Semantic search offers results based on the user’s geographical context, the user’s past search history, and user intent. Personalization uses the searcher’s previous searches and interactions to determine response relevance and rank. Semantic search can also rerank results based on how other users have interacted with the responses it has pulled. For example, when you type "restaurants" into your search engine, it will produce results that are in your area. With a better understanding of user intent, semantic search can respond to a query like "Creuset vs. Staub dutch ovens" with content that prioritizes product comparisons because that is the user’s intent. Semantic search will recognize the intent behind “best Staub deals” or "Creuset discounts" as intent to purchase and offer responses accordingly. Another example is predictive text. As you type a query into a search bar, it uses semantic search to complete your query and suggest relevant search terms based on context, common searches, and past search history.