Finding relevant and reliable information on the Internet is a constant challenge. Between the multitude of sources, the sorting of results and the risk of misinformation, the search for information takes time and requires increased expertise.
This is where it comes in Deep Search, the new feature in ChatGPT. Unlike traditional search engines that list links, Deep Search goes further: it collects, analyzes and synthesizes information from the web to provide a structured and sourced document. A promising advance for professionals, but also a solution that poses certain limitations. We tested Deep Search to understand how it works and assess its effectiveness.
We submitted a demanding request to Deep Search: “What is the macroeconomic analysis of the retail sector in France in 2024?”
✅ A structured document with 38 sources : Far from a simple summary, Deep Search compiles information and references to offer detailed and contextualized analysis.
⏳ Standby time: 11 minutes : Unlike a traditional Google search, which provides results in a fraction of a second, Deep Search requires time to analyze and return quality information.
⚠ A limited number of uses : OpenAI imposes restrictions on the use of Deep Search, which requires you to choose your searches carefully to maximize their impact.
Deep Search doesn't just index and categorize web pages. It acts like a information analyst, transforming a mass of raw data into a usable report. Here's how it differs from traditional search engines:
🔹 Summary and analysis of sources : Google offers thousands of links; Deep Search extracts key information from them and organizes it in a coherent way.
🔹 Reliability and contextualization : By providing accurate references, Deep Search limits the risk of coming across erroneous or misleading information.
🔹 Significant time savings : For complex searches, Deep Search avoids browsing a multitude of sites to extract relevant data.
However, Google remains faster and more accessible, especially for simple searches or immediate news needs.
Deep Search does not replace a conversational chatbot or a traditional search engine, but it can be a strategic asset for:
✔ Get an overview of a complex subject : Ideal for analysts, journalists, and researchers. ✔ Enrich specialized AI models : Deep Search can feed a GPT with verified and contextualized data. ✔ Accelerate analysis work : For professionals who need to produce in-depth reports without spending hours researching literature.
🔹 Refine your prompt before sending the request : Testing the question first on ChatGPT-4O helps to avoid results that are too generic or not very usable.
🔹 Set a clear objective : A precise query generates more relevant and directly actionable results.
🔹 Integrate it into an AI workflow : Deep Search perfectly complements a structured analysis process by automating the documentary search phase.
Despite its advantages, Deep Search has several constraints:
❌ Long response time : Not suitable for instant searches.
❌ Cost and restrictions of use : The tool is still limited in access and can be expensive for intensive use.
❌ Dependence on accessible sources : If information is not indexed or protected by a paywall, Deep Search will not be able to fully exploit it.
Deep Search marks a significant advance in AI-assisted search. By providing documented analyses rather than a simple list of results, it allows save time and improve the quality of in-depth research. However, it does not replace Google for fast and up-to-date searches. Its use is therefore reserved for professionals who need reliable, organized and directly usable data.
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