In today’s marketing world, generative AI promises to deliver highly personalized customer experiences at scale. However, ensuring high-quality, unified customer data to effectively power these advanced AI tools is a significant obstacle.

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• Marketers are eager to use generative AI for personalization, but poor customer data quality risks derailing these efforts.
• Building a robust and unified customer data foundation with AI-powered profiling is crucial for effective AI marketing.
• Brands investing in data quality may gain a competitive edge by delivering seamless, highly personalized experiences.

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AI Marketing’s Issue: Getting Customer Data Right for Better Experiences

The Key Highlights:

• Marketers are eager to leverage generative AI, with 70% already using it and 19% testing it.
• Top use cases include personalization, content creation, and market segmentation.
• However, poor data quality can derail AI marketing efforts, creating impersonal and frustrating experiences.
• To unleash AI’s full potential, brands must establish a unified, solid customer data foundation.

The Problem: When Data Falls Short

Imagine buying new ski gear online using a retailer’s AI personal shopper. If the AI needs more complete data on your purchase history and preferences, it may ask you for basic information it should already know. With a comprehensive view, its product recommendations could be better, leaving you satisfied and more likely to purchase.

The Solution: Unified Customer Profiles

Now, picture the same scenario with AI powered by accurate, unified data on your customer journey. The AI greets you warmly, referencing your past purchases to provide tailored product suggestions and direct purchase links. You enjoy a smooth, highly personalized experience from start to finish, increasing loyalty and potential spending.

The Benefits of Data Quality for AI Marketing:

• Standout customer experiences with relevant offers, seamless interactions, and end-to-end personalization.
• Operational efficiency gains like faster time-to-market, less manual work, and better campaign ROI.
• Reduced computing costs by minimizing unnecessary back-and-forth conversations with customers.

Building a Robust Data Foundation

Overcoming poor data quality requires brands to establish a unified customer data foundation connecting all touchpoints—from the first interaction to the latest purchase. Leveraging AI models can uncover these connections at scale, creating comprehensive customer profiles to inform marketing AI efforts accurately.

Best Practices:

• Clearly define use cases and expected outcomes for AI marketing initiatives.
• Carefully evaluate if generative AI is the appropriate solution.
• Prioritize data quality and build unified, AI-powered customer profiles.
• Start with manageable, human-monitored use cases like generating email subject lines.

As generative AI reshapes marketing, brands that invest in high-quality customer data may gain a significant competitive advantage, delivering the seamless, one-to-one personalized experiences modern consumers crave.