Price comparison and AI
I wonder to what extent ChatGPT, Gemini or Claude will eat the lunch of various price comparison sites. Looking at early examples like Google’s Flight Deals and Perplexity Shopping, these AI-powered tools make it incredibly easy to use natural language to find the best deals relevant to you. Think about prompts where users ask for a product in a specific price range, or users asking AI to search for a trip to a winter destination that meets specific criteria.
There are three reasons why LLMs can successfully challenge existing comparison sites:
Contextual Understanding
I know “personalisation” is an overused buzzword, but LLMs can take into account user-specific traits, behaviours and preferences to provide highly relevant answers or recommendations. AI can consider:
- A user’s past choices (e.g. always picks aisle seats, prefers boutique hotels, buys eco-friendly brands)
- A user’s life context (e.g. parent who prioritises family rooms and prefers non-stop flights with free cancellations)
- A user’s goals (e.g. wants the cheapest airfare, even with flight transfers vs wanting to maximise airline points to hit Platinum status)
AI can parse highly specific requests like “Find me a flight to London under £200 that leaves after 10am and doesn’t land at Gatwick” or “Show me car insurance that covers my 19-year-old daughter but doesn’t penalise me for ride-sharing.” Traditional comparison sites have been more limited by basic filters like “non-stop only” or “sort by price”.
Established price comparison sites are now playing catch-up by introducing their own AI assistants and search capabilities. For example, Romie — Expedia’s new AI assistant — helps travellers plan their itineraries and enables them to add their own filters (e.g. rooftop views or early check-ins).
Predictive & Adaptive Recommendations
LLMs are effectively prediction machines, which means they can anticipate user needs based on a user’s profile and behaviours. As a result, AI can say: “Last time you picked flights with 2 check-in bags, here are options with luggage included” or “You usually buy midrange phones every two years. The Pixel 9 is about to launch, so here are deals if you wait a month.” Comparison sites typically don’t predict — they use current price information to show the best deals.
Looking at example outputs from Perplexity Shopping and Google Flights, I notice two key advantages:
With Google Flights, users can create really specific prompts and get highly nuanced responses in return. For example: “Find me the cheapest flight from London to Madrid that lets me earn British Airways points, departs early in the morning and includes check-in luggage for 2 passengers.”
When AI responds, it balances cost with personal preferences. I also expect products like Google Flights to both predict price drops and send notifications to users monitoring prices of certain flights or accommodations. Google has been developing an AI product tracker which can track specific products and alert consumers when prices drop below a certain level.
US-based users of Perplexity Pro can use “Shop Like a Pro”, Perplexity’s native checkout experience, similar to Google AI Mode. OpenAI is also developing an integrated checkout feature so users can complete purchases without leaving ChatGPT.
I can imagine that with Perplexity storing my user profile and past purchase history, I’ll get much more tailored product and deal recommendations. Especially if I use Perplexity’s new Comet agentic browser as my personal assistant to perform tasks across different websites and apps.
From a brand perspective, startups such as Profound, Refine and Algolia offer the ability to monitor brand presence in AI chatbot and agent responses.
With Google Flights, users can create really specific prompts and get highly nuanced responses in return. For example: “Find me the cheapest flight from London to Madrid that lets me earn British Airways points, departs early in the morning and includes check-in luggage for 2 passengers.”
When AI responds, it balances cost with personal preferences. I also expect products like Google Flights to both predict price drops and send notifications to users monitoring prices of certain flights or accommodations. Google has been developing an AI product tracker which can track specific products and alert consumers when prices drop below a certain level.
Main learning point: AI-powered comparison tools are fundamentally changing how we shop by understanding context, predicting needs, and providing personalised recommendations that traditional comparison sites simply can’t match. The future of price comparison isn’t just about finding the cheapest option — it’s about finding the right option for you.
Related links for further learning:
