A customer journey is the combined experiences and encounters people have with your brand. Often, the customer journey refers to the pathway from brand discovery to a first purchase. But marketers recognize that the journey can — and should — continue past a single purchase into multiple customer experiences over the customer's lifetime.
Marketers create customer journey maps to chart the in-person and digital touchpoints where brands connect with customers. Along the journey, customers encounter everything from basic brand info, like NAP data, to AI search results generated from sentiment in first- and third-party reviews.
Stage 1 – Attraction: A customer develops awareness and interest in your brand
Stage 2 – Nurture: A customer encounters relevant information about your brand
Stage 3 – Conversion: A customer begins to interact with your brand consistently
Stage 4 – Engagement: A customer develops an attachment to your brand
Stage 5 – Transaction: A customer buys a product or service offered by your brand
Stage 6 – Adoption: A customer actively uses the product or service they purchased from you
Stage 7 – Loyalty: A customer buys from you over and over again, demonstrating a tried-and-true preference for your brand
Stage 8 – Advocacy: A customer freely shares positive information about your brand, perhaps in an online review or through word-of-mouth referrals
Stage 9 – Ambassadorship: A customer becomes a paid spokesperson for the brand, often supporting engagement from customers on their new journeys
How is AI search impacting brands and the customer journey?
AI search has redefined the customer journey by blurring the lines between Attraction and Engagement. How? Customers now begin their journey with unbranded searches that sound like conversational queries. These queries also sound a lot like context-rich late-funnel questions.
Plus, they aren't just asking questions. Customers from every generation are in dialogue with AI-powered chat interfaces. They're also expanding the role of social media and pushing away from traditional search engines.
Today, only 64% of customers search for products and services on traditional search engines first. Nearly half (45%) are likely to use and trust an AI tool to find information about a brand. Meanwhile, the shift to AI-driven search experiences is happening fast.
Suddenly, it's much harder to discern where customers are in their journey. To adapt, brands must craft flexible marketing strategies to meet customers with exploratory and transactional intents that look very similar.
How can brands adapt to AI's impact on customer journeys and experiences?
As AI-driven search adoption grows in the customer journey, brands that use a knowledge graph in their data strategy stand to attract the most new customers. Why? Structured and unstructured data fuel generative AI. Structured data, like location and hours, ensures foundational accuracy. Unstructured data, like managed reviews, social posts, and other enhanced content, gives generative AI the context it needs to compose relevant responses.
Both types of data work together to attract customers. When centralized in the Yext Knowledge Graph, your local listings, photos, reviews, social media highlights, and more are structured in a way that helps AI models "understand" the data — and surface it to customers. Thus, a Knowledge Graph becomes the key to finding SEO success in generative search — anywhere and everywhere your customers are in their journey.
Want to better understand the digital customer journey for every generation?
Yext's 2024 Digital Customer Journey survey reveals how customers from each generation make buying decisions. Explore all the data and insights collected from customers in France, Germany, Italy, the United Kingdom, and the U.S.