Parker Analytics Glossary | Parker Help Center

Parker Analytics is currently in Beta

Parker seamlessly integrates a wide range of data sources. When you connect a new data source, the newest data will typically take 24 hours to reflect in Parker Analytics.

If you would like to unlock access to the latest Analytics feature set, please reach out to [email protected]

Profit & Loss Module

Data Sources
1. Store API data for Gross Sales, Refunds, Discounts, Net Sales, and Store Fees from your sales channel connections in Parker. Be default, Parker analytics reports in UTC timezone for all sales level data.
  1. Amazon: We are limited to 2 years of order data from the date you connect your sales channels to Parker.
  2. Shopify: We are limited to 5 years of order data from the date you connect your sales channels to Parker.
2. COGS can come from either Store API or user inputted COGS into Parker dashboard
3. Ads spend data comes from connected APIs for supported networks: Facebook, Google, and Amazon Ads (accounts must be connected by users). Ad spend data is in the timezone of the advertising account.
  1. Amazon Ads limits us to 3 months of historical data from the date you connect your Amazon Ads Account. Google & Facebook ads go back all time.
4. Shipping & Fulfillment Costs: Parker currently supports estimators for Shipping & Fulfillment expenses.
  1. Customers have 2 options to input their estimated Shipping Costs
    % of Gross Sales: A fixed % based off the gross sale amount of every order.
    Fixed $ Amount per Order: A fixed $ amount per order.
  2. For Amazon FBA accounts, we automatically extract FBA Fulfillment fees per order. Thus, the estimator does not need to be used for such accounts.
Glossary
1. Gross Sales: Total revenue from all sales before any deductions (excluding shipping and taxes). Gross Sales = Total Amount Charged + Discounts - Shipping - Taxes.
2. Discounts: Discounts applied to orders in Dollar Amount.
3. Refunds: Refunds issued to Customers in Dollar Amount.
4. Net Sales: Gross Sales - Discounts - Refunds. This data comes from the store connections directly.
5. COGS: Your costs for the items sold in a given period. The data source for COGS can vary:
  1. If you input COGS per item in Shopify, COGS are automatically ingested
  2. For items missing COGS, you can also input them per SKU in the Parker Inventory Module
  3. As a fallback, you can also use the COGS estimator as % of the Sales Price (this method may lead to inaccuracies in your profitability calculations).
6. Store Fees
  1. Shopify: Includes payment processor fees associated to an order.
    If your store does NOT use the Shopify Payment processor, fees will appear as $0 in the P&L module.
  2. Amazon: Includes all fees associated with servicing an order including the Amazon referral/commission fee
    FBA Fulfillment fees are NOT included as Store Fees, instead, they are treated as Shipping & Fulfillment costs.
7. Ad Spend
  1. Pulled from your Ad account connections with Parker
    We currently support Facebook Ads, Google Ads, and Amazon Ads.
    Amazon Ads limits us to 3 months of historical data from connection time. Google & Facebook ads go back all time.
8. Shipping & Fulfillment
  1. The total shipping costs based on either % of Sales, Fixed $ per Order, or your FBA Fulfillment fees.
9. Contribution Profit: Net Sales - COGS - Fees - Ad Spend - Shipping & Fulfillment
  1. Contribution profit is a key financial metric that helps you understand the profitability of your business before considering fixed costs. It is calculated by taking your net sales and subtracting the cost of goods sold (COGS), fees, advertising expenses, and shipping costs. Keeping an eye on contribution profit helps ensure that your business is sustainable. If your contribution profit is positive, it means your business is generating enough to cover variable costs, and potentially contribute to fixed costs and profit.
10. Contribution Margin: (Net Sales - COGS - Fees - Ad Spend - Shipping Costs) / Net Sales
11. MER Ratio: Net Sales / Ad Spend
  1. This metric measures the efficiency of marketing campaigns by comparing net sales to total ad spend over a specific time period. Ad spend comes through your Ad Account connections to Parker

Customers Module

Data Sources
1. New Customer counts & LTV data is powered by order level data from your store connections. Parker receives anonymous customer IDs from both Shopify and Amazon that represent an individual customer which enables us to track their Lifetime value over time. Be default, Parker analytics reports in UTC timezone for LTV level data.
  1. Amazon: As we are limited to 2 years of order data from the date you connect your sales channels to Parker, new customer counts may be higher than actuals if your channel is older than 2 years old.
  2. Shopify: As we are limited to 5 years of order data from the date you connect your sales channels to Parker, new customer counts may be higher than actuals if your channel is older than 5 years old.
2. CAC is powered by both Order Level Data for new customer counts and ad spend data which is from connected Ad Accounts to Parker. Ad Spend only includes data from connected Ad Accounts to Parker (i.e. Facebook, Amazon, and Google Ads). Ensure you have all relevant accounts connected for accurate CAC values. Ad spend data is in the timezone of the advertising account.
  1. Amazon Ads limits us to 3 months of historical data from connection time, thus your CAC values may be lower than actuals for older months.
Glossary
1. Cohort: We count a customer as new when they make their first transaction with you and each new customer is assigned to their Cohort (by first purchase month).
2. New Customer: Counted as when your customer makes their first purchase with you.
3. Returning Customer: Counted when your customer comes back to make another purchase.
4. Lifetime Value (LTV): Represents the Lifetime Value of a customer in revenue. It is measured by taking the sum of all revenue from every customer over a given duration divided by total new customers in a cohort. For example, if a customer makes their first purchase with you on Oct 1, 2023 for a total of $10 and then goes on to make a 2nd purchase on Nov 5, 2023 for $20, the 30 Day LTV would be $10, while the 60 Day LTV would be $30 (as the second purchase occurred after 30 days and before 60 days). Revenue = Total Amount charged to the customer including shipping and taxes (refunds are deducted from LTV Revenue)
5. Customer Acquisition Cost (CAC): the Cost to acquire a new customer. We calculate CAC by Dividing Total Ad Spend by your New Customers from a given month. To be conservative, Parker assumes a front-loaded blended CAC because the value does not account for any spend for activating past buyers.
6. LTV/CAC: Avg Revenue per Customer for the Selected Duration divided by the CAC for a cohort. Simply put, the LTV/CAC ratio compares the value of a customers over their lifetime to the cost of acquiring them. Higher is Better. For example, if your 30 Day LTV / CAC is 1.2, that means that by day 30, your customers spent 20% more than it cost you to acquire those customers. If your ratio is below 1, then that means it cost you more to acquire that customer than the revenue generated by the same customer by their 30th day after converting.
7. New Customer Revenue: Revenue from a customer’s first order (includes shipping and taxes)
8. Returning Customer Revenue: Revenue from returning customers (includes shipping and taxes)
9. Repeat Rate: The % of new customers from a given month that go on to make a repeat purchase by a certain day. For example, if the 30 day repeat rate for a single cohort is 25%, that means 25% of your new customers from that month have gone to make another order by their 30th day.
  1. Some metrics may be missing if a cohort did not have enough time for a given duration. For example, If today is Sep 1, 2024, both Aug 2024 & Sep 2024 cohorts will show no metrics since they did not have enough time to get a fair read on their repeat rate.

Finance Module

Data Sources
1. Powered by bank transaction data from your connected Bank Accounts including Parker depository accounts. Only depository account transactions are included in this view (Credit Card account transactions are not included here). Transactions are reported as UTC timezone.
  1. Depending on the Bank and Connector, there may be limitations in the amount of transactions Parker can ingest, such as limiting us to only 3 months worth of transactions.
Glossary
1. Cash Inflow: Total Credits coming into your connected depository accounts, including Parker Depository accounts
2. Cash Outflow: Total debits leaving your connected depository accounts, including Parker Depository accounts.
3. Net Cashflow: Total Credits - Total Debits for a given time period.
4. Cash Flow Chart: This is to show you your cash inflow and totals by category
  1. Parker Automatically tags your cash based transactions to assign categories for each.
5. Cash Forecasting Chart: This is to project your cash balance into the future (For Credit Customers only)
  1. Daily Cash Balance in Customer Linked Bank Accounts
  2. Payouts from Shopify: Via Store API data of when incoming payouts will hit a customers bank account
  3. Parker Bills: Expected future payments to Parker based on due dates
  4. Data Sources:
    Powered by your Connected Bank Accounts
    Shopify API data for upcoming payouts
    Upcoming Parker bills
6. Card Spend: A Chart the shows your Parker card spend by category
7. Upcoming Payments: A Chart that shows a customer’s upcoming payments owed to Parker

Product Sales & Profitability Module

Data Sources
1. Store API data for Gross Sales, Refunds, Discounts & Net Sales. This data is reported in UTC timezone.
2. COGS: The data source for COGS can vary:
  1. If you input COGS per item in Shopify, COGS are automatically ingested.
  2. For Amazon items or other items missing COGS, you can input them per SKU in the Parker Inventory Module (either individually or CSV upload).
  3. As a fallback, you can use the COGS estimator as a percentage of the sales price (this method may lead to inaccuracies in your profitability calculations).
Glossary
1. Gross Sales: Original product price multiplied by quantity sold.
2. Units Sold: Total units sold per Item
3. Discounts: Price reductions issued per item.
4. Refunds: Amount refunded for a returned item.
5. COGS/Unit: Cost of goods sold per item in a given period.
6. Gross Profit % : (Net Sales - COGS of a SKU) / Gross Sales. We use gross sales as the denominator to highlight items that may have high discounts and refunds.