Average Transaction Fee Savings
Before accepting a transaction, an user can check in their wallet an estimation of the maximum amount that would be charged as total transaction fee. This is an estimation calculated based on transaction demand at that time. Usually users end up paying less. This metric shows the rest between the expected amount to be paid and the final amount that is paid. Each day an average of this fee is calculated by averaging the total fee saved per transaction in all the transactions that occurred in that single day.
This indicator is essentially a measure of how accurate the fee estimation is and how much users are saving relative to their initial fee estimates. Here's how this indicator can be useful:
This indicator can help users understand how much they're saving on average on their transactions compared to the estimated fees. This can be particularly valuable for frequent users of the Ethereum network or DApp developers who need to manage their operating costs effectively.
Significant differences between the estimated and actual transaction fees may suggest variations in network congestion and demand for block space. If the actual fees are consistently lower than the estimated ones, it could indicate that the network is less congested than expected.
The indicator can also provide insights into how accurate the fee estimations provided by Ethereum wallets are. If the actual fees are regularly much lower than the estimated ones, it might indicate that the estimations are too conservative or that the fee estimation algorithms could be improved.
For regular users of the network, this metric could be used to strategically plan transactions. If the 'savings' metric tends to be high at certain times of the day or week, users might choose to schedule their transactions during these periods to save on fees.
Lastly, if there's a consistent pattern of high 'savings', it could indicate a bearish market or decreased transaction demand. Conversely, lower 'savings' might suggest a bullish market or increased transaction demand, as more congestion may lead to users paying closer to their maximum fee estimates to ensure their transactions are processed.