Feature
The Gist
- Strategic integration. Generative AI in customer experience and marketing is revolutionizing the field — offering tools for campaign simulations, ad creative optimization and personalized recommendations.
- Content creation. More than 100 billion pieces of content, including articles and social media posts, have been produced by generative AI.
- Safety first. While generative AI offers transformative potential, it's essential to approach its deployment with caution, considering risks like misinformation, biases and security concerns.
Once the realm of science fiction, today the use of generative AI in customer experience and marketing is shaping real-world interactions between brands and consumers. From smart chatbots that offer instant customer service to intricate data analytics that enable personalized recommendations, generative AI technologies are no longer optional — but increasingly integral — to effective, customer experiences and engagement strategies.
Let’s delve into the varied ways generative AI in customer experience and marketing is revolutionizing the landscape of customer behavior, breaking down the hype to reveal actionable insights.
What Is Generative AI?
Generative AI normally refers to AI systems whose primary function is to “generate” content. Its arrival marks a significant leap in the field of artificial intelligence, extending its capabilities beyond mere data analysis to the creation of original content across multiple formats — from text and images to audio, code, simulations and videos.
How Can Generative AI Help CX and Marketing Strategies?
The impact of generative AI in customer experience (CX) and marketing strategies has been transformative, enabling unprecedented levels of automation, efficiency and personalized customer experience. Today, generative AI is being used in a variety of applications.
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Marketing campaign simulations
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Optimizing ad creatives
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Personalized recommendations
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Interactive simulations for product experience and enhanced customer experiences
Enhancing Customer Experience in Ecommerce With Generative AI
In campaign planning, generative AI facilitates simulations of various marketing strategies, providing a virtual testing ground to optimize campaigns before actual implementation and plays an instrumental role in refining ad creatives by generating and analyzing myriad versions to achieve optimal results. Beyond mere automation, generative AI engages customers through AI-generated content, such as chatbots for routine queries or personalized news feeds. The algorithms behind these AI systems also deliver personalized recommendations in ecommerce, elevating both sales and customer satisfaction. Further, the use of generative AI in creating interactive simulations offers a novel, immersive approach to product and customer experience, too.
Related Article: AI Customer Experience: Not Quite Ready for a Solo
Generative AI in Customer Experience and Marketing: How to Craft a Game Plan
Businesses should start by selecting the appropriate generative AI platforms and tools tailored to their specific needs and goals, followed by a detailed implementation roadmap, delineating tasks, timelines and responsibilities to ensure a smooth rollout.
Among marketers, generative AI is most often used for creating content — and has already produced more than 100 billion pieces of content including articles, blog posts, social media posts and more 2023 State of AI Report by HubSpot.
Grammarly, a popular writing app that offers spelling, grammar and style suggestions, has incorporated AI for around 14 years — and while it’s still early days for generative AI, Matt Rosenberg, CRO at Grammarly and head of Grammarly Business, says the impact has been profound, with editing times cut by 60%, a 17% boost in both customer retention and satisfaction scores and half the rate of escalations.
Avoid Lackluster Content With Generative AI
However, he cautions, context and personalization are critical for businesses to gain value from generative AI — otherwise, they’re left with generic, lackluster content that isn’t relevant to their business or customers.
Foundational Principles of AI Deployment
On the roadmap to success, he advises companies establish “foundational principles” to deploy and use generative AI in customer experience and marketing effectively, including organizational readiness, a cohesive approach to customer journey with clear objectives, dedicated training and guidelines and usage policies.
Finally, a robust framework for using predictive analytics and measuring ROI should be in place, capturing key performance indicators such as customer engagement, conversion rates and operational efficiency to assess the impact and success of the generative AI initiatives.
Evaluating Needs and Readiness
Consider the limitations and risks of the generative AI tools you’re looking at — and whether you have the infrastructure and operations in place to manage them. From there, Rosenberg advises setting a purposeful, long-term strategy with clear outcomes and use cases. Further, ensure buy-in across stakeholders and IT to “save you from headaches and wasted resources spent right-sizing down the road.”
Build Literacy Around Generative AI
A study conducted by Forrester Consulting reveals that while nearly 70% of respondents use generative AI for some or all of their writing — 80% work at companies that haven’t officially adopted a comprehensive strategy for its use.
With widespread ungoverned use, the dire need to build literacy around generative AI becomes tantamount to securing a coordinated implementation. To avoid the risks of unsanctioned use.
Rosenberg suggests that companies provide dedicated training and clear usage guardrails.
Experiment and Play With Generative AI Tools
Cristina Lawrence, EVP of consumer and content experience at Razorfish, said her company is still at the stage where it’s critical that teams continue to experiment and play with generative AI tools, adding, “it’s the only way one will get a sense of how these tools can be effectively used to get work done. Hands-on discovery will lead to personal use cases and adoption.”
“One of the approaches that we took early on at Razorfish was the establishment of pilot programs, where we have been onboarding specific generative AI tools and establishing benchmarks against certain project types to see if these tools are making a sizable impact on efficiency, while maintaining (or improving) quality,” Lawrence said. “This data-based approach is a tremendous tool for furthering adoption and getting teams hands on with new processes or ways to work.”
Related Article: Don’t Leave Generative AI for Customer Experience and Marketing on Autopilot
What Are Common Misconceptions About Generative AI in Customer Experience and Marketing?
Generative AI holds unparalleled potential in revolutionizing customer experience and marketing, but it's not without its pitfalls. According to Rosenberg, the biggest mistake companies make with generative AI is rushing in without a clear, coordinated strategy.
Don’t Rush Your Generative AI Game For Optimal Customer Experience
With the inherent fear of falling behind, many companies want to jump in and start reaping the benefits of generative AI. But Rosenberg cautions, doing so opens companies up to long-term risks and disadvantages.
For its part, Grammarly invests in benchmarking to ensure they can show the value their product delivers and illuminate the new strategic opportunities AI can solve for customers for safer deployment at scale and boost customer retention.
“If we don't handle generative AI properly, it can pose some significant risks, such as spreading misinformation and biases as well as privacy and security threats,” Rosenberg said. “Companies need to thoroughly understand both generative AI’s capabilities and limitations so they can manage expectations and carefully plan and execute their adoption strategy.”
Adopt Clear Generative AI Objectives
Even with the best technology in place, companies can still go astray by not defining their objectives clearly. In the rush to adopt, many also fail to clearly define their objectives by implementing AI technologies and novel machine learning tools that don’t have a clear purpose.
“The key is intentional deployment,” Rosenberg said. “Focusing on solutions that are designed to improve internal team skills and productivity will naturally have a positive impact on customer interactions and brand image, reducing complexity and risk in the long run.”
What Are the Risks of Deploying Generative AI in Marketing and CX?
Strategy is just one part of the equation. A critical but often overlooked factor are the inherent risks associated with generative AI, including the spread of misinformation and biases, as well as privacy and security concerns.
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According to a recent Gartner study, two-thirds of consumers are concerned about discrimination or bias in generative AI. And what every organization should be focusing on right now, according to Lawrence, is the creation of generative AI standards, safety and governance, and “the need to begin creating the right policies and processes that guide how these tools should be used internally and externally to ensure brand safety.”
Enterprise Security and Privacy
A sentiment echoed by Rosenberg, who also insists that when it comes to selecting generative AI technologies, safety is just as critical as quality — yet most companies simply don’t know how to assess the security of potential providers.
“Enterprise-grade security and privacy are absolutely essential in any deployment to protect company and customer data, and ensure you always stay in control,” he said. “When working with vendors, ensure the involvement of your IT and security teams to ensure information is protected. Aligning around a coordinated strategy and solutions is essential to avoid fragmentation, which increases business risk.”
Generative AI in Customer Experience & Marketing: Transforming Business, With Caution Urged
In an era where technology is rapidly evolving, the use of generative AI in customer experience and marketing is a transformative force, reshaping the dynamics between brands and consumers.
However, with great power comes great responsibility. As companies race to harness the capabilities of generative AI, experts emphasize the importance of a clear, coordinated strategy, understanding its limitations, and ensuring safety and governance.
