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AI fueled by First-Party Data


Unlocking the Real AI Potential: Improving product ownership interactions with first-party data.

You’ve probably seen firsthand how a lack of first-party data can result in frustrating AI experiences, for both customers and employees. Chatbots that can only answer broad-ranging basic questions, irrelevant offers that target the wrong audience, support queues that require customers to repeat the same information multiple times. Each of these experiences has the potential to be beneficial to both the customer and the brand, but without the right data underlying the AI technology, they fall short.

How first-party data enables AI personalization 

First-party data gives brands a significant advantage when seeking to engage customers via AI. It’s the difference between an AI chatbot that welcomes every customer with “Hello! How can I help you?” – and then often proceeds to be less than helpful – and an AI with built in decision intelligence that greets a specific product owner in a personalized way, such as “Hi Bill! Do you have a question about using your coffee maker?” 

Because first-party data includes information and identifiers that a brand acquires directly from customers, it is more accurate and reliable than secondhand data. Another advantage of first-party data is that it’s highly customizable as brands can tailor their data collection to gather the specific types of information that are most relevant to their business, customer experience goals, and how they intend to leverage AI. As such, first-party data can include rich contextual information about customer behaviors, preferences, and interactions with the brand that when applied to AI-enabled technology, such as the Registria OXM Platform, elevates customer experiences to the next level. 
Equally as important is that when first-party data is collected, companies set clear expectations with customers about how the data will be used. This transparency tends to increase customer trust and encourages them to voluntarily share their personal information, understanding they will receive a better future experience from the brand.  
A majority of today’s consumers are willing to share their information in exchange for more personalized offers, better support and more convenient access to the information and resources they need – as long as the brand is clear about how the data will be used, protects their data, and respects their privacy by not sharing the data with unauthorized parties.   

According to McKinsey research, 71% of consumers expect companies to deliver personalized interactions – and 76% get frustrated when companies don’t deliver on this expectation. 

Collecting first-party data during customer onboarding 

Durable goods brands can benefit from collecting various types of data to leverage AI effectively in their operations, across their tech stack, and in their decision-making processes. The specific data requirements may vary depending on the organization’s goals, but here are common types of first-party customer data that brands should consider collecting for AI: 

  • Owner Information: Basic but necessary owner data includes name, address and contact information such as email and phone number. This information helps manufacturers personalize interactions to the individual.
  • Purchase History: Understanding which product(s) customers own and when and where they bought the product(s) can provide valuable insights for targeted marketing, personalized recommendations, or contextual support.
  • Communications and Privacy Preferences: Given increasing consumer concerns about data security and privacy, it's essential to collect and respect opt-ins and to be transparent about how the consumer data will be used. It should be clear to the consumer how they can opt-out, as well.  
  • Product Preferences and Behaviors: Conducting surveys and questionnaires can help brands gather specific information on customer preferences, shopping habits, product likes/dislikes, satisfaction levels, behaviors, and more, which can take a brand’s AI to the next level.

For durable goods brands, one of the easiest and most reliable methods to acquire first-party data is through product registration. Modern product registration has become part of a carefully crafted digital onboarding experience during which brands can collect valuable first-party data, including all of the above data types.  

This digital onboarding process provides product owners with a convenient and efficient way to engage with the brand, while at the same time allowing the brand to collect first-party data that can be used to fuel AI initiatives that improve the customer experience. 

How first-party data fuels effective AI 

First-party data is highly valuable due to three key factors: it’s self-reported, it’s time-based, and it’s specific to the product owned. When used in conjunction with AI, first-party registration data can be leveraged across the business, from fueling personalized AI-led marketing campaigns to better equipping product owners with AI-enabled support options.  

  • Targeted Marketing Offers: Product data collected during registration enables brands to present related offers such as accessories, consumables, and Care plans. Research shows that customers prefer to buy these items directly from the brand as opposed to third-party vendors. 

Thermacell, an outdoor recreation brand that specializes in mosquito repellent devices, uses registration data to personalize follow-up offers. They have realized a 17% CTR on refill offers, in addition to 40% of product owners buying refills during registration. 

  • Personalized Product Recommendations: Knowing what product was purchased and when opens the door for brands to notify customers when an upgraded product model is available. Brands can also derive insights about other products the customer may be receptive to based on their currently owned products.
  • Enhanced Customer Service: Both owner and product data can improve customer service and support when these teams have access to current data. With first-party data, both AI chatbots and support personnel become more effective. As a result, customers are more satisfied with their support experience and brands reduce ACHT. 

Since implementing digital onboarding, luxury products brand Shinola has documented a reduced workload on sales and customer service teams as a result of having access to more accurate, comprehensive data across the organization.

  • Proactive Maintenance Alerts: Using first-party data and AI, brands can proactively remind customers when maintenance is recommended. This can help their products last longer and contribute to a positive image of the brand. First-party data is also essential for brands to keep customers informed of active recalls.
  • Product Development: AI can analyze vast amounts of first-party data to uncover patterns, correlations and preferences that can be used to drive product development. This level of customer insight simply isn’t possible without AI and first-party data. The same methods can be used to enhance the brand’s marketing strategy.  

First-party data is the foundation upon which comprehensive, effective, and trustworthy AI-driven customer experiences are built. It empowers brands to better understand, engage with and serve their customers in a highly personalized and effective manner while respecting data privacy and compliance requirements.