A branded search occurs when customers look online for a specific product or service using the brand's name or its variations. A customer does a branded search when she asks Siri for directions to the nearest "Tim Hortons" or he types "Tims Coffee" into a search engine.
Unbranded search is when customers look for information without using a specific brand name. Think, "female dermatologist doing tattoo removal" or "biggest selection of low-light houseplants." Unbranded search is often the first stage in a customer journey, and it's a gateway to brand discovery and local SEO success.
How can brands surface more in unbranded searches?
While 84% of customers still use "traditional" search engines, 45% of customers are likely to use and trust an AI-driven search experience. AI is becoming an undeniable factor in local SEO marketing.
With tools like ChatGPT and Perplexity, search queries are evolving. Customers used to ask, "best Italian restaurant near me." Now they wonder, "Where can I reserve a table at an authentic BYOB Italian restaurant with gluten-free pasta?"
To stay discoverable in the Age of AI and unbranded searches, brands need a strategy for structured and unstructured data. So, what is structured vs. unstructured data?
Structured data
Structured data is organized in a schema markup that search engines and AI can crawl and make meaning out of. It's like a shared vocabulary, and it should be centralized in a knowledge graph that serves as a single source of truth about your brand.
Structured data compels AI-driven search experiences to trust your brand when they see it.
Structured data includes NAP data, hours of operation, and product or service descriptions. That's why it's essential brands manage it so it's always accurate, up-to-date, and consistent across business listings.
Unstructured data
Unstructured data is information that does not fit into a schema markup. Think of it as enhanced content. It can be text-based, like a blog post introducing a new physician at your practice. It can also be image or video files that show the behind-the-scenes stories of how your new seasonal menu came together.
Unstructured data gives AI the context it needs to surface your data in conversational, unbranded search.
Here are a few more examples of unstructured data in enhanced content:
1. Customer reviews contain keywords and rich, descriptive language AI uses to surface relevant features and rank data.
A review saying "friendly staff and a cozy, quiet atmosphere" might appear in an unbranded search like, "Show me three cozy, out-of-the-way restaurants with great service that isn't too loud. Prioritize Vietnamese or Thai cuisine."
2. Social media posts with images, videos, hashtags, and UGC provide real-time context about events, promotions, or trends linked to a brand.
An IG Stories recap, tagged "live instrumental jazz" and "jazz lounge," can feature clips from previous events, but the posts inform AI results for "Where can I meet friends on the north side of Chicago for live music this weekend?"
Branded search, unbranded search, and AI
The shift toward unbranded, conversational queries is accelerating. Brands that don't adopt a strong data strategy risk losing to rivals using AI-driven search strategies.
While branded search builds trust and helps guide customers deeper into their journey, unbranded searches introduce your brand to customers for the first time. Optimizing for these queries drives foot traffic, builds awareness, and opens doors to untapped audiences.