February 07, 2017 23:08
Overview
You most likely already have a Profit & Loss (P&L) statement as a part of your financials that you use on a regular basis to help manage your business. Amongst other things, P&Ls allow you to measure the profitability of your business. The P&L dashboard is designed to emulate a financial P&L that you're used to looking at but provides the ability for you to stipulate details that your financial P&L probably does not accommodate (i.e., report on profit/loss by a specific campaign).
The P&L dashboard provides a financial summary of the revenues and expenses incurred during a specific period of time. This dashboard brings together all expense items and profile assumptions input into sticky.io and associates them with the relevant revenues.
In order for the P&L to function properly, there are three areas of that you will enter expense assumptions into, including:
Expense Assumption Profiles. Go to Products | Expenses. From this section of the platform, you will add the desired number of Expense Assumption Profiles to support your Profit & Loss statement.
Gateway Costs. Go to Payments | Gateways | Edit the appropriate gateways | Update the appropriate expenses.
Product Costs. Go to Products | Products | Edit | Edit the "Cost of Goods."
Go to the Expense Assumptions page for complete instructions on how to properly set-up Expense Assumptions.
Potential Actions
Use the Profit & Loss dashboard to:
Drill into the details of your revenue and expenses to make better business decisions. Monitor, analyze and act on revenue, expense, and profit numbers specific to any of the dashboard filters such as product, campaign, vertical, channel, country, etc.
Identify components of marketing efforts that can be optimized to increase profitability.
See patterns for when you typically have lower or higher than average expenses or revenues which can help in many areas of business planning.
Establish your break-even point. This is obviously an essential part of any business. If you have a consistent shortfall resulting in losses, the P&L is going to help you see where expenses need to be trimmed or revenues increased to meet your break-even point. When you know the percentage of loss each period that you’re analyzing, you can decide what aspects of your business to alter.
Identify supplier costs that need to be renegotiated. Historical records of profit and loss show where margins are eroding and empower senior employees and business owners to take action.
Data presented in this dashboard is based on "Acquisition Date" unless otherwise noted. Acquisition Date is the date that the original order was placed and allows Analytics to present data in an appropriately connected way. Specifically, Acquisition Date associates Re-bill and Recurring transactions (Cycles 1…X) to the Initial transaction that initiated the order. When calculating many measures, disassociating the recurring transaction types from the date of origination (the Initial transaction) causes arithmetic inconsistencies and brings incorrect and misleading results - and ultimately incorrect business decisions. As an example: measures that incorporate time-phasing and transaction type correlation into the calculation: think Re-Bill rate or Chargeback Rate; they both associate a transaction event to other components of the overall order within a timeframe. That being said, there are instances where you may want to simply see the count, or value, or count by transaction type, of transactions within a period. When this type of analysis is performed it will be noted as such.
All orders marked "test" within the platform are automatically removed from the Analytics data.
Please reference the sticky.io Order Cycle Nomenclature visual below to understand the way that sticky.io references the phases of each order type.
Data Elements & Measures
The following data elements and measures are shown on the Profit & Loss dashboard. For comprehensive definitions of data elements and measures, please reference the
Additional Resources
You may find the following Help Center articles relevant to Analytics helpful.