A conversational way to shop Rather than typing brand names into a search bar and sifting through pages of results, shoppers can describe real‑life needs in natural language, like “the best winter jacket if I live in San Francisco and take a ferry to work.” Perplexity then surfaces options that match the actual context, weather, commute, use case, rather than generic “best of” lists.
Follow‑up questions such as “What about boots?” sit in the same conversation, so the assistant keeps track of your style, climate and earlier constraints.
This conversational layer is built on the same assistant logic Perplexity uses across browsing, email and task tools, where AI is meant to scale the user’s thinking instead of replacing their judgement. An assistant that remembers you With memory turned on, Perplexity learns from past searches to refine future recommendations.
If you have previously asked about mid‑century modern furniture, the assistant can prioritize that aesthetic when you next look for a desk lamp. If you have been comparing minimalist running shoes for a marathon, it can keep that preference in mind when helping you pick a race‑day bag. This personalization is designed to…