopping assistants—retailers are invigorated to rethink how customers experience and engage with their brand. The possibility of the future of search and online commerce includes higher customer engagement, loyalty, sales, and reducing operational costs. Retailers are rethinking what “search” means to their consumers with AI. They can now hyper-personalize customer interactions at scale, increasing conversion rates, and reducing customer acquisition cost (CAC). Continuously training and fine-tuning AI models with accurate data helps ensure shopper recommendations remain relevant and contextual.  

Accenture’s Consumer Pulse 2024 research found that more than half (around 51%) of consumers are already open to using conversational AI solutions. For example, ASOS leverages this technology to fine-tune product recommendations and deliver hyper-personalized experiences like their AI Stylist. Their Azure OpenAI-powered experience helps customers discover new looks through an easy-to-use, conversational interface, built using early access to Microsoft’s generative AI tools, that reflects the ASOS brand and tone of voice authentically. 

But personalization isn’t a one-and-done task. Critical to both content generation and conversational AI are continuous data feedback loops to refine models and ensure long-term agility with AI investments. AI-powered solutions, such as Azure OpenAI models, perform best when enriched by real-time data from cross-functional systems—including sales, supply chain, and customer platforms. Often this approach requires something like a unified data platform, or Microsoft Fabric, so data is compiled in a single data layer and fed into the AI models in real-time. 

Tools like Personalized Shopping Agent enhance customer interactions through conversational AI and customized recommendations, or through a combination of Microsoft 365 Copilot, Azure OpenAI, and Fabric to ensure data feedback loops are present and continually optimizing the offering.  

Building these systems allows organizations to move beyond incremental change and achieve compounding competitive advantages over time. 

Three takeaways for CMOs 

1. Think big: Don’t stop at automating small tasks—reimagine entire processes to unlock greater value from your investments. Ensure collaboration with IT to create data flywheels that future-proof marketing efforts.
2. Collaborate early and often: Secure alignment across the executive leadership team and potentially the board, along with external partners to drive adoption and maximize outcomes. 

3. Innovation is iterative: Success with AI isn’t a one-time event—it’s a continuous journey of learning and refinement. 

CMOs who act fast will capture a first-mover advantage in this new era of AI-powered marketing. AI offers CMOs the tools to optimize spend while personalizing experiences at scale, ensuring sustainable growth and customer satisfaction. By rethinking resource-intensive and costly business processes like content creation and personalized customer engagement, brands can unlock new efficiencies, deliver meaningful interactions, and achieve long-term success. 

Learn more

• Read the blog Harnessing AI to supercharge personalized marketing at scale. 
• Learn about Microsoft’s responsible AI principles.

The post How CMOs can personalize marketing and optimize spend with AI appeared first on The Microsoft Cloud Blog.

But what if your organization is currently still in pilot mode? The challenge with pilots is that they don’t drive consequential change in the bottom line, and it’s a struggle to democratize learnings. With three in five chief marketing officers (CMOs) driving funding behind investment for generative AI,² there’s pressure to prove return on investment (ROI) and value from AI investment amidst numerous pilots.

Microsoft Cloud for Retail

Connect your customers, your people, and your data

Get started

As we transition from hype to reality, brands are shifting from basic generative AI applications like content and tagline generation and to evaluating comprehensive business processes that leverage generative AI to accelerate timelines, unlock more value, and drive increased growth. Marketers are leading the way in leveraging AI as a powerful co-creator at scale.

Let’s evaluate age-old challenges and lengthy processes for marketers.

First, identify key areas where AI creates significant impact in a 6 to 18 month period:

• Increased investment in a multitude of omnichannel marketing solutions and partners has led to fragmented customer profiles and data. Siloed analytics, reports, and data make it difficult to create a unified view of the customers, hindering segmentation efforts to personalize each interaction with customers
• Isolated business analysis tools and cross-media performance and recommendation data across partners and platforms make it difficult to develop real-time or predictive media planning strategies. Marketers struggle optimizing spending and maximizing return on ad spend (ROAS).
• Convoluted naming conventions, metadata tagging, and static reporting from disconnected create “tech debt.” This debt makes it difficult to spot patterns in data such as best keywords, segments, content, and channels.

Powerful personalization at scale with AI

How can AI create more personalized touchpoints across a shopper journey?

Common “personalization” mishaps that decrease loyalty: A customer browses running shoes online but buys a pair in-store, later they receive a generic email offering discounts on the shoes they just purchased and unrelated accessories.

The future process of personalization accelerated with AI: The customers’ needs are anticipated before they even ask. A customer now browses for running shoes online, purchases them in-store, and receives a personalized upsell promotion to “complete the look” with complimentary products. The brand then sends a promotion the following year to upgrade the shoes to a new pair.

Making AI-powered personalization “real”

1. Collaboration is the heartbeat of innovation: Personalization at scale should be a joint priority for business and technical stakeholders. Together, executives collaborate over a single “source of truth” for data and ensure a dynamic flywheel of data is in place, updating customer signals and operational data (supply chain, promotions, product, point of sale [POS]) in real time. Consistent updating and scrubbing of the data sources ensure conversational agents used by marketers, like Microsoft Copilot, are reasoning over accurate, quality data and keeps data secure.
2. Simultaneously, marketers apply “AI as a co-creator strategy” to the end to end (E2E) process of creating, planning, executing, and analyzing campaigns adopting, training, and utilizing conversational agents.

But, how?

Collaboration between IT and the CMO: Preparing the data estate to accelerate personalization at scale, stakeholders can leverage Microsoft Fabric, a unified data platform with compatibility across multiple cloud platforms, allows marketers to access and analyze up-to-date data directly within the governance boundary. Fabric offers intelligent data analytics as a service, allowing brands to build custom reports in Power BI without having to export data, ensuring greater security.  Marketers can spend less time consolidating reports from multiple groups, partners, and internal resources and instead simply ask questions of their data.

Create a comprehensive view of the customer and their journey with a customer data platform like Dynamics 365 Customer Insights, connected to Fabric, offering better segmentation, insight generation, and campaign activation tools for data-driven optimization driving ROAS, growth, and elevated customer experiences. With both Fabric and Dynamics 365 Customer insights, marketers leverage advanced analytics and AI capabilities to gain deeper insights.

Marketers can then leverage Microsoft 365 Copilot as an AI “co-creator” to enhance productivity and collaboration across marketing and agencies, reimagining the entire content creation and activation process, from creative brief development to real-time brainstorming with agencies.

Embrace the future of marketing with AI

As brands struggle to make the promise of generative AI and its benefits “real,” cross-collaboration across both data and marketing stakeholders becomes more critical than ever before. By overcoming the challenges of disparate data, marketers create more effective campaigns that drive better ROI. The future of marketing about more than leveraging generative AI as a content creator, but a co-creator grounded quality, accurate, and up to date in company data and supercharged by large language models (LLMs). These E2E strategies will turn marketing strategies from reactive to predictive. Ready to begin the journey to personalization at scale?  Learn more about how Microsoft can help.

Get in touch with a Microsoft representative at any time for more information on the ways Microsoft can help your retail business achieve more with insightful, intuitive AI tools. We are eager to help you innovate and achieve your goals.

Learn more

• Microsoft’s responsible AI principles
• Generative AI will revolutionize Revenue Growth Management
• “What’s my generative AI strategy?” Microsoft is helping consumer goods brand marketers embrace the era of AI
• Generative AI transforms business processes

¹Sitecore Launches Sitecore Stream, Delivering on Vision for Industry’s First Intelligent Digital Experience Platform.

²How CMOs are shaping their GenAI Future, BCG 2024.

The post Harnessing AI to supercharge personalized marketing at scale appeared first on The Microsoft Cloud Blog.

Marketers are asking us how can generative AI:

• Accelerate time to market
• Drive marketer efficiency
• Accomplish creativity at scale
• Make analytics more accessible

Generative AI streamlines communication between humans, computers, and data, simplifying the work we do by enabling conversational queries across analytics, email generation, marketing content, and even retail media. It is now a critical time to put data at the core of your marketing strategy.

Generative AI in consumer goods and retail

When thinking about how to retain and increase the lifetime value of loyal customers, generative AI can use deep understanding and intent, and get more accurate with each query and interaction. It can elevate the shopper experience and maximize the value of your data in unparalleled ways. Below are a few use cases we’ve been hearing from our consumer goods and retailer customers that can help you brainstorm and prioritize your investments in an AI strategy.

Reply to customers faster, with localized messaging, and on-brand. Brands used to give call center employees massive binders filled with scripts detailing every possible customer problem and solution. With generative AI there are infinite paths of conversation in the decision tree. Chatbots can even showcase your brand’s conversational style.

Revolutionize your site’s search engine. Sometimes the only conversation you will ever have with a customer is via your site’s search bar. Imagine: need dinner? Type “how do I make chicken casserole” into the search bar and have all the best-selling, in-stock ingredients populate in basket. Broken fence? Type “there’s a hole in my fence” and marvel as all the necessary tools populate in your digital basket. Investing in this critical engagement may lead to significantly higher conversation rates and basket size. Microsoft Azure Cognitive Search and Microsoft Azure OpenAI Service, power rich semantic search experiences over a variety of content across web, mobile, and enterprise applications—using customer intent versus keywords. You can also generate search summaries and analytics internally to better predict product demand and recommendations. Investing in your search engine may significantly improve customer experience.

Satya Nadella provided several examples during the Microsoft Build 2023 keynote. View the entire keynote below, or see the plug-in extensibility with shopping cart example at time stamp 11:11.

Make faster, more informed decisions on where to invest in e-commerce improvements with accessible analytics. Clarity chat, a free analytics tool that delivers advanced e-commerce and site analytics, allows brands to ask questions about their data in natural language. How’s my website performing week over week? What’s my bounce rate? Get simple, accessible summaries and analytics from your data.

Reach customers in new, native ways online. It’s a new era of search. As CVP of Microsoft Advertising, Kya Sainsbury-Carter said in an interview with The Wall Street Journal, “the future of search is an integrated experience across search, answers, chat and creating.” New ad formats are on the rise with AI-powered Microsoft Bing. The new Bing is empowering brands, publishers, and app creators to choose the ad formats they know drives the best results and customer experiences, serving native ads on chat platforms from Microsoft and other companies.

Democratize data for non-technical employees to make real-time and predictive optimizations. In today’s economy, brands can’t afford to wait days or weeks for an analysis to be prepared and delivered before making much-needed campaign optimizations. Generative AI enables marketers to ask campaign data questions using natural language, so insights are even more accessible. Copilot in Dynamics 365 Customer Insights allows non-technical employees to ask data questions using everyday language identifying the best performing segments and channels to drive sales.

Experiment with automating content generation at scale, speeding up the writing and image generation processes. For many, a blank page is the most intimidating part of the creative process, and with countless numbers of legacy and emerging channels requiring campaign content derivatives with unique specifications—text, video, visuals, tweets, posts, blogs, email, website—marketers need a (shall I say it?) copilot. Generative AI amplifies human capacity for creativity and speed-to-launch. Copilot in Dynamics 365 Marketing can accelerate campaign time-to-launch for marketers by offering inspiration and simply creating personalized content, and Dalle-2 in Azure OpenAI Service can generate a variety of campaign images across marketing mediums using natural language text.

Drive better engagement with product detail page content creation. Many brands struggle managing wildly different descriptions, images, and reviews across websites selling their products, to test product description page content and find the winning version. Generative AI aggregates digital descriptions and reviews of a product across the internet and standardizes the product detail pages with the best variation. In an example with Carmax, Azure OpenAI Service was used to produce 11 years’ worth of car summaries in a matter of months. The impact led to hyper-personalized offers to customers, time and cost optimization through intelligent search engine optimization, and increased revenue.

You can even accelerate configuration of shipping labels. Generative AI can generate new labels without constraints to find the best possible use of space.

Create a ChatGPT like experience tailored to your own enterprise data. In this demo, you can see the Azure OpenAI Service based assistant for enterprise data in action.

How do I get started?

Learn more with Microsoft resources

• New era of value realization is here—put your data to work with AI
• Responsible AI principles from Microsoft
• What is Microsoft’s approach to AI?
• Visit our Consumer Goods and Retail blog homepages to stay informed.

The post “What’s my generative AI strategy?” Microsoft is helping consumer goods brand marketers embrace the era of AI appeared first on The Microsoft Cloud Blog.

Enabling intelligent brands

Deliver the future using innovative technology tailored for the consumer goods industry.

Get started today

Personalized customer experiences

The most successful loyalty programs are agile. The ability to quickly respond to change is key to success not only in business overall but also in loyalty programs specifically. Having customer data that provides insights into why your customers are loyal to your brand will give you a solid foundation for your loyalty program.

Customers have so many contact points with a brand. Maintaining consistency and relatability, across online, offline, in-store, and more is massively complex. The ability to capture and analyze the multitude of customer signals across these channels provides the customer knowledge you need. Over the past few years, the explosion of e-commerce and direct-to-consumer strategies has provided many new ways to reach customers. This evolution has impacted every aspect of retail and consumer goods, from transforming supply chains to merchandising, customer service, and advertising. Adapting your loyalty strategy from being reactive to predictive requires a system that can analyze all that data. Often AI solutions are required to make it predictive. Data is a great enabler for every brand, especially retailers and consumer goods companies.

Have you noticed the brands you shop with are expanding into interesting new services? Brands are experimenting, trying new and diverse ways to both attract and retain customers. Some brands are doubling down on their resale business, providing customers with opportunities to sell products back. Resale channels are increasingly popular for fashion brands. For example, one popular clothing retailer partners with secondhand e-tailer. Another clothing brand resells its gently used products via its own site. Brands are also offering unique payment options. A popular smart-bassinet brand promotes rental services to new parents. Subscription models are growing as a category—from meal prep to clothing and accessories to diapers—a subscription set-it-and-forget-it strategy ensures brands stay top of mind. Managing economic uncertainty over the last few years, more brands are offering new payment solutions like buy now, pay later (BNPL). In fact, in the age group of 18 to 24 years, 61 percent of consumers made a BNPL purchase.¹ These programs are designed to meet customers where they are economically and keep conversations ongoing. They also feed an incremental stream of data related to customer needs that can point to new and necessary loyalty solutions and offerings.

As critical as it is to leverage data to power a strategy to increase loyalty, it’s equally important to capture data from customer events and power it to uplevel the overall customer experience. Brands can drive deeper customer engagement by using customer data to improve their overall experience. Campari launched a campaign “Aperol Together Again” focused entirely on bringing people back together as COVID-19 restrictions were lifting. The campaign was entirely orchestrated on the Microsoft platform. Data from in-person events across the globe fed into behavioral and transactional customer data to inform the next best actions online, like intelligent product recommendations and predictions.

Demonstrating and communicating core values is another key ingredient to earning customer loyalty. Shoppers want to know what brands stand for and how they give back. Classic differentiators like price, selection, services, and convenience are not the only factors influencing loyalty. Brands are building connections with customers on an emotional level by entwining mission and purpose with products. According to Capgemini, “86 percent of consumers with high emotional engagement say they always think of the brands they are loyal to when they need something, and 82 percent always buy the brand when they need something.”² One clothing brand sends customers receipts for purchases that cite the exact impact a purchase made towards saving the planet (12 pounds of carbon dioxide and 8,196 gallons of water). One clothing retailer famously donates a pair of socks for every sock pair purchased to homeless shelters. Shoppers want more than standard perks for their devotion and data.

Examples of how brands are adapting

To earn access to data, retailers and consumer goods companies must first gain the trust of their customers. Be explicit and clear about the information you are collecting and how your organization will use it.

Trust is a long game to win, and a short one to lose. It takes years to build long-term loyalty, but one small slip-up can reset things to zero, so it’s critical for retailers and consumer goods companies to get it right. If brands want to use customers’ data to drive their loyalty programs, they must prove they can be trusted to use it wisely and transparently and provide perks such as personalized services, relevant product recommendations, exclusive promotions, or better delivery options in exchange.

Brand loyalty program staples such as mailing lists, coupons, and advertising are being reevaluated. AI, including generative AI, can improve personalized messages to customers. Finding ways to include gamification can attract customers or build unique engagement opportunities in a commerce-enabled environment in the metaverse. Unlocking insights hidden within data gives brands what they need to build connected, personalized experiences for customers, employees, and partners.

Finding ways to combine online and in-store experiences creates consistency for customers. Brands are exploring how to use mobile applications to send personalized promotional offers to customers in real-time while they’re in stores.

The future of loyalty programs

The evolution of loyalty programs continues. Recent headlines have shown brands shifting and changing their programs. The reality—and the challenge—is that customers expect consistency across every brand channel. They expect better and better experiences with each engagement. Staying current with technology, both customer-facing and behind-the-scenes, is critical. Having a platform to collect, store, and analyze customer data is the first step. However, customer touch points like point-of-sale systems will also need to evolve. Having the ability to engage with customers on their smartphones will continue to be important.

We’ll continue to explore new technologies to create solutions such as headless loyalty services. Headless commerce is the separation of a website’s front-end from its back-end e-commerce functionality. This separation gives more flexibility and increases the number of buyer experiences you can create. There is an appeal to loyalty engines that are always present and consistent, regardless of which channels customers engage with. In addition, brands are exploring how to use the metaverse and Web 3.0.

Capitalize on Microsoft technologies and solutions

Now is the ideal time for your brand to drive lifetime customer loyalty. Both the market and customer expectations are changing. There are new technologies that can help you capitalize on opportunities and enhance customer relationships. However, we would caution against haste. Retail and consumer goods companies should view the race to win customer loyalty as a marathon, not a sprint—every experience matters. A customer’s last best experience sets the standard for the type of experience they expect everywhere, particularly in the digital world where experiences transcend industry boundaries. Take time to understand your customers, plan loyalty strategies carefully, and harness the power of technologies and solutions from Microsoft and key partners to help you develop and deliver unforgettable experiences that lead to lifetime loyalty.

Learn more

Explore our strategy blogs, website resources, and how consumer goods companies are innovating:

• Read our blog on how to harness powerful, customized tools to consolidate and manage data flow to drive improved performance and more.
• Visit our website on Microsoft solutions for the consumer goods industry.
• Grupo Bimbo takes a bite out of production costs with Azure IoT throughout factories.
• Campari Group personalizes customer experiences and builds brand awareness with Dynamics 365.
• Peet’s Coffee meets market changes with Dynamics 365.
• PepsiCo uses Azure Machine Learning to identify consumer shopping trends and produce store-level actionable insights.

¹Gen Z is flocking to buy now, pay later to beat inflation, ModernRetail.

The post Building brand loyalty and how data can guide you appeared first on The Microsoft Cloud Blog.