Discovering hidden gems in the cryptocurrency market can be a daunting task, but with the help of ChatGPT, retailers can now track “Smart Money” movements and identify accumulation or distribution patterns. By feeding technical indicators and on-chain transaction data to ChatGPT, retailers can carry out metrics, mood, and contract security for more well-founded decisions. In this article, we will explore how to use ChatGPT as a research instrument for cryptocurrency analysis.
A coin can have large foundations, but when nobody talks about it, your potential does not remain realized. A hidden jewel is often one that is just beginning to inspire positively. You can make ChatGPT synthesize a picture of public opinion by feeding information from various sources. For example, you can copy and insert current headlines from large crypto messages or snippets from popular social media platforms such as X or Reddit. Try an input request like: “Analyze the following news headings and social media comments on [coin name]. Synthesize the overall market mood, identify all aspiring stories, and mark potential red flags or important concerns that are discussed by the community.”
The AI can use the data that you have provided to create a summary that indicates whether the mood is neutral, optimistic, or negative, as well as what specific discussions receive traction. This method can help you determine the general emotional state of the market. In addition, ChatGPT can be asked to search for growth in the ecosystem of a project. You can send snapshots from platforms such as Defillama, but you cannot provide real-time data. For example, you can use such an input request: “Based on the following data points on the total value for protocols within the [coin name] ecosystem, identify which sectors gain the most dynamics and which protocols grow the fastest in the past 30 days.”
According to MEXC research of 2025, 67% of crypto traders from Gen Z have activated at least one trade bot or strategy operated with AI in the last 90 days, which has a large shift of the generations in the direction of automated trading with AI-supported. For advanced traders, digging up technical and on-chain metrics can result in outstanding options. Here you switch from the researcher to analysts and actively collect the correct data to provide you with the AI for deeper knowledge.
For more technical indicator interpretation, you can feed ChatGPT raw technical data from diagram platforms. For example, you can give him the values of the relative strength index (RSI), the convergence divergence (MACD), and different movable average values for a certain coin over a certain period of time. A useful example of a prompt example could be: “Analyze the following technical indicators for [Coin Name] in the last 90 days. What can you conclude based on the current market trend and the potential upcoming price movements based on the provided RSI, MACD, and 50-/200-day crossovers for the sliding average monitoring? Remove all bullish or bear signals.”
Through on-chain data analysis, you can show the truth behind the activity of a project. You can copy and insert raw data from a block explorer or analytics tool. For example: “Here you will find a list of the latest transactions and item pockets for [Coin Name]. Analyze this data to identify ‘Smart Money’ movements that are large volume transactions of wall pockets that have historically well-executed. Can you recognize based on this accumulation or distribution pattern?” This method can help you track the movements of large players and ideally identify the early signs of a potential leap before they become visible for the rest of the market.
ChatGPT’s real performance comes when you explore GPTs, custom versions of ChatGPT, which are tailored to certain applications. Many GPTs are developed to expand the functions of ChatGPT, e.g., the analysis of intelligent contracts, the summary of blockchain research, or the pull of structured market data. For example, you can use a GPT developed for token security analysis, another for the persecution of on-chain money exchanges, or an optimized for the parsing of crypto research reports.
To create a data-controlled scanner with ChatGPT, you can go beyond one-time input requests by entering ChatGPT an automated detection pipeline. First, create embeds from projects’ white papers, social media posts, and Github commits. Combine these vectors into superficial outliers that are worth human review. Add a TOKENOMICS risk score that weighs the circulating supply, unlock, and cliffs, together with a liquidity depth metric, which was created from snapshots and decentralized Exchange (Dex) Pool of the order book.
Learn more about how to use ChatGPT to find hidden gems in the crypto market at https://cointelegraph.com/news/how-to-use-chatgpt-to-find-hidden-gems-in-the-crypto-market?utm_source=rss_feed&utm_medium=rss_tag_altcoin&utm_campaign=rss_partner_inbound
