How to use AI to research a new market

AI can help you research a new market faster. It can organise sources, compare local search terms, identify recurring questions and turn scattered evidence into a usable market brief. But AI should not decide where you expand, what product is available in a country or whether a promotion is compliant. Those decisions need current official information, Deriv guidance and local validation. Use AI to create better research questions and faster first drafts. Use real evidence to make the decision.

In this article, Mexico is the running example. A partner wants to understand whether Spanish-speaking people who are new to trading may need beginner education about Deriv MT5 and its demo account. The same workflow can be applied to Sri Lanka, Bulgaria, Cameroon or another market—but conclusions from one market should never be copied directly to another.

Quick summary

• Begin with a decision question, not a generic prompt.
• Use AI research tools to collect, organise and summarise evidence.
• Validate AI findings with search trends, live ads, local community questions and official Deriv information.
• Ask AI to separate evidence, assumptions and unanswered questions.
• Turn the result into a short market brief before creating content or running a campaign.

What AI is good for in market research

AI is most useful when you give it a narrow task and reliable inputs.

It can help you:

• generate local-language search terms;
• summarise official sources and public reports;
• group audience questions into common themes;
• compare how competitors communicate;
• translate the meaning of local comments or reviews;
• identify gaps in existing educational content;
• draft research questions, interview questions and test ideas;
• produce a first version of a market brief.

It is not reliable enough to:

• confirm that a Deriv platform, product or payment method is available in a market;
• interpret regulation without qualified review;
• tell you what local people believe without real local evidence;
• make claims about trading outcomes;
• replace conversations with people in the market.

AI can produce a confident answer that is incomplete, outdated or wrong. Treat every output as a research lead, not a fact. OpenAI also advises users to verify important information and use cited sources where available. Read about ChatGPT’s accuracy and limitations.

Start with a decision question

Do not ask:

“Is Mexico a good market for trading?”

That question is too broad. It encourages a vague answer.

Ask a question that relates to a practical partner decision:

“What questions do Spanish-speaking people in Mexico who are new to trading ask about learning to use a trading platform, and could beginner education about Deriv MT5 and its demo account address any of those questions?”

This gives AI a clear job: identify learning needs. It does not ask AI to decide whether people should trade.

Use an AI research tool with a defined source set

Current AI research tools are becoming more useful because they can work from specified websites and uploaded files, rather than relying only on a general response.

For example, ChatGPT Deep Research can search the public web, use uploaded files and work with selected websites or connected sources to produce a cited report. Read how Deep Research works.

Create a small source pack before asking AI to analyse a market. Include:

• official Deriv product and educational pages;
• current Deriv promotional guidance;
• relevant local regulator or advertising guidance;
• local-language search results;
• reports from credible local or international sources;
• screenshots or links to competitor education content;
• notes from real community conversations.

A source-grounded tool, such as Google NotebookLM, can be useful when you want AI to answer questions only from the documents you provide. It can work with websites, PDFs, copied text, audio and other source types, and can help organise a larger source set. Learn about adding and discovering NotebookLM sources.

Use AI to generate local research terms

The words a partner uses may not match the words a new learner uses.

Ask AI to suggest terms in the local language, then validate them yourself.

Example prompt

You are helping me research beginner trading education in Mexico. Generate 15 Spanish-language search queries that a person new to trading may use when trying to understand a trading platform, a demo account, charts or trading risks. Group the queries into: platform basics, demo-account learning, trading terminology, risk questions and support questions. Do not recommend trades, predict returns or claim that any specific platform is available in Mexico.

Next, test the terms in Google Trends. Compare the terms and related topics, then review regional interest and rising searches. Google Trends measures relative search interest, not total market size, so use it to compare patterns rather than to estimate how many people will become referrals. Learn how Google Trends compares terms and topics and how its data is normalised.

Find the questions behind the search terms

AI is especially useful for clustering questions into themes.

For the Mexico and Deriv MT5 example, you might collect public comments, search suggestions and frequently asked questions, then ask:

Group these questions by the problem the learner is trying to solve. Identify the exact language they use, the terms they appear to misunderstand and the questions that should be answered with official support rather than partner-created content.

The output may reveal themes such as:

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This helps you create education that is useful without stepping into trading advice or account support.

Use AI to review the local content environment

AI can speed up competitor and content research, but it should work from evidence you provide.

Start by collecting examples from:

• local creators and trading-education channels;
• public community discussions;
• search-result pages;
• relevant websites;
• active ads in the market.

Meta’s Ad Library lets you search active ads across Meta technologies by keyword or advertiser. Use it to observe messaging, format and disclosure patterns—not to copy claims or assume an advert is compliant. Explore the Meta Ad Library.

TikTok Creative Center is also useful for understanding current creative patterns. Its Trends tool can show regional popularity, related videos, audience insights and related hashtags. Learn about TikTok Creative Center and its Trends tool.

Then use a prompt such as:

Review the examples I have collected from Mexico. Create a table with: audience question, format used, tone, trust signal, risky claim or compliance concern, and an education gap that a Deriv partner could address responsibly. Do not rank competitors or repeat their promotional claims as facts.

Connect the research to a relevant Deriv product

AI should help you match an audience need to an educational path. It should not tell you which product to push.

In the running example, research may show that new learners want to understand a trading platform before considering real-money trading. A relevant education-first path could be a Deriv MT5 introduction followed by a demo-account walkthrough.

Deriv MT5 demo accounts use virtual funds, allowing users to explore the platform without depositing real money. Partners should still make clear that demo practice does not guarantee the same experience or outcome in real-money trading. Learn about the Deriv MT5 demo account.

Ask AI to help you frame the educational value:

Based only on the source pack, draft three value propositions for Spanish-speaking beginners in Mexico who want to understand Deriv MT5. Each proposition must focus on platform education and demo-account learning. Do not include earnings claims, signals, urgency or personalised advice.

One possible result:

“I create clear Spanish-language guides that help new learners understand the basics of Deriv MT5 and explore a demo account before deciding whether trading is right for them.”

Before using it, check that the wording is accurate, appropriate for the market and aligned with Deriv’s current requirements.

Ask AI to separate facts from assumptions

This is one of the most useful prompts in the workflow.

Create a two-column table. In the first column, list the evidence supported by the supplied sources. In the second, list assumptions that still need local validation. Add a third column called “How to validate”, with a practical next step for each assumption.

For example:

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This step prevents a polished AI report from becoming an untested strategy.

Create a one-page Deriv market brief

After you validate the key points, use AI to organise your research into a brief your team can review.

Include:

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Example first test

For the Mexico and Deriv MT5 example:

Publish one short Spanish-language video explaining what a Deriv MT5 demo account is, what virtual funds mean and where learners can find official support. Ask viewers what they would like explained next.

Measure the quality of the responses. If people ask relevant beginner questions, the test has taught you something. If they mainly ask for signals or guaranteed trades, revisit the proposition and strengthen your boundaries.

Keep a human validation step

Before you create a campaign or invest in a new market, ask someone with real local knowledge to review:

• whether the language sounds natural;
• whether the examples are culturally appropriate;
• whether the audience problem is genuine;
• whether the content could be misunderstood;
• whether the platform information is current;
• whether any local rules or Deriv requirements affect the content.

AI can reduce the time it takes to prepare research. It cannot replace local judgement, responsible promotion or direct evidence from the people you want to serve.

Final checklist

Before using AI research to enter a new market, confirm that you have:

• written a specific decision question;
• used credible and current sources;
• separated evidence from assumptions;
• validated search and content patterns with real tools;
• checked platform availability and product information through official Deriv sources;
• avoided income claims, signals and personalised trading advice;
• tested the content with a small local audience;
• created a clear next step for education or official support.

AI can help you discover where to look. Your job is to verify what you find, understand the local audience and create content that genuinely helps them.