First, I used the AVG_PRICE_ETH and MAX_PRICE_ETH columns to provide insights into the valuation of the top 10 tokens. So we can assess the average and maximum prices, helping in understanding the range and potential value of these tokens. Second, I checked that the COUNT_SALES column to indicate the trading frequency of each token, found that higher counts may suggest strong market demand and popularity, influencing our decisions on the liquidity and attractiveness of the tokens. Next, I utilized the factor of the TOTAL_SALES_VALUE_ETH gives a cumulative value of sales for each token, reflecting the economic impact of these tokens within the 'MAYC' project. So we can use this information to assess the overall market health and potential returns. Then, I used the AVG_PRICE_USD to provide an average token price in USD, allowing for a global perspective for our analysis. This enables comparisons with other NFT projects and aids in understanding the project's international appeal. Finally, I used the Variability in AVG_PRICE_ETH and TOTAL_SALES_VALUE_ETH across the top 10 tokens to indicate diversity in token performance. By the way, I found that MAYC #376, MAYC #5441, and MAYC #389 are the top 3 most valuable NFT in the whole MAYC NFT collection.

I used queries to describe the hourly sales count for 'MAYC', in order to gain deeper insights into user behavior during peak hours, to monitor whether peak hours remain consistent over time or if there are shifts in user behavior, then to keep track of the long-term trends can inform sustained marketing and engagement strategies. Here's what I found: the Hours 14 (2:00 PM) and 23 (11:00 PM) exhibit exceptionally high sales counts, surpassing the overall average sales count. These hours can be considered as peak hours of activity, indicating increased engagement and transaction volume. In the meanwhile, the sales distribution is relatively consistent throughout the day, with varying levels of activity. This consistency suggests that the 'MAYC' project maintains a steady flow of transactions, potentially catering to a global audience across different time zones. Then, I checked the late hours transactions, found that the Hours 22 (10:00 PM) and 23 (11:00 PM) show significant sales counts, suggesting that late evening and night hours might be opportune for engagement and marketing efforts. Next, the Daytime hours, particularly 14 (2:00 PM), also exhibit high sales counts, indicating strong engagement during this period. The 'MAYC' project appears to have global reach and user engagement throughout the day. Consider exploring ways to cater to the needs and preferences of users across different time zones. In a word, I think we should use the insights to optimize resource allocation, ensuring that marketing efforts and community engagement activities align with the hours of peak activity.

Firstly, I used the [TO_CHAR(m.CREATED_AT_TIMESTAMP, '%Y-%m')] to calculate the month, in order to find the historical_total_revenue trends of MAYC project based on month. Hence, the result is: there is a noticeable increase in Total Revenue from Month 1 to Month 6, reaching a peak in Month 6 (June). From Month 6 onwards, there's some fluctuation in Total Revenue, with notable peaks in Month 11 (November) and Month 16 (January of the following year). Months 18 (March of the following year) and 20 (May of the following year) show a decrease in Total Revenue. Next, if we want to find the high performance months, the Month 6 (June) has the highest Total Revenue, indicating a particularly successful period for the business. Andf the Month 11 (November) also stands out as a high-performing month with a substantial increase in Total Revenue.In the meantime, as we value the low performance of months, the Months 18 (March) and 20 (May) show lower Total Revenue compared to the surrounding months. Investigating the reasons behind these decreases could provide valuable insights. In additional, the Month 10 (October) to Month 13 (January of the following year) shows a continuous increase in Total Revenue, suggesting a potentially successful holiday season. The Month 14 (February) and Month 15 (March) show a significant decrease in Total Revenue compared to the previous months, which could be a result of seasonality or specific business factors. In a word, we can investigate the factors contributing to the success of high-performing months, especially in Month 6 (June) and Month 11 (November). To eplore the reasons behind the decrease in Total Revenue in Months 18 (March) and 20 (May) to identify potential areas for improvement. Also, we should consider seasonality and external factors that may impact Total Revenue, especially during low-performing months.

Secondly, I used queries to value the historical Highest Price of MAYC, and found that there is considerable variation in the Highest Sale Price across the months. The Month 6 (June) has the highest Highest Sale Price, indicating a significant spike in premium sales during that period. There are notable peaks in Month 2 (November of the previous year) and Month 13 (October of the following year), suggesting other periods of high-priced items. Besides, the Month 6 (June) stands out with a remarkably high Highest Sale Price, suggesting the presence of high-value or premium products during that period. And the Month 2 (November of the previous year) and Month 13 (October of the following year) also show spikes, indicating potential seasonal or promotional influences. Next, Months 18 (March) and 20 (May) have the lowest Highest Sale Price. Investigating the products or strategies during these months could provide insights into lower-priced items or potential sales challenges. In conclusion, we need to explore the factors contributing to the exceptionally high Highest Sale Price in Month 6 (June) to understand the success and potentially replicate it in other periods. And we also need to investigate the reasons behind the spikes in Month 2 (November) and Month 13 (October) to identify successful sales strategies during those periods. Besides, we also need to analyze the product mix and marketing strategies during Months 18 (March) and 20 (May) to understand the lower Highest Sale Price and identify areas for improvement.

Thirdly, we can also evaluate the trends of Monly Sales of MAYC, and found that there is variation in Monthly Sales over the months, with some months experiencing high sales counts. The highest sales count is in Month 6 (June), followed by Month 11 (November) and Month 13 (January of the following year). Then, the Month 6 (June) stands out with the highest sales count, suggesting a particularly successful period for the MAYC project. The Month 11 (November) also shows a high sales count, indicating potential success during the holiday season. The Month 13 (January) has a considerable sales count, potentially reflecting post-holiday shopping. In the meanwhile, the Months 18 (March) and 20 (May) have relatively low sales counts. Investigating the reasons behind these decreases could provide insights into potential challenges or factors affecting sales. In the end, the Month 10 (October) to Month 13 (January of the following year) shows a continuous increase in Monthly Sales, suggesting a potentially successful holiday season. The Month 14 (February) and Month 15 (March) show a decrease in Monthly Sales compared to the previous months, which could be a result of seasonality or specific business factors.

For here we can see, there is a range of Creator Fees, with the highest fee being 200,050 ETH and the lowest being 10,156 ETH. Such a range indicates diversity among the fees charged by different creators.By the way, the creators with the highest fees (e.g., Token_Name 1 with 200,050 ETH) are likely top performers or have high-demand content/products associated with the MACY project. Also, the distribution of Creator Fees provides insights into how rewards are allocated among the top creators. Creators with higher fees may have a significant impact on the success and visibility of the MACY project.

From the results we can see that, November 18, 2023, and November 9, 2023, have notably high transaction counts on the 'blur' platform. The 'blur' platform consistently appears with high transaction counts, indicating it is a major player in the MAYC project ecosystem. In the meantime, the 'opensea' also has varying transaction counts, suggesting transactions are distributed across multiple platforms. Beside, the number of active buyers' wallets provides an indication of user engagement. The 'blur' consistently has a higher number of active buyers' wallets compared to other platforms, reflecting a larger user base or higher engagement. From the perspective of the USD Volume, the 'blur' consistently has high USD volumes, indicating significant value and economic activity within the platform. Then, November 18, 2023, stands out with a high transaction count on the 'blur' platform. In a word, we need to understanding the specific features or events associated with each platform and date can enhance the interpretation of the data. External factors, such as market trends or platform-specific changes, should be considered for a more comprehensive analysis.