Introduction

While the use of artificial intelligence (AI) to generate messages creates new opportunities for retailers to produce content at scale, there is a risk that simply creating more content will merely add to the “digital noise,” as more businesses send more marketing messages across more channels. AI-generated, personalized language, in contrast, can cut through digital noise with relevant, engaging messages that help retailers drive conversion. Its success can be enhanced through first-party data containing insights about language elements that can better motivate consumers. 

Retailers that fail to innovate their digital marketing strategies risk leaving revenue and profit on the table—which is especially risky heading into a more uncertain retail and macro environment. 

In this Custom Report, we discuss how retailers can address revenue and cost challenges by engaging customers with AI-generated, personalized digital marketing.

This report is sponsored by Persado, the Motivation AI company that uses generative AI to enable companies to drive personalized communications at scale that motivate and engage individuals.

Current Retail Challenges 

Multiple marketing headwinds are likely to increase operational costs and make it harder for retail marketers to drive business growth in 2023: 

• An increase in digital advertising costs is making it costlier for retailers to acquire customers and drive incremental online revenue, putting pressure on digital marketing campaigns to become more efficient. According to a 2022 study by CommerceNext, rising customer acquisition costs are seen as the top obstacle to achieving 2022 e-commerce goals by 61% of retailers and 66% of digital-first retailers. 
• The protracted death of third-party cookies, along with tighter privacy restrictions on consumer data, will make it harder for retailers to understand their customers and provide more tailored digital experiences. The need for robust first-party data is mounting.
• Competition for online consumers’ attention has increased as they are flooded with more messages across more digital channels.

To make matters more challenging for retail marketers, a macroeconomic environment defined by decades-high inflation and high interest rates, is affecting the consumer heading into 2023: 

• The US personal savings rate dropped to 2.3% in October 2022—the lowest rate since 2005.
• According to a Coresight Research survey conducted in November 2022, 78.5% of US consumers have observed recent price increases in retail—and of those, almost half (49.4%) plan to buy fewer items to deal with inflation, while around one-third (32.8%) plan to delay nongrocery purchases.

To reach their 2023 top- and bottom-line growth objectives, retailers must increase the effectiveness of their digital marketing. 

Market Scale and Opportunity

We expect retailers to increasingly leverage AI to efficiently aggregate, augment and analyze first-party consumer data to enable marketing personalization at scale and drive business growth. 

According to research from Statista and Dash Network, global revenue for the customer experience personalization and optimization software and services industry is estimated to total $8.3 billion in 2022 and is set to grow to $10.7 billion in 2025, representing a CAGR of 8.8%. 

---

Figure 1. Global Revenue from Customer Experience Personalization and Optimization Software (USD Bil.)  

 

Motivating Customer Action and Driving Business Growth with AI-Generated, Personalized Digital Marketing: Coresight Research x Persado Analysis 

1.  How Marketing Campaigns Can Stand Out Amid Increased Digital Noise  

The rise of e-commerce coupled with retailers’ increased use of language-generation technology has brought waves of marketing messages to consumer inboxes, on websites and on social media. Shoppers can easily feel overwhelmed and perceive them as merely digital noise, rather than as relevant, interesting messages. 

As consumers reach this saturation point, we expect that the cost of conversion will continue to rise, putting even more pressure on marketers to pursue more effective digital marketing techniques that better engage consumers.

To break through the digital noise, retailers need to personalize their marketing. The most effective and efficient ways to do this will rely on a combination of real-time, aggregated consumer data and generative AI to produce motivating language tailored to specific individuals. 

Key benefits of personalized marketing that retailers can quickly realize include the “Three Cs”: customer motivation, customer loyalty and channel optimization (see Figure 2). 

---

Figure 2. “Three Cs”: Key Benefits of Personalized Marketing 

 

Personalized marketing presents an opportunity in retail today, yet there are obstacles to unlocking its potential, such as:

• Efficiently collecting, analyzing and drawing insights from data to establish the optimal marketing message in real time
• Leveraging consumer data to go beyond designing personalized product offers and accurately identifying the language elements that will motivate individuals to act based on a message 

Retailers have three levers to overcome these obstacles and better personalize their marketing messages across a variety of digital marketing channels: 

1. Leverage generative AI to produce and optimize language. Automate the process of generating the optimal language for a given message using Motivation AI (a specialized segment of natural language generation as termed by Persado) to create personalized messages designed to motivate the customer to act.
2. Use a data-backed approach to personalization. Base personalization strategies and approaches on current, accurate and relevant consumer data rather than generalizing about retail preferences of broad consumer segments. 
3. Track personalization performance. Analyze KPIs (key performance indicators) in relation to personalization techniques across channels to understand impact and identify high-potential opportunities for improvement.

2. Using AI-Generated, Personalized Messaging To Drive Top- and Bottom-Line Growth 

AI can be a powerful tool for retailers to drive operational efficiency and increase profits as high inflation and slower consumer spending hit retailers’ top and bottom lines. 

Retailers can increase digital marketing effectiveness by leveraging AI and machine learning (ML) to run sophisticated digital experiments that measure the impact of different versions of a marketing message to identify the highest-performing message elements. 

• Commonly used method: A/B tests that compare two versions of a message to see which performs better 
• More effective method: AI/ML-enabled multivariate experiments that enable fast and simultaneous comparison of multiple message elements to identify the optimal combination for high performance—the equivalent of running numerous A/B tests simultaneously 

AI platforms can leverage the simultaneous approach to select the best-performing message for each consumer segment. With increased granularity, the result is individualized, hyper-personalized messages that optimize customer engagement. 

Figure 3 presents the top improvements global marketers have seen in customer engagement through enhanced personalization, showing that personalization is becoming more useful, according to the latest findings from an annual survey conducted by digital experience platform Acquia. 

---

Figure 3. Improvements Seen in Customer Engagement Resulting from Enhanced Personalization (% of Respondents) 

 

Delivering motivating personalized content at scale, however, is one of the most challenging barriers to marketing success. Retailers need to take action to make sure they get personalized content right and drive better personalization at scale: 

• Retailers must use a data-driven approach based on mathematical reasoning—an area in which AI thrives—to inform personalization, instead of making assumptions. 
• Retailers should leverage specialized AI platforms that augment first-party data and translate it into readable insights to optimize the marketing message and drive business results. Previous Coresight Research and Persado research, conducted in November 2021, found that more than nine in 10 US-based retail executives currently use or plan to use AI or ML to offer personalized experiences to their customers. 

3. The Missing Ingredient for Effective Personalized Digital Marketing—Combining AI and First-Party Data 

A Coresight Research survey conducted in December 2021 found that while 71% of US brands and retailers think they excel in marketing personalization, only 34% of US consumers currently think retailers are succeeding at personalization. To improve the effectiveness of personalized digital marketing, retailers need to use first-party data, as shown in our November 2021 survey of US-based executives whose organizations use first-party data for marketing purposes:

• Nearly four in five (78.2%) respondents see first-party data as “very important” for AI in digital marketing.
• Enhancing personalization is among the top benefits of using first-party data (see Figure 4).

Read more findings from our survey in Coresight Research and Persado’s separate report, AI-Powered Language: A New Era of Enhanced Customer Engagement.

---

Figure 4. Topmost Benefits of Using First-Party Data (% of Respondents)

 

AI-generated personalized language that leverages enhanced first-party consumer datasets is the missing piece of the puzzle that will enable retailers to meet consumer expectations for personalized experiences at scale. 

Marrying first-party data with AI-generated personalized content brings optimal results when applied at each stage of the customer journey and through all customer contact channels, as each moment and context may require a different personalized message. For example, a Coresight Research survey conducted in October 2021 found that US consumers prefer to receive personalized marketing through certain channels over others: website and email (each cited by 32% of respondents) are the top channels in which consumers prefer to receive personalized marketing.

Retailers can take the following specific actions based on these insights: 

• Retailers should adopt AI solutions that leverage first-party data and enhance it to ensure consistency of communication to individual customers across all channels. Retailers should invest more in channels that have a higher impact.
• Retailers should emphasize language personalization within their proprietary websites, email campaigns and loyalty apps. This becomes more important as social advertising becomes less effective at driving engagement due to growing privacy constraints.
• Retailers should emphasize the moment of engagement with the customer and use AI together with first-party data to dynamically identify the best tailored message to the customer in real time.

Driving Business Results with Personalized Marketing: Michaels Case Study

Michaels, a leading arts and crafts retailer in the US, wanted to increase its use of personalized marketing across its social, email and SMS channels. The company realized it needed to automate the process and turned to Persado.

Persado used Michaels’ existing content to build a custom language model true to the brand’s voice. With its Motivation AI, Persado generated and deployed language experiments to feed predictive models to understand how to best personalize for customer engagement. These insights allowed Michaels to grow its personalization efforts, and the company now personalizes over 95% of its email campaigns.

Michaels reported the following results due to its enhanced marketing personalization: 

• Increased engagement and loyalty, with a click-through rate (CTR) increase of 41% in SMS campaigns
• Boosted engagement and loyalty resulting in a CTR increase in email campaigns of 25%

What We Think 

Consumer mindsets and shopping behaviors will continue to evolve as the economic outlook dims and retail trends shift—it is more important than ever to understand consumer motivations and mindsets and provide personalized messages and offers to engage consumers and optimize marketing campaign performance. 

Retailers that use AI to more actively leverage first-party data will drive top- and bottom-line business growth—despite macroeconomic uncertainty—by enhancing customer engagement, driving new customer acquisition, and motivating shoppers to complete their purchases. 

---

About Coresight Research Custom Reports

Coresight Research Custom Reports are produced as part of commercial partnerships with leading firms in the retail, technology and startup ecosystems. These Custom Reports present expert analysis and proprietary data on key topics in the retail, technology and related industries, and enable partner companies to communicate their brand and messaging to a wider audience within the context of brand-relevant research.