Don’t Leave Generative AI for Customer Experience and Marketing on Autopilot

The Gist

• AI emphasis. Generative AI for customer experience and marketing is fast becoming a "must-have" for optimized, personalized campaigns.
  
• CX paradox. Simply increasing content volume doesn't guarantee value; only 5% of consumers find digital interactions with brands valuable.
  
• Insight gap. Using generative AI without adequate customer understanding risks amplifying existing marketing blind spots.

By now, we’ve all heard the promise of increased productivity that generative AI for customer experience and marketing will bring to a variety of functions. Naturally, over time, productivity segues into growth, which is at the top of CEOs’ lists of priorities, according to the most recent Gartner CEO and Senior Business Executive Survey.

Generative AI for Customer Experience and Marketing: A Game-Changer

Generative AI for customer experience and marketing and its ability to automate the rapid production of more personalized creative content makes it a “must have” for marketing, sales and digital commerce initiatives. More than half of marketing teams are already leveraging AI heavily to create, execute and optimize campaigns. What’s more: executive leaders deem customer experience (CX) and retention as the primary focus of generative AI investments.

Related Article: 3 Ways Ecommerce Brands Can Use AI for Personalization

More Content, Less Value: The CX Paradox in Digital Marketing

However, simply “doing more” and investing more does not guarantee growth. While the volume of content, ads and notifications that customers receive daily is proliferating, the value they attach to the content is strikingly low. Our research shows that only 5% of consumers recall experiencing valuable digital interactions with a brand when considering a purchase, reinforcing my previous guidance on ensuring customers are at the center of customer experience, not channels.

Don't Autopilot AI: The Risk of Amplifying Marketing's Insight Gap

Customer understanding is a top capability gap for marketers. Therefore, it’s highly likely that the digital experiences and content created is based on assumptions vs. customer insight. Using generative AI for customer experience and marketing to produce experiences en masse could only exacerbate the issue as these tools create derivatives of what already exists. Don’t leave this mission on autopilot.

Smart AI Use in Marketing: Balancing Mass Production with Customer Insight

As a part of a marketing leader’s overall strategy, evaluating generative AI for customer experience and marketing use cases that help accelerate a renewed emphasis on customer research and insight should be supplemented by human oversight to avoid biases and inappropriate uses. Think applying generative AI to VoC data to detect themes in customer data such as surveys and customer reviews. Doing this can help organizations detect drivers of satisfaction, dissatisfaction and even product enhancement opportunities across the customer journey. In turn, they can more effectively and efficiently create experiences that address those critical moments. Consider these two theoretical examples:

1. A hotel brand applied generative AI to customer reviews to surface themes. The brand discovered that there was a pattern in neutral or negative reviews that mentioned their hotels were not pet friendly after booking or that it was hard to determine whether that hotel allowed pets. The hotel brand made the decision to test a filter that allowed customers to find hotels that were only pet friendly. After finding that this tool was highly utilized, they decided to test integrating pet-related experiential benefits into their loyalty program.
2. A fitness wearable device company applied generative AI in order to detect trends in their customer feedback data, as they were looking for ways to increase the daily utilization of their health insights dashboard. They learned that many customers were overwhelmed by the data on the dashboard and felt like the data was only for elite athletes. Customers left comments about wanting to be able to apply the data to their own situation. As a result, the brand made the investment to create fitness journey "tracks" that customers could follow based on personal and lifestyle data inputs in their user profiles. The dashboard included data ranges and averages that customers should look for in each track. The brand’s content marketing team featured customer stories across different channels that highlighted user-generated content (UGC) and stories about what customers learned about themselves and how they overcame challenges using certain data features.

Both examples show the need for real brands to open their eyes to their customers first before jumping to other mass produced content without the listening piece.

Related Article: Dealing With AI Biases, Part 1: Acknowledging the Bias

How Generative AI Can Be Leveraged to Support Better CX

Even in the face of shifting customer preferences, here are three ways generative AI can help enterprises enhance both productivity and CX:

1. Shift focus from more tactical tasks, such as design production, to customer research, strategy and content curation. More resonant and engaging customer experiences will result. Regard generative AI as a complement to human expertise, not a substitute.
2. Optimize product choices and potentially influencing customers’ decisions — by nudging them toward different options — can accelerate adoption of new products or services.
3. Enhance value for customers by educating them on how to use products and services better, anticipating their needs and validating purchase decisions, among others. Consider using generative AI to onboard new customers or assist agents to give contextualized information and advice in real time.

Final Thoughts on Generative AI for Customer Experience and Marketing

There are a number of promising use cases for generative AI for customer experience and marketing. However, if customer understanding is an area lacking maturity at your company, and your organization (like many) is actively exploring how to apply generative AI to marketing, consider prioritizing your use case for customer understanding ahead of others. Customer insight should be at the top of your “order of operations” to avoid the trap of generating a large volume of neutral experiences vs. ones that are notable.

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