The Evolving Role of Local Citations in Answer Engines

The new role of local citations in answer engines.

If you’ve heard it once, you’ve heard it a thousand times, search and local SEO are changing. Now we talk about AI optimization (AIO) and the importance of answer engine (AE) readiness, because thanks to ChatGPT, the ways consumers search have changed dramatically. Local citations were at the core of traditional SEO and continue to play a role (albeit an evolved one) in answer engines, and today we’re looking closely at this shift.

The Transition From Traditional Search Engines to AI Search

ChatGPT has quickly become a go-to search engine, especially for younger consumers, and is one of the reasons changes in search are moving so swiftly. ChatGPT, Google Gemini, Microsoft CoPilot, Perplexity and Grok are examples of generative AI answer engines. These large language models (LLMs) pore over tons of data to understand the vastness of information on the web, compile it, then summarize it into a simple answer.

Answer engines differ from traditional search engines in user experience as well as back-end data use. Consumers interact with AEs in a conversational manner, where intent is gauged and answers returned. Questions build on one another for longer “conversations,” meaning that good, clean data needs to be readily available.

Traditional search engines focused on specific keywords and phrases. Fighting for those was the difference between ranking highly in Google and Bing or being cast into the shadows, behind the competition. Understand that both traditional and AI search share an important base—the need for clear, reliable data in the form of a local business citation. In the same way that bad citations ruin ranking chances in Google, inconsistent local citations can damage your clients’ AI visibility.

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