The question everyone is asking about Deep Research is… How does a person get the most out of every search, knowing that the limit is only 10 per month?
With Deep Research being a premium feature available only to paid users—and with a limited number of queries per month—the last thing you want to do is burn through them too fast. If you only get 10 queries per month on Plus, Team, or Edu plans (or 120 on Pro), every single request needs to count.
So, how do you make sure you’re getting maximum value from every Deep Research query instead of wasting them on questions you could answer without Deep Research?
1. Plan Your Research Before You Ask:
Before you even type a query, get super clear on exactly what you need. Think about the end result. Are you looking for trends? Comparisons? Data-backed insights? Do you need a market overview or a deep dive into a niche topic? A scattered approach—just writing random questions—will empty your query allotment fast without giving you the in-depth insights you actually need.
Pro Tip: Instead of asking “What are AI trends in marketing?” ask: “What are the top 3 AI marketing trends in 2025, supported by real-world case studies?” This makes the query focused and ensures a more valuable response.
2. Use One Query to Unlock Multiple Insights
A single Deep Research request shouldn’t just answer one question—it should give you layers of insight that you can use across different areas of your work. For instance, instead of using up three queries like:
- How is AI used in sales?
- What are the best AI tools for sales?
- What industries are adopting AI sales tools fastest?
You could combine them into one query: “Provide a research-backed analysis of how AI is transforming sales in 2025, including the top tools, adoption trends by industry, and measurable impacts on revenue.” Also, try using “How,” “Why,” and “What” in a single request to tackle different angles of a topic at once.
Why It Helps: Well-structured queries unlock deeper, more comprehensive insights in a single go, saving queries for additional follow-ups.
3. Refine Queries Instead of Wasting New Ones
If your Deep Research response isn’t exactly what you need, don’t waste a new query—refine what you have. Instead of running a whole new request, try prompting:
- Expand on the section about AI-driven email marketing.
- Provide real-world examples of the trends mentioned above.
- Summarize this into key takeaways I can present in a meeting.
Why It Helps: It keeps the research focused while enhancing the quality of the information, maximizing the return on each query.
4. Use Regular ChatGPT for Broad Topics, Save Deep Research for Precision
Not every research question needs Deep Research. If you just need a general overview of a topic, use ChatGPT’s standard capabilities first. Use Regular ChatGPT for: Definitions, broad explanations, and summaries. Use Deep Research for: Data-backed insights, industry comparisons, and detailed reports with sources. Think of it like hiring a top-tier research team…you don’t waste their time on basic questions
5. Stay Organized to Avoid Asking the Same Questions Twice
Let’s say you use Deep Research to gather a detailed industry report, but later on, you forget some key details and end up running a similar query again. That’s frustrating, and a bit of a waste. To avoid this, save your best responses in a document as you go along. That way, you can easily refer back to them whenever needed. If you’re not sure how to pull out key points, ask ChatGPT to summarize the report for you into action steps or key insights.
Why It Helps: Staying organized means you won’t waste queries asking for info you already have.
BONUS TIPS: Taking Deep Research Even Further
- Incorporate Industry Experts and Thought Leaders
Try asking: “What do experts say about the role of AI in marketing?” or “How have thought leaders in tech predicted the future of machine learning?” This gives your research more depth and authority. - Use Deep Research for Competitive Analysis
For example: “Compare the top 3 competitors in the SaaS industry for 2025, including their revenue models, target markets, and growth strategies.” This kind of analysis gives you a sharper competitive edge. - Utilize Data-Driven Insights for Decision-Making
Instead of just qualitative analysis, ask for statistical data, charts, and trends. Example: “Provide the latest statistics on consumer spending in 2025 and highlight significant shifts from the previous year.” - Understand the Limitations
Deep Research is powerful, but it’s not always up to date with real-time data. If you need ultra-current stats, supplement your findings with reports from sources like Statista, Gartner, McKinsey, or industry whitepapers.
Stretching Your Deep Research to the Max
Before you hit enter, ask yourself:
- Could I refine this question to get more insights in one go?
- Is this something I could get with regular ChatGPT instead?
- Do I have a clear research goal, or am I just exploring aimlessly?
Deep Research is powerful, but only if used strategically. Follow these steps, and you’ll make sure your queries last the full month instead of running out in a day.
Your Turn: How Will You Use Deep Research?
Are you using Deep Research yet? If not, hopefully, this article will help you structure your Deep Research queries so that you get more out of them. Want more AI insights? Check out OpenAI’s Deep Research FAQ and YourBrandExposed.com for more expert takes!
Scott MacFarland
YourBrandExposed.com
Sources:
- Image generated by OpenAI’s DALL·E
- OpenAI’s Deep Research FAQ
- com
- Ariel Brown Video Commentary
