This is a vision of a world in which automation and automated-content generation go hand in hand with increased customer insights. Customers save time and effort, accessing the goods and services they want and need. Marketers can better meet and deliver customer value and focus on innovation.

The emergence of generative AI brings this vision of hyper personalization at scale close to reality.

In a recent McKinsey report titled “Economic Potential of Generative AI: The Next Productivity Frontier” the survey conducted projections on the future of AI’s growth potential based on current technologies and C-suite confidence. Estimates suggest that gen AI could contribute up to $4.4 trillion in annual global productivity. More specifically to our targeted analysis, marketing and sales is one of four functional groups that could reap an estimated 75 percent of that value. Productivity of marketing alone due to generative AI could increase between 5 and 15 percent of total marketing spend, worth about $463 billion annually. Furthermore, the research indicates that players investing in AI are currently seeing a revenue uplift of 3 to 15 percent and a sales ROI uplift of 10 to 20 percent.

Current uses of generative AI in marketing mostly consist of off-the-shelf pilots integrated into existing workflows. These efforts are delivering immediate value by helping companies generate copy and images in less time, personalize campaigns, and respond to (and learn from) customer feedback more effectively. But they are also helping companies learn about generative AI for the future and build the capabilities they’ll need to take advantage of AI in unforeseen ways. This use of new technologies frees up valuable employees for higher-level tasks. That’s one of the primary attractions of generative AI, particularly among retail employers.

Personalization of Marketing Campaigns through AI

While we’re still learning and projecting future uses of this inchoate technology, AI does possess the potential to deliver value quickly, unlike other technologies that reward companies only after years of investment. Let’s take a quick look at how traditionally brick and mortar companies have taken on AI as an invaluable asset to marketing to customers.

One of the most obvious and perhaps beneficial aspects of AI in the marketing space has been the ability for corporations to personalize marketing campaigns. The global revenue of the customer experience personalization and optimization software industry is estimated to total $8.3 billion in 2022 and is set to grow to $10.7 billion in 2025, representing a Compound Annual Growth Rate (CAGR) of 8.8%.

According to a recent survey from Adobe, 87% of surveyed senior executive respondents agreed that the events of the pandemic have rewired customers to be digital first. Since 2020-2021, the overwhelming sentiment consistently demonstrates that consumers have grown not only accustomed to targeted marketing but nearly require it in order to expect to keep up with consumers’ rate retention. In a survey by McKinsey, 71% of consumers say they expect personalization with their online content. To further hammer home the importance of personalization in the marketplace:

• First-time purchases: 67% of consumers say their decision to buy from a brand the first time is influenced by relevant product or service recommendations.
• Repeat purchases: 78% of consumers reported how personalized experiences make them more likely to repurchase. The same number also say they are more likely to refer friends and family to companies that utilize personalization.

However, there appears to be a disconnect with how best to integrate personalized marketing campaigns. Despite the demand for personalization hitting new highs, many marketing teams are struggling to determine how to collect valuable customer data without cookies. In fact, 38% of practitioners surveyed by Adobe do not consider themselves prepared for a cookieless future. And the numbers aren’t any more encouraging when surveying senior staff. Not only do under half of senior executives believe marketers aren’t collaborating successfully with IT, but an even-lower 34% of practitioners score collaboration between marketing and IT at 8 or higher out of 10.

This is where generative AI has the capabilities to lead marketing teams and their strategies into the once-future, now present state of the field. Crafts retailer Michaels Stores, for example, has been at the forefront and major proponent of using generative AI as part of its approach to deepened customer engagement through custom generated and frequent interactions with its shoppers.

Since the first store was opened in Dallas, Texas in 1973, Michaels has grown to be the largest arts and crafts retail chain in North America with more than 1,200 stores in the U.S. and Canada. A major reason for their continued success has been Michaels’ connection with their customers, affectionately known as “Makers.” Since day one, the company has provided everything that beginners and experts alike need to complete an array of artistic, leisure, and home décor DIY projects from start to finish.

When faced with updating their modes of communication for the digital landscape, the big question for Michaels was not whether it should personalize its campaigns, but how, exactly, it would build those more meaningful, personalized relationships at scale. To do so, the company would need to search for a partner to spearhead a content generation and decision-making platform with the aim of copy development and quantitative understanding of how customer segments engage with different messages.

Michaels found that partner in 2019 when Persado, the Motivation AI company that generates personalized communications at scale, came knocking. Persado worked with Michaels with two goals in mind. The first was to put the Persado Motivation AI Platform to work in order to deliver campaigns with more engaging, personalized language that would drive loyalty and incremental revenue. And secondly, Persado was tasked with delivering insights that would allow Michaels to make creative, strategic decisions about their marketing and customer experience.

Michaels decided that it wanted Persado to focus on campaigns in three channels: SMS, Facebook, and email. The Persado Motivation AI Platform generates and predicts which words will perform best in any campaign using the most extensive proprietary language knowledge base of over a million tagged words and phrases mapped to human emotion. Essentially the AI technology would take the guesswork out of crafting customer messaging by tapping into the equivalent of 600 years of consecutive A/B testing.

How Persado used Generative AI to bring about an Omnichannel personalization strategy.

• Persado began by using the company’s content to build a custom language model that is true to Michaels’ brand voice.
• Persado then generated and deployed language experiments to feed predictive models that understand how customers engage with messaging across campaigns, channels, and audiences.
• Finally, Persado used those learnings to predict the right message for future campaigns, enabling Michaels to deliver more relevant content to its Makers.

Since its collaboration with Persado’s AI launch, Michaels has gone from personalizing 20 percent of its email campaigns to personalizing 95 percent. This has lifted the click-through rate for SMS campaigns by 41 percent and email campaigns by 25 percent. Michaels also saw a 41% CTR lift on SMS campaigns using the same strategy.

A model for marketing teams across industries, Michales’ structured customer data analysis provides concrete evidence on the case for ushering in generative AI practices into marketing practices. However, unstructured customer data analysis also benefits from more granular analyses of consumer behavior which can be augmented by generative AI.

Grocery shopping has undergone a remarkable transformation over the last 48 months. Digital sales have grown 3x, and there is a shift away from a singular focus on e-commerce. The majority of grocery sales in 2023 were digitally influenced (discovery, inspiration, order, pick-up, wayfinding, coupons, etc.). Digital purchases alone continue to hold steady, accounting for more than 13% of all grocery sales as of Q2 2023. Shoppers want to navigate seamlessly between online and in-store environments, and grocers must meet their diverse needs and preferences at every step of the journey.

A recent joint report titled “The Impact of AI in Grocery” from Grocery Doppio in partnership with FMI, The Food Industry Association and Wynshop, found that 69% of grocery sales as of 2023 were digitally influenced (i.e., discovery, inspiration, order, pickup, wayfinding, and coupons) and 73% of grocery technology executives expect AI capabilities to be embedded in most or all of their technology software by 2025.

San Francisco based, Maplebear subsidiary Instacart has already incorporated AI and machine learning solutions into its platform, offerings, services and features, including its Ask Instacart generative AI tool, which helps consumers personalize their shopping and Instacart AI plugin for ChatGPT. Last September, Instacart announced it had acquired Eversight, an AI-powered pricing and promotions platform, for an undisclosed amount.

Instacart is using generative AI to offer customers recipes and meal-planning ideas as well as generate shopping lists. A simple question like ‘What’s for dinner?’ is among the most complex for families everywhere to answer. From decisions about budget and dietary specifications to cooking skills, personal preferences, and so much more, Ask Instacart can help customers answer all of their food questions and deliver the ingredients for the perfect meal in as fast as an hour. Whether it’s, “What’s the best fish for tacos?” or “What should I make for a Memorial Day BBQ?,” by supercharging Instacart search with generative AI, Instacart promises to create a truly inspiring experience that unlocks even more opportunities to engage and help customers as they shop online from their favorite retailers.

Ask Instacart leverages the language understanding capabilities of OpenAI’s ChatGPT and their own AI models and unique catalog data that spans more than a billion shoppable items across more than 80,000 retail partner locations. Instacart was one of the first to build a plugin for ChatGPT and brought AI-powered search to its own app, providing customers with product recommendations that are intuitively organized, as well as additional useful information about food preparation, product attributes, dietary considerations, and more. The newly enhanced search experience also incorporates personalized question prompts into the search bar that anticipate customer preferences, remind them of their needs based on their shopping history, and inspire them to discover new products.

While technology innovation is gaining steam in the grocery industry, the Food Marketing Institute’s research indicates grocers have been more focused on technologies aimed at maintaining existing systems and operations. Only 12% of surveyed food retailers said they used in-store technology such as robotics and AI as part of their service differentiation strategies in 2022, per the trade group’s 74th annual Industry Speaks report. Instacart may have devised an answer to help usher grocers into digital retail.

The new Instacart Storefront, featuring AI-powered conversational search and In-Store mode.

Instacart Storefront is an end-to-end omnichannel digital commerce platform designed specifically for retailers. Bringing the best of Instacart’s proprietary technology to retailers’ owned-and-operated storefronts – including Costco in the US and Canada, Price Chopper/Market 32, and Tops Friendly Markets – the new Instacart Storefront is built on the same core infrastructure, including those powered by Instacart’s 150 AI models.

Instacart tests new features on its app and brings the most successful ones to retailers’ storefronts, giving them access to the best of the company’s e-commerce technology.

AI for opportunity identification and idea generation.

In our final analysis, some companies are finding value in the potential of using generative AI to analyze competitor moves, assess consumer sentiment, and test new product opportunities. Rapid generation of response-ready product concepts can improve the efficiency of successful products, increase testing accuracy, and accelerate time to market.

Mattel, for instance, is using AI in Hot Wheels product development to generate four times as many product concept images as before, inspiring new features and designs. Coupled with a Hot Wheels movie in the works and cross-promotional digital and physical tie-ins, Mattel has put the AI image generator DALL-E to work by having it come up with ideas for new Hot Wheels toy cars and endless consumer possibilities for designing customized cars. Used vehicle seller CarMax is summarizing thousands of customer reviews with the same “generative” AI technology that powers the popular chatbot ChatGPT.

Other consumer products stalwarts like Kellogg’s are scanning trending recipes that incorporate (or could incorporate) breakfast cereal and using the resulting data to launch social campaigns around creative and relevant recipes. And L’Oréal’s AI specialized system, TrendSpotter, is analyzing millions of online comments, images, and videos to identify potential product innovation opportunities. In fact, TrendSpotter scans 3,500 online sources — social networks like Facebook and YouTube, as well as cosmetic-focused online publications and bloggers — looking for what’s new and innovative. Meanwhile, the cosmetic company’s other AI powered technology Modiface technology allows virtual try-ons and skin-care tips. Customers may upload a photo of their face to “digitally” apply a host of makeup options from the convenience of their cell phone and laptop screens.