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What’s my LTV, and how is it trending by channel?
Drivepoint automatically creates multiple kinds of LTV metrics. 1. Navigate to [Reports](https://app.drivepoint.io/) 2. Click on "DTC" or "Amazon Cohort Analysis" 3. Open the first report (Cohorted Financials) 4. Toggle between Gross/Net Sales LTV and Contribution Profit LTV after Marketing If you have questions about how certain metrics are calculated. Click on the 💡 in the report that will link to our [documentation](https://docs.drivepoint.io/help/using-the-web-app/reports/cohort-analysis).Where can I see if we're actually profitable by cohort?
1. Open the Cohorted Financials report (see one question above of how to navigate there) 2. Toggle the metric to "Contribution Profit Less Blended CAC" *In order to get to change the metric. Click the Customize button on the top right of the report.*
How do I quickly understand what’s driving our EBITDA?
If you have a full Financial Model built out in Drivepoint, navigate to Variance Reviews and then the P\&L Variance Report to understand line by line where you missed. If you are not fully set up as a customer in Drivepoint, a good place to start is the P\&L Benchmarks report to see how your drivers performance compare to your peers. 1. Click on [Reports](https://app.drivepoint.io/) 2. Click on "Benchmarks" 3. Click on P\&L "Benchmarks" 4. Hover over the table to view your score compared to the quartiles and medianCan you show me a few scenarios if we increase spend or expand wholesale?
Creating scenarios is easy in [Drivepoint](https://app.drivepoint.io/): 1. Click on "Plans" 2. Click on "Quick Edit" on the top right of your live model 3. Select a wholesale driver in the drop-down 4. Change the driver by editing the values in the table directly or set it to a specific value via the drop-down 5. Click on "Preview" 6. View the impact of a specific wholesale driver change 7. Save as new plan to your Drivepoint "Plans" interface [Here's](https://docs.drivepoint.io/help/using-the-web-app/quick-edit) a full video walk-through of how to scenario plan in Drivepoint.How can I compare different growth strategies?
Similar to adjusting wholesale drivers (see question above), you can change certain growth strategies with Quick Edit: * Increase Ad Spend by specific channels * Decrease CAC * Increase Wholesale door count * Change product prices All you need to do is quickly edit these drivers and save as new plans. Then you can select them in the plans page and click on "Visualize" to view the impact of all of the scenarios visually.
How do I see performance vs. plan?
You're able to view performance vs. plan multiple different ways\*: **Mid-Month Pacing Summary** down to [Net Income](https://docs.drivepoint.io/help/using-the-web-app/reports/performance-vs.-plan/performance-vs.-plan): 1. Open [Drivepoint](https://app.drivepoint.io/) 2. Click on Variance Review 3. Click on "Performance vs. Plan" 4. Select your Plan 5. Select your Channel **Post Month End Accounting Close Variance reports** 1. Open [Drivepoint](https://app.drivepoint.io/) 2. Click on Variance Review 3. Click on P\&L, Balance Sheet or Cash Flow Variance report 4. Select a Plan 5. Change the month and breakdown 6. Export and send to investors **Post Month End Accounting Close Variance views in the model** 1. Navigate to the Plans page 2. Open your model (or any Drivepoint plan) 3. Navigate to the blue "Variance Summary" tab 4. Toggle between different tabs to view your performance vs. plan *\*all Performance vs. Plan features require at least one saved plan in Drivepoint*Where do I check assumptions behind the forecast?
The best way is to do this in the Drivepoint model. We're happy to give you a full demo and run-down of how we're building towards your Sales assumptions by channel or your demand plan.How do I model changes to CAC, Ad Spend, etc.?
Making changes is easy in [Drivepoint](https://app.drivepoint.io/): 1. Click on "Plans" 2. Click on "Quick Edit" on the top right of your live model 3. Select any driver (e.g. Blended Paid CAC or Ad Spend Channel) in the drop-down 4. Change the driver by editing the values in the table directly or set it to a specific value via the drop-down 5. Click on "Preview" 6. View the impact of a specific wholesale driver change 7. Save as new plan to your Drivepoint "Plans" interface [Here's](https://docs.drivepoint.io/help/using-the-web-app/quick-edit) a full video walk-through of how to scenario plan in Drivepoint. Of course, you're also able to do this in any Drivepoint plan as soon as you're a customer of Drivepoint.Can I export this into my board report?
Yes. As a Drivepoint customer, you get a monthly board report dashboard which contains core reports that might be relevant for your board report (e.g. P\&L Variance, Financial Margins, etc). A dashboard is a collection of reports and you can build your own. If you just want a single report export, you can export any by clicking on the ⬇️ on the top right.Where’s the cash flow tracker?
We offer a cash flow forecast as additional product module. Talk to your Drivepoint rep to learn more and see it in action.Do we have visibility into expected POs vs. received?
Yes. Drivepoint integrates natively with Cin7 Omni + Core. We have out of the box Sales reports to understand expected vs. received POs as well as Gross Sales by retailer. You can also import PO-level information by product and account into any Drivepoint Plan. Talk to us if you want to see Cin7 as part of your Quickstart.Where can I see inventory burn vs. sales pace?
You can see it in the demand planning report module. Drivepoint integrates with 70+ WMS and 3PLs that allow us to create inventory burn and velocity reports on a Warehouse level. This module is only available for Pro customers.How do I track performance vs. plan at a SKU level?
If you use Drivepoint for Demand Planning, open the SKU Summary tab in the model, select a plan and view your performance by SKU. We're happy to send you a 5 min Loom of the SKU-level variance review.Where’s the LTV by marketing channel?
1. Open Drivepoint 2. Open the LTV by Dimension Report 3. In the filter on the bottom right, search for a source site or discount code to filter for LTV performance by Marketing *The LTV by Dimension Report is complex in the way it calculates the maturity of cohorts. Read more in our documentation* [*here*](https://docs.drivepoint.io/help/using-the-web-app/reports/cohort-analysis/ltv-retention-by-dimension)*.*How do I see CAC vs. LTV in one place?
Drivepoint offers multiple LTV metrics. Our most popular is the Cohorted Financials Report that marries financial and operational data to get to a Contribution Profit LTV After Marketing. 1. Open [Drivepoint](https://app.drivepoint.io/) 2. Click on Reports 3. Click on "DTC/Amazon Cohort & LTV Analysis" 4. Open the first report 5. Toggle between CAC and LTV metrics Another interesting view is our **LTV Benchmarks report where you can compare all of your LTV and CAC performance** to peers. 1. Open [Drivepoint](https://app.drivepoint.io/) 2. Click on Reports 3. Click on "Benchmarks" 4. Click on "LTV Benchmarks" 5. Hover over each metric to see your performanceWhat’s our average payback period?
1. Open [Drivepoint](https://app.drivepoint.io/) 2. Click on Reports 3. Click on "DTC/Amazon/TikTok Shop Cohort & LTV Performance" 4. Click on the N-Day LTV report 5. Change your metric to "Contribution Profit Less Fully Loaded CAC"
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I can't seem to be connecting through the UI. Is there another way?
Yes! There's a manual way to connect Drivepoint to AmazonSP. You can invite our emailWhy do some Amazon Seller Central Stores not connect to Drivepoint?
* We tried to pull historical data but unfortunately our data pulls failed because we do not have permissions to the "restricted orders" * The restricted orders are not necessarily relevant but we currently do not have a way to exclude them in our datapulls * Hence, the whole things fails because we lack the permission to one of the table There are some providers that offer to pull the data (through some weird loophole that Amazon seems to be unaware of or weirdly allow). If you are curious to learn more emailHow does Drivepoint identify customers without buyer email?
As of early 2026, Amazon replaced all buyer email addresses in SP-API fulfilled shipment reports with anonymous proxy addresses (`@marketplace.amazon.com`). This is a permanent change that affects all platforms relying on Amazon order data, not just Drivepoint. Drivepoint identifies returning customers using shipping address, phone number, and order history patterns. This approach produces high assignment rates (the vast majority of orders get a customer identity), but it is a completeness metric, not an accuracy guarantee. Edge cases like gift orders, address changes, and shared households are harder to resolve without email as a cross-check. For sellers enrolled in **Amazon Brand Registry**, Brand Analytics Repeat Purchase data provides an independent accuracy calibration that Drivepoint can use to validate the matching.What happened to new vs. returning customer data on Amazon?
In early 2026, Amazon replaced all buyer email addresses in their Selling Partner API fulfilled shipment reports with anonymous proxy addresses (`@marketplace.amazon.com`). This is a permanent change that removed email as a customer identity signal for all platforms that rely on Amazon order data, not just Drivepoint. Previously, buyer email was one of the signals Drivepoint used to link orders to the same customer. With that signal removed, Drivepoint now relies on shipping address, phone number, and order history patterns to identify returning customers.Was my data affected?
If you have an Amazon sales channel connected to Drivepoint, the transition period (approximately February through March 2026) may have had temporarily degraded accuracy while the new matching approach was rolled out. Since then, the address-based matching pipeline has been fully deployed across all accounts.How does matching work now?
Drivepoint matches Amazon orders to customers using shipping address, phone number, and order history patterns. This produces high assignment rates: the vast majority of Amazon orders receive a customer identity. It is important to understand what this means. **Completeness** (what percentage of orders get assigned a customer identity) is high. **Accuracy** (whether each assignment is correct) is harder to measure directly because Amazon does not provide a ground-truth customer ID. Edge cases like gift orders, address changes, and shared households can cause a single real customer to appear as multiple customers, or vice versa. For sellers enrolled in **Amazon Brand Registry**, Brand Analytics Repeat Purchase data can serve as an independent check on the accuracy of new vs. returning segmentation.What is Brand Analytics and how does it help?
Amazon Brand Analytics is available to sellers enrolled in Amazon Brand Registry. It includes a Repeat Purchase report that shows, at the ASIN level, how many orders came from new vs. returning customers, based on Amazon's own internal customer identity. Drivepoint can use this data as a calibration layer to validate and improve the accuracy of our address-based customer matching. If you are enrolled in Brand Registry, reach out to your Drivepoint contact to discuss enabling this.What if I notice something off in my historical data?
Reach out to your Drivepoint contact and we'll review it with you. Most accounts will see no material difference, but a small number of customers experienced shifts of a few percentage points during the transition.
Email Method (Recommended)
1. **Step 1 - Find your dedicated Drivepoint x Netsuite email address** Your NetSuite email address is automatically generated when you add a NetSuite data source in the Drivepoint web app. Navigate to **Sources > Add Source > NetSuite** and you will see your dedicated email address displayed on the configuration page. The format is: `netsuite+{your-company-id}@drivepoint.io` No setup or provisioning is needed. The address is ready to receive reports as soon as you see it in the app. > **Existing customers:** If you were set up before August 2026, your email may use the legacy format `{companyId}-netsuite@bainbridgegrowth.com`. Both formats continue to work. You do not need to change your scheduled reports. 2. **Step 2 - Create Drivepoint as a Vendor in Netsuite** To create a vendor record in Netsuite: 1. Go to Lists 2. Click Relationships 3. Click Vendors 4. Click New 5. Enter the email from Step 1 above and any required fields. 6. Click Save. Netsuite article on adding vendor:FTP Method
1. You'll need to create a destination on your FTP server where reports will be uploaded from Netsuite. Make sure uploaded report files have proper name and format and are replaced with a fresh ones at the desired frequency: 1. Income Statement report file should be in CSV format named `income_statement` 2. Balance Sheet report file should be in CSV format named `balance_sheet` 2. Provide us with the following data to access FTP for those reports: 1. FTP host 2. FTP port 3. username 4. password 5. directory path on FTP with reportsDirect Delivery via Upload to Cloud Storage Bucket
1. We will create `netsuite_reports` bucket in your Cloud Storage storage and prepare service account JSON access key that will have access only to that bucket. 2. You can then use provided key to connect your service to `netsuite_reports` bucket. 3. You can then set up Netsuite reports upload, make sure uploaded report files have proper name and format and are replaced with a fresh ones at the desired frequency: 1. Income Statement report file should be in CSV format named `income_statement` 2. Balance Sheet report file should be in CSV format named `balance_sheet`Step-by-step Balance Sheet Setup Guide
The balance sheet should look like [this](https://docs.google.com/spreadsheets/d/1kHBuef22-2tyReRTDsUgAJhh7D6BhVEGfZa5tIggyvc/edit#gid=0) sample Balance Sheet. Feel free to keep it open while you are going through the setup guide to compare. 1. Open Netsuite in your browser 2. Click on "Reports" field in the top navigation bar 3. Select "New Financial Report" 4. Select "Balance Sheet" in the view list of all reports 5. Name "Drivepoint Balance Sheet" 6. Click on "Edit Columns" in the header next to "Edit Layout" 7. Select "Accounting Period" in "View by Columns Field" 8. Click on "Preview" to see the balance sheet 9. Navigate to the footer of the balance sheet preview to set the periods 10. "End Of": should say "Custom" 11. "As of": set to earliest month of financial records 12. "Column": should say "Accounting period" 13. Click "Save" in the Financial Report Builder 14. Navigate to the right footer of the balance sheet 15. Click on the "Calendar icon" 16. Select the date of tomorrow as the first day of sending it 17. Select a time at night (2-5am) to send the report to the Drivepoint team 18. Click on the check box: "Run report more than once" 19. Select "Daily Event"; Repeat every "1" day (NO end date) 20. Select Drivepoint as the vendor for the CSV send 21. Click on "Message" in the blue navigation bar next to "Recipients" 22. Type in "balance\_sheet" in the message text box 23. Select "CSV" from drop-down menu below the message text box 24. Hit save 25. Double check the scheduled report is showing up by navigating to "Reports" > "Scheduled Reports" 26. You set up the balance sheet report! Move to the income statement.Step-by-step Income Statement Setup Guide
Most clients have additional dimensions segmenting the financial rows from the account periods. [Here](https://docs.google.com/spreadsheets/d/1zwfo4fTYrCK8HJ-tzMU96pu_Hx_B8P7IbVcfGOB94Xk/edit#gid=0) is a template of how the income statement with classes should look like. 1. Open Netsuite in your browser 2. Click on "Reports" field in the top navigation bar 3. Select "New Financial Report" 4. Select "Income Statement" in the view list of all reports 5. Name "Drivepoint Income Statement" 6. Click on "Edit Columns" in the header next to "Edit Layout" 7. Select "Accounting Period" in "View by Columns Field" 8. Search for your desired dimension in the search box on the left 9. Drag the class you selected into the table on the right 10. Move left or right to place them in between the financial rows and accounting period 11. Click on "Preview" to see the income statement 12. Double check that you have selected the correct classes 13. Navigate to the footer in the income statement preview to set the periods 14. "End Of": should say "Custom" 15. "As of": set to earliest month of financial records 16. "Column": should say "Accounting period" 17. Click "Refresh" and see any potential updates 18. Click "Save" in the Financial Report Builder to save the "Drivepoint Income Statement" 19. Navigate to the right footer of the income statement 20. Click on the "Calendar icon" 21. Select the date of tomorrow as the first day of sending it 22. Select a time at night (2-5am) to send the report to the Drivepoint team 23. Click on the check box: "Run report more than once" 24. Select "Daily Event"; Repeat every "1" day (NO end date) 25. Select Drivepoint as the vendor for the CSV send 26. Click on "Message" in the blue navigation bar next to "Recipients" 27. Type in "income\_statement" in the message textbox 28. Select "CSV" from drop-down menu below the message textbox 29. Hit save to save the scheduled daily report 30. Double check the scheduled report is showing up by navigating to "Reports" > "Scheduled Reports" 31. You set up the income statement report! **LAST IMPORTANT STEP**: Navigate to the Drivepoint web-app and click on "Connect Netsuite" on the bottom right. You should see a field that is toggled on to show the live Netsuite integration.Your data will only show up after the first email has been sent from Netsuite. It could therefore take some time to show up. If you still have concerns after 48h, email [support@drivepoint.io](mailto:cs@drivepoint.io) or speak to your Drivepoint Representative. #### **I would like to have extra granularity in my forecasting. What should I do?** *💡Some of our clients create extra reports for incorporating granular data from various channels* If you would like to have extra granularity in your financial model Drivepoint supports two extra dimensions (columns) for a Netsuite report You will need to: 1. Prepare the report in Netsuite in the format similar to the image below with column B being “Class” and column C being any other extra dimension. Or find the link to the sample Income Statement [here](https://docs.google.com/spreadsheets/d/1zwfo4fTYrCK8HJ-tzMU96pu_Hx_B8P7IbVcfGOB94Xk/edit?usp=sharing). 2. Send the report sample via email ([support@drivepoint.io](mailto:cs@drivepoint.io) with the subject: “Custom Netsuite Report”), slack your Drivepoint representative or bring it up in the next call with the Drivepoint team so we can properly map those columns to the internal fields. 3. Schedule the report delivery in Netsuite to your custom Netsuite-Drivepoint integration email. # Retailer Integrations 💡 You will need the Wholesale Add-On in order to integrate with retailers. Thanks to our amazing partnership with [Muffin Data](https://www.drivepoint.io/muffin-data), we are able to power your wholesale forecasting easily. Muffin Data connects seamlessly with major retailers and sends Drivepoint's platform reliable wholesale data frequently so you can see granular wholesale data on a weekly basis. **Supported Retailer Integrations**
& many more
Retailer Integration Setup View in Muffin Data
Example of pop-up within Cin 7 Core API setup
The green rows indicate that there are no issues and everything matches QBO.
Example: Latest data for QBO that can be imported into the SmartModel is from June 18th, 4am EST
Drivepoint > Reports > DTC Sales
Sales Dashboard within Amazon Seller Central
Drivepoint > Reports > Amazon Sales
Muffin Data Dashboard
R-Wholesale by PRA / Product / PRA Product
# SmartModel Best Practices How to best work in the SmartModel™ (without breaking anything!) Excel is a magical tool in part because of its immense flexibility. But to preserve your sanity and allow a machine (the Drivepoint Add-In) to work properly, there are a few restrictions that have to been enforced: 1. **Don't Delete Rows, Columns or Tabs.** In general, don't delete rows or columns in your model. If you really don't want to see something, use the native Excel options to **Group** or **Hide** rows or columns instead. Avoid deleting tabs unless you created them and know for certain they're not "wired" into the model in some way (e.g. if you created a quick scratch tab). 2. **Don't Insert New Columns.** Adding columns is a no-no, since the model and Add-In expect certain data to appear in certain specific columns. Column structure is protected by default to help make sure this doesn't happen by accident. If you need to insert columns for a specific reason, please contact us for support and we're happy to help find a solution. 3. **Column B is for Drivepoint.** Our add-in uses Column B to read your model and move the right data in and out of your sheets. Don't manipulate the data in this column unless you know exactly what you're doing. And so you don't think it's all doom and gloom, the following operations are totally safe: 1. **Add (Whole) Rows Wherever You Want.** You can add whole rows to create calculations and notes without fear. Adding rows is almost guaranteed to be a safe operation. Go for it! 2. **Add Any Tabs Any Time.** Add tabs to your heart's content for scratch calculations or quick schedules. If you're building a more permanent schedule or something you'd like to integrate with the Drivepoint system, your sheet will need to adhere to the Drivepoint schedule spec and be registered with the model - just give us a shout and we're happy to help with this. {% hint style="success" %} **Hit us up!** When in doubt about any operation in the model, just ask! Slack your account rep or email us via
"Live Model" and Working in Excel
* What does the notion of live model mean? (min 0:39) * My formulas are not calculating how do I fix that? (min 5:52)Marketing Scenarios + CAC + New Ad Sources
* How do I override my forecast for an existing ad source? (min 1:34) * How do I add a new ad source? (min 3:00) * How do I adjust my CAC? (min 6:45) * How should I think about CAC across channels even though Drivepoint only asks for a blended CAC? (min 7:20) * How should I think about how a new ad source influences my CAC? (min 8:15)Checking my Work by Utilizing Drivepoint Templates
* How can I check the Marketing changes that I made and which templates are the most useful? (min 9:15) * How do I compare against a base plan? (min 10:35)Adding new Wholesale/Retail Accounts
* How do I add a new account/chain that I am starting to sell in? (min 12:57) * How do I name my Wholesale tabs correctly? (min 14:56)Adding New SKUs + Changing my Sales Mix
* How do I add a new SKU (min 19:09)? * How should I think about import shipping? (min 19:31) * How should I think about landed unit costs? (min 19:53) * How do I change my sales mix? (min 21:10) * How should I indicate cannibalization of Sales by product with new product launches? (min 21:43) * How do I change my channel pricing? (min 21:58) * Is there an easy shortcut toOther Tips
* As you are building scenarios, go big in your assumptions so that you can truly see the impact of the scenario. Instead of $4000 for Bing Ads, go for $400,000 in Bing Ads. * If your product sales mix + pricing is generally pretty stable, we have a shortcut for assuming product information. (min 22:04)| Reports | Reports are tabs that present the output of your model. | |
| Schedules | Schedules include inputs and are how the model calculates its outputs. | |
| Data Tabs | Data tabs contain data tables that are used to drive your schedules. |
Blended Paid Customer Acquisition Cost (CAC) - Orders
Calculation: Direct Advertising Spend divided by First Time Customer Orders Description: This represents the blended (average) cost to acquire a First Time Order into the business. This is used to gauge advertising spend efficiency and profitability on a more granular level. We can use this to view the cost of bringing on an “average order” during a specific time period. We can then track additional lifetime purchases of a cohort against this metric to determine if and when this cohort of orders are net profitable to the business (meaning they have paid back these direct advertising costs).First-Time Customer Orders
Calculation: n/a Description: First-Time Customer Orders here means all Shopify orders that are the first order for the customer regardless of their Shopify segment (Subscription, One-Time Purchase etc.) during the defined period (usually Month). * First time represents that this is the first month the customer has purchased an order * Note: if a customer purchases two orders in that same month they both will be considered first time as they are grouped within that first month.First-Time Customers
Calculation: n/a Definition: Similar to First-Time Customer Orders, *First-Time Customers* represent the number of unique customers that purchased an order in a given segment for the first time (regardless of Shopify segment such as subscription or one-time purchase) during the defined time period (usually Month). * This will often be lower than First-Time Customer Orders as customers can order more than one order during the time period (either within the same segment or amongst multiple segments). * Note: these customers may have ordered previously in other non-Shopify segments (such as Amazon or Wholesale) but for simplicity of attribution, those are excluded here.First-Time Order to Customer Ratio
Calculation: First Time Customer Orders divided by First-Time Customers Definition: This represents the ratio of first time customer orders to first time unique customers. This ratio can tend to be around a 1.0 but will vary based on frequency of ordering. * For example, if customers tend to order more frequently than one per month, such as bi-weekly, this number will trend notably higher than 1.0.Blended Paid CAC (Customers)
Calculation: Direct Advertising Spend Divided by First-Time Customers Definition: Similar to the Blended CAC - Orders, this represents the blended (average) cost to acquire a First Time Customer into the business. This is used to gauge advertising spend efficiency and profitability on more of a customer basis. We can use this to view the cost of bringing on an “average customer” during a specific time period. We can then track the lifetime purchases of this cohort against this metric to determine if and when they are net profitable to the business after including those direct advertising expenses.Blended Average Order Value
Calculation: Total Gross Sales divided by the Total Orders for the Period. *💡 Total Orders Represents both First-Time and Returning customer orders.* **Definition**: This approach represents, on average, how much a customer pays for an order in this segment on Shopify during the time period. This is a useful metric to start to understand overall unit economics to the business as well as a starting point for granular analysis into Customer Lifetime Value (LTV). *💡 Since Gross Sales is used as an input here, this represents the average price paid for an order before any discounts, refunds, shipping income or Taxes.*Orders (First Time)
**Calculation**: n/a **Definition**: This represents all orders within the first month within the One-time (OTP) segment - meaning that these customers have no prior purchases in another month in either OTP or Sub segment within Shopify. *💡 These could have been repeat purchasers from Wholesale or Amazon, but for simplicity of attribution, they are treated as first time in DTC.* All orders in that first month within the segment are considered first-time, meaning there can be more than one order per one first-time customerOrders (Returning)
**Calculation**: n/a **Definition**: Similar to First-Time Orders, these represent returning customers in the OTP segment. These returning customers signify that Shopify has recorded at least one other purchase from this customer in the history of your store and this order took place not in the first month that the customer purchased.AOV (Gross Sales Per Order) - First-Time
**Calculation**: Total Gross Sales from First-Time OTP orders in the period divided by Total First-Time Orders for the period. **Definition**: This metric represents the average price paid per First-Time order in the OTP segment for the given period (e.g.,, month of July). Note: because this metric utilizes Gross Sales in its numerator, it represents the average price paid *before* any discounts, returns, refunds or taxes are considered.AOV (Gross Sales Per Order) - Returning
**Calculation**: Total Gross Sales from Returning OTP orders in the period divided by Total Returning Orders for the period. **Definition**: This metric represents the average price paid per Returning order in the OTP segment for the given period (e.g.,, month of July). Note: because this metric utilizes Gross Sales in its numerator, it represents the average price paid *before* any discounts, returns, refunds or taxes are considered.Blended Average Order Value
Calculation: Total Gross Sales divided by the Total Orders for the Period. *💡 Total Orders Represents both First-Time and Returning customer orders.* **Definition**: This approach represents, on average, how much a customer pays for an order in this segment on Shopify during the time period. This is a useful metric to start to understand overall unit economics to the business as well as a starting point for granular analysis into Customer Lifetime Value (LTV). *💡 Since Gross Sales is used as an input here, this represents the average price paid for an order before any discounts, refunds, shipping income or Taxes.*Orders (First Time)
**Calculation**: n/a **Definition**: This represents all orders within the first month within the One-time (OTP) segment - meaning that these customers have no prior purchases in another month in either OTP or Sub segment within Shopify. *💡 These could have been repeat purchasers from Wholesale or Amazon, but for simplicity of attribution, they are treated as first time in DTC.* All orders in that first month within the segment are considered first-time, meaning there can be more than one order per one first-time customerOrders (Returning)
**Calculation**: n/a **Definition**: Similar to First-Time Orders, these represent returning customers in the OTP segment. These returning customers signify that Shopify has recorded at least one other purchase from this customer in the history of your store and this order took place not in the first month that the customer purchased.AOV (Gross Sales Per Order) - First-Time
**Calculation**: Total Gross Sales from First-Time OTP orders in the period divided by Total First-Time Orders for the period. **Definition**: This metric represents the average price paid per First-Time order in the OTP segment for the given period (e.g.,, month of July). Note: because this metric utilizes Gross Sales in its numerator, it represents the average price paid *before* any discounts, returns, refunds or taxes are considered.AOV (Gross Sales Per Order) - Returning
**Calculation**: Total Gross Sales from Returning OTP orders in the period divided by Total Returning Orders for the period. **Definition**: This metric represents the average price paid per Returning order in the OTP segment for the given period (e.g.,, month of July). Note: because this metric utilizes Gross Sales in its numerator, it represents the average price paid *before* any discounts, returns, refunds or taxes are considered.**Structure of the Wholesale Schedule that is powered by Muffin Data** * [Profit and Loss Summary](#profit-and-loss-summary) * [Sales Cash Flow Summary](#sales-cash-flow-summary) * [Gross Sales by Account](#gross-sales-by-account) **Let’s dive into each section and understand it in detail.**
#### **Profit and Loss Summary** This section provides a high level overview on the core financial metrics for your wholesale data schedule. Easily identify the total monthly gross sales, discounts, returns, COGS and Marketing Expenses for your wholesale business. Once you have the quick brief on the core financial metrics, you can continue on in the schedule to view the Sales Cash Flow Summary.
#### Sales Cash Flow Summary Knowing that payment schedules in wholesale are quite variable and dependent on the specific account, you are able to view your monthly wholesale cash flow in this row. Now, it’s time to dive into the details and see how the core financial metrics, including the cash flow, is broken down into more granular categories.
#### Gross Sales by Account This section identifies the main drivers for the wholesale gross sales and direct costs, making it the “bread and butter” of the wholesale tab **Definitions of the Section:** * Account: the business that purchases your product and sells it either directly to consumers in their stores or sells it again to other stores (e.g., Distributors). * Stores Selling: the number of individual stores your product is actively selling in * Average SKUs per Store Selling: the number of individual product items present per individual store. * Velocity (Units Sold per SKU per Store Selling per week): the number of units sold per individual product item per individual store per week. This is a measurement of how fast your individual products are selling on average. **Got more specific questions?** {% content-ref url="/spaces/GWP01Uan8w7wePRkCAQS/pages/JIL9p5hP3IZ9pTXZcuqP" %} [Contact Us](/help-1) {% endcontent-ref %} # Product Your home to add any and all individual Product information. Our most effective customers maintain this tab with all core information on SKUs (whether it's individual products or bundles) as a back bone to some of their forecasting across different channels. We are working on a native product mapping feature that will help the maintenance and reference of products across all Drivepoint plans. **Want to be a beta tester?** {% content-ref url="/spaces/GWP01Uan8w7wePRkCAQS/pages/JIL9p5hP3IZ9pTXZcuqP" %} [Contact Us](/help-1) {% endcontent-ref %} # Opex Forecast your Operating Expenses. In this video, we cover: 1. An overview of the Opex schedule 2. How to forecast expenses for your existing GL accounts 3. How to forecast expenses for a new account that's not in the GL {% embed url="
Is there a simple way to pull an excel doc showing the full budget, with balance sheet, to show bankers and investors?
I would recommend sending just an export of the Monthly Summary tab (if you need it monthly) or the 3Y Plan Tab if Annual Summary works. I f on Web version of excel (vs. Desktop App) File -> Create a Copy -> Download a Copy and then just Copy those tabs into a new Separate Workbook. (If in Desktop you can just copy the tabs right away). Once in that new workbook with just copy of the tabs, you can break the links to the main model so that if an investor opens it it won't try to refresh etc.How do I forecast DTC Net Revenue?
**To forecast net revenue** navigate to the the DTC - Acquisition and DTC OTP tab. -> DTC - OTP schedule is where first time & returning orders and first time & returning gross AOV assumptions can be toggled **For the Ad spend forecast**, navigate to the Acquisition tab. -> This is where direct ad spend is divided by first time orders to calculate Blended CaC for historical periods, which you can then update in forecast.How do I add a new product in the model?
**Step 1:** Start on the Product tab in the SmartModel™️ *New Products are entered into the Average Unit Cost - Material and Direct Labor section -> this will populate product lists throughout the model (DTC, Amazon, Wholesale and Retail Tabs).* **Step 2:** Enter assumptions for average cost by month in this section *Assumption percentages for freight, import tax, and shipping costs can be entered in sections below* **Step 3:** However if your inputs from above include those amounts you can disregard these. **This will all flow into a summary of landed costs by product by month at the top of the schedule**How do I calculate and update AOV?
**We have updated our AOV calculation so you can now incorporate the sale of new products more explicitly in the DTC - OTP tab.** *Previously we just used Shopify AOV data to predict future AOVs in rows 42 and 87.* **Step 1:** Navigate to the yellow DTC - OTP tab in the SmartModel™️ The new method is to adjust “Attach %” which simply describes the number of each product (in units) in proportion to overall orders. **Step 2:** Attach % = 100% would suggest 1 unit per Order, while 200% would suggest 2 units per order. These rates for historical (legacy) products are calculated based on Shopify data for your reference while forecasts require your input based on expectations of take rates on those new products. Additionally, overall attach rates for legacy products will likely decrease after launch of new products given the size of those AOVs so it may be prudent to trend down those legacy rates relative to historical trends. **Step 3:** Repeat these attach % inputs for First-Time and Returning Customers. These rates will then be used in combination with GMV or prices per unit by product to estimate overall AOVs for First-Time and Returning customers.Where do I input my Sales Mix?
Given the AOV updates using attach %, the Sales Mix on the DTC tab will now be an Output vs. Input. **Step 1:** Navigate to the DTC tab **Step 2:** Scroll to the "Costs of Goods Sold - Units Sold" section **Step 3:** View list of products which mirrors the input on the yellow Product tab schedule.Orders vs. Order Items vs. Units Ordererd (with image)
* **Order**: A customer's completed request to purchase one or more products from the store.
* **Line Items (on Amazon as Order Items)**: Distinct product variants that were added to the order. A line item will have an associated quantity that represents the number of units purchased for that distinct product variant.
* **Units Sold (on Amazon as Units Ordered)**: The total number of products that were purchased on the order. This is calculated by summing up the quantities per line item.
Find the "Add-Ins" button on the far right
Visual Overview
Help?! I don't think I have a manual sign-in option?
To use your Google email and password, navigate to the Drivepoint Web-App. Click Alt / Option and click on your icon on the top right. You can see an option to link your Google account. Once successfully linked you can sign into Drivepoint on Desktop manually but with your Google Email + Google Password.Help?! I need to re-add the Add-In every single time?
We sometimes observe this is the case when you are not signed in properly with your Excel account or if your company does not have a Microsoft Excel 365 license. [Reach out](/help-1) to our team with any questions in terms of which email address we should add to your Drivepoint account so that you don't have to re-add the Drivepoint Add-in every time.
Honey - I am home!!
My QBO was skipped. Why?
This likely happened because some of your accounts are not mapped to Drivepoint categories. In order to map Drivepoint categories, click on the side arrow next to QBO in data import and map the accounts to the Drivepoint categories. If the issue persists, please contact Drivepoint Support viaMy data was only imported partially. What should I do?!
Sometimes it can happen. Don't worry! There is a way to import specific tables that might have failed in the "All Data Import" or specific data import per source. Here's how you can import a specific table that might have failed: 1. Click on the Info button to see which table did not import (e.g. R - DTC Retention) 2. Click on the **>** arrow next to specific data source that failed to import a table 3. Select the table in the drop-down that failed to import 4. Change or keep the defaults of the table settings *(if you are unsure, stick with the defaults)* 5. Click on import 6. Success - it should have worked! If you are still experiencing issues please contactWhat tables are imported when I import "All Shopify Data"?
We will import the following tables when importing all Shopify data: 1. Product Sales Mix 2. DTC Retention Predictions 3. Cohorted Sales 4. Monthly Shopify Data Pivot All of these options can also be selected individually when clicking the ">" next to the Shopify option in the Data Import screen.What tables are imported when I import "All Amazon Data"?
For Amazon data, we import the following tables: 1. Amazon Monthly 2. Amazon Product Sales Mix 3. Amazon Retention Predictions All of these options can also be selected individually when clicking the ">" next to the Amazon option in the Data Import screen.Where does the imported data live?
Newly imported data lives in the "R-" tabs in your Excel files. For example: * R-GL: is the general ledger and therefore the raw data import sheet for your financial information that maps throughout the file * R- DTC Product Sales Mix: is the import tab for Shopify product sales mix actuals and information. If you import fresh data, the model should automatically update with the fresh data BUT it is always good to double check. [Reach out to our team](/help-1) if you want to learn more.
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Please do not map these accounts!
Create new Plan Interface
Compare Plans tab in the SmartModel™
Help!? I need to re-add the Add-In every single time?
We sometimes observe this is the case when you are not signed in properly with your Excel account or if your company does not have a Microsoft Excel 365 license. [Reach out](/help-1) to our team with any questions in terms of which email address we should add to your Drivepoint account so that you don't have to re-add the Drivepoint Add-in every time.What is sync and why do I have to do it?
Syncing pushes all of your progress from the Excel file into the Drivepoint Cloud. This currently does not happen automatically so we rely on you to press "Sync" after you have completed your working session. Learn more [here](/navigating-the-excel-add-in/core-functions-of-the-drivepoint-add-in/sync-to-drivepoint).What are all of the timestamps in the Add-in?
Drivepoint is not fully synced to raw data meaning that YOU have to import fresh data into your files before a roll forward or a working session. The Drivepoint Data Warehouse (DWH) grab raw new data from sources every couple of hours. You can see the freshest data available for you to import into your model from the Drivepoint cloud as "Freshest data available in the Data Warehouse". When we talk about last time this data source was imported into the model it is the timestamp of when you or your colleague have pressed the "Import" button to get data into the mode. Learn more [here](/navigating-the-excel-add-in/core-functions-of-the-drivepoint-add-in/import-data).Where does the freshly imported data live?
Newly imported data lives in the "R-" tabs in your Excel files. For example: * R-GL: is the general ledger and therefore the raw data import sheet for your financial information that maps throughout the file * R- DTC Product Sales Mix: is the import tab for Shopify product sales mix actuals and information. If you import fresh data, the model should automatically update with the fresh data via Lookup formulas BUT it is always good to double check. [Reach out to our team](/help-1) if you want to learn more.What does promoting a live model mean again?
This essentially indicates to you, your team and us which Excel file you are viewing as your source of truth and source of actuals. If you decide to promote a new Excel file as the new live model then the Drivepoint Tech will grab actuals from that new file for all financial reports moving forward (and retroactively).How can I delete old plans?
In the Web-App, click on the three dots of the row of the plan you would like to delete and then "archive" to remove them from the UI.
How do my cohorts automatically include the most recent cohort?
You can select a time range in the future to include recent months. Example: Today is September. I want to make sure March cohort is included in my 180 Days LTV report. You can just select Jan-Dec 2025 in the absolute date picker and every time you re-access the report in the future it will include the matured cohorts -> e.g. March next month. *Users can select months in the future to avoid having the problem of including future matured cohorts, as you described: They could also select Jan 2025 - Dec 2026 if they want.* You could also create a relative lookback window if you don't want to look at YTD but the last 12 months maybe by selecting "Last 12 months" and then they will see Oct, Nov, Dec, Jan, Feb today and next month "March" (remove Oct), etc. So you basically create a relative lookback period that moves with time.What are Breakdowns, Metrics and Filters?
### Breakdown Segment to group your data into different categories. ### Metrics Add an event to analyze. You can select one or multiple metrics depending on the report. ### Filters Filter to include or exclude specific data.# Cohorted Financials This report is derived by combining the financial information from the Drivepoint Smartmodel™️ and your Sales data (e.g. DTC Sales from Shopify or Amazon Sales from Amazon). ## Determining Contribution Profit In order to calculate contribution profit per customer, the contribution margin pulled from the model is applied towards every single order that occurred within the same month. Since the contribution margin is not calculated per product, keep that in mind when using the `First Segment` filter that the average contribution margin from a month has been applied across **all products**. ## Determining Total Cost and Customer Acquisition Cost (CAC) The report provides insights into key cost metrics, including **Direct Ad Spend** and **Total Marketing Spend**, which represent the investment required to acquire new customers. **Total View** When selecting the **Total** metric type, the report displays the absolute amount of **Direct Ad Spend** and **Total Marketing Spend** for each month. This allows for an analysis of overall spending trends without adjusting for customer count. **Per Customer View** When selecting **Per Customer**, the report divides these costs by the number of customers acquired in each month, providing an average cost per customer. For instance, the direct ad spend for Jan. 2024 was $10,000 and the number of customers acquired in Jan. 2024 was 200; thus, the Blended Spend CAC (Customer Acquisition Cost) for the month was $50 (`$10,000 spend / 200 customers`). As a result, this calculation generalizes that 100% of the spend is towards customer acquisition, which Drivepoint has found to be close to true across a portfolio of companies. Similar to the determination of contribution profit mentioned above, there is no attribution of the CACs to a specific segment. The marketing spend that acquires a customer is not determinant of the product the customer chooses to buy. ***Amazon can often experience a 14 day lag. Click below to learn more.*** {% content-ref url="/pages/N9BKbfVSxVucmF4yc5IK" %} [Amazon Reports](/using-the-web-app/reports/amazon-reports) {% endcontent-ref %} ## Definitions **Metric Type:** This report allows you to analyze customer financial metrics in two different ways: * **Per Customer (Selected by Default):**\ When the **Per Customer** option is selected, all financial metrics are divided by the **Cohort Size**, providing insights at an individual customer level.\ Example: **Net Sales** is calculated as **Cumulative Net Sales / Cohort Size**. * **Total:**\ When the **Total** option is selected, financial metrics are displayed in absolute values without dividing by cohort size. This allows for an overall view of revenue and profitability trends across all cohorts.\ Example: **Net Sales** in **Total** mode reflects the **total cumulative net sales** without normalization per customer. *** * **Months Since First Purchase:** Calculated as calendar months from the date of the first purchase. Month 0 represents the partial calendar month in which the first purchase occurred. Month 1 and onward represent the full calendar months that follow. *For instance, a customer was acquired in Jan. 2020. The Month 0 is representative of that first purchase and any purchases that followed within Jan. 2020. Month 1 would represent any purchases that took place in Feb. 2020, Month 2 would be Mar. 2020, Month 3 as Apr. 2020, and so on.* * **Gross Sales:** Cumulative Gross Sales / Cohort Size * **Net Sales:** Cumulative Net Sales / Cohort Size * **Net Revenue:** Cumulative Net Revenue / Cohort Size *The following metrics rely on financials being saved from the model to the data warehouse during a Save Plan action. If you see, for instance, a Blended Spend (CAC) at $0 for a Cohort Month, you may need to save a plan.* * **Contribution Profit :** Cumulative Contribution Profit / Cohort Size * **Blended Spend:** Direct Ad Spend / Cohort Size * **Fully Loaded Spend:** Total Marketing Spend / Cohort Size * **Contribution Profit Less Blended Spend:** Contribution Profit - Blended Send / Cohort Size * **Contribution Profit Less Fully Loaded Spend:** Contribution Profit - Fully Loaded Spend / Cohort Size *💡Example: After 4 months, the Contribution Profit Less Fully Loaded Spend (aka without any direct costs related to acquiring a customer) of customers who bought a subscription in Feb-23 is $14. After 10 months their Contribution Profit without fully loaded Spend is $20.*
# Customer Retention This data is pulled from Sales data (e.g. DTC Sales from Shopify or Amazon Sales from Amazon). ## Definitions *In order to focus on the customer retention after the first purchase, this report completely excludes the first purchase from any of the calculations. As a result, any Day 0, Week 0 or Month 0 Since First Purchase displayed that would always be 100% will instead represent the percentage of customers that made a returning purchase within the same period in which they made the first purchase.* **Customer Retention:** Cohorted by when they made their first purchase (*Cohort Interval*), the number of customers that made a returning purchase divided by the number of customers from the cohort (*Cohort Size*). **Cohort Interval:** This is a control available in the *Filters* menu with the possible options of *Quarter, Month*, *Week*, and *Day*. Each option groups first-time customers together into cohorts based on the interval selected. For instance, a customer that makes their first purchase on January 15th, 2024 is cohorted into Q1 2024 (*quarter*), Jan-24 (*month*), (*week of*) Jan 14, 2024, and Jan 15, 2024 (*day*). **Interval Since First Purchase:** This is a control available in the *Filters* menu with the possible options of *Month*, *Week*, and *Day*. Each option calculates the calendar distance since the first purchase. *As an example, let's assume we selected Month and we're looking at customers acquired in Jan. 2020. The Month 0 is representative of any purchases that followed within Jan. 2020. Month 1 would represent any purchases that took place in Feb. 2020, Month 2 would be Mar. 2020, Month 3 as Apr. 2020, and so on.* ***Amazon can often experience a 14 day lag. Click below to learn more.*** {% content-ref url="/pages/N9BKbfVSxVucmF4yc5IK" %} [Amazon Reports](/using-the-web-app/reports/amazon-reports) {% endcontent-ref %} ## Pro Tips & Tricks 1. View the performance of your previous 12 month cohorts in a graph and table. 2. Hovering over the graph will show you the percentage of customers acquired that made a returning purchase broken down per month. *💡Example: 5.1% of customers who bought their first product in October-23 also purchased a product in the following month (November-23). Whereas 6.1% of customers who bought their first product in May-23 purchased a product in the following month (June-23)* 4. Toggle between different segments to uncover further insights (i.e.. Subscription vs. Non-Subscription) *💡No segments specified? Talk to your Drivepoint rep or contact us* 5. Toggle between different timeframes to hone in on specific cohorts. 6. Export the graph and table by clicking the arrow button in the top right. # LTV/Retention by Dimension This report is derived from your Sales data (e.g. DTC Sales from Shopify or Amazon Sales from Amazon). ## Definitions **Cohort Start Date:** This filter defines the period in which the customers made their first purchase. By default, this report is set to a period from two years ago to one year ago so that we use a large cohort that has aged exactly one year. **Cohort Dimension:** Pick the dimension you would like to compare LTVs or retention between. For instance, if you select "First Order - Product Title", you'll receive a cohorted comparison over time of each product title purchased on the first order in terms of the metric you select (e.g. Customer Retention). **Interval Since First Purchase:** This is a control available in the *Filters* menu with the possible options of *Month*, *Week*, and *Day*. Each option calculates the calendar distance since the first purchase. Metrics: * **Customer Retention:** `Returning Customers / Cohort Size` * **Gross LTV:** `Cumulative Gross Sales / Cohort Size.` * **Net Sales LTV:** `Cumulative Net Sales / Cohort Size` * `Net Sales = Gross Sales - Discounts - Returns` * **Net Revenue LTV:** `Cumulative Net Revenue / Cohort Size` * `Net Revenue = Net Sales + Taxes + Shipping` *The below metrics utilize a blend of transactional data and financial data from the SmartModel. These metrics include an **asterisk (\*) as a caveat** to their use in this report due to how they're constructed. These are constructed by applying the SmartModel's monthly actuals on contribution margin to every order that occurred within the same month and by applying monthly marketing spend actuals to every **first-time** order within the same month.* *As such, drilling down deep to a specific product, for instance, may not generate a true LTV for that product, but will allow the user to get an estimate at that level using average numbers sourced from the SmartModel. All of the metrics listed above (e.g. Net Revenue LTV), however, are true to any combination of filters or groupings since we purely use transactional data for those.* * **Contribution Profit LTV\*:** `Cumulative Contribution Profit / Cohort Size` * `Contribution Profit = Contribution Margin * Net Revenue` * **Contribution Profit LTV Less Blended CAC\***: `Contribution Profit LTV - (Direct Ad Spend / Cohort Size)` * **Contribution Profit LTV Less Fully Loaded CAC\***: `Contribution Profit LTV - (Total Marketing Spend / Cohort Size)` ## Constructing LTV and Retention Curves This report only outputs LTVs or Retention Rates of *n* **Intervals Since First Purchase** such that every customer within the cohort would've had a chance to purchase up through the very last **Interval Since First Purchase**. *Let's dig into that further...* When opening the report for the first time, it will default to a **Cohort Start Date** range between two years ago and one year ago. As a result, the report will pull LTVs of a length exactly equal to one year. The report will also default to using *Months* as the **Interval Since First Purchase**. This means that, for every month represented in this report, every customer in the cohort would've have a chance to make a returning purchase from Month 0 all the way to Month 12. So if you were to look at *Days* **Intervals Since First Purchase** and set the **Cohort Start Date** range to, say, six months ago to 15 days ago, the LTVs outputted would only be a length equal to 15 days. This is because we're only constructing LTVs such that every customer has had the same length of time to make a returning purchase. (The customers who were acquired 15 days ago have only had 15 days where they could've made a returning purchase.) ***Amazon can often experience a 14 day lag. Click below to learn more.*** {% content-ref url="/pages/N9BKbfVSxVucmF4yc5IK" %} [Amazon Reports](/using-the-web-app/reports/amazon-reports) {% endcontent-ref %} ## Pro Tips & Tricks 1. Make sure to set the Cohort Start Date to a range of dates in the past. 2. View the performance by cohort of your previous 365 days in a graph and table. 3. Hovering over the graph will show the customer lifetime value by a specific segment. *💡Example: After 21 days, the net revenue customer lifetime value of customers who bought a subscription in Feb-23 is $51. After 250 days their net revenue customer lifetime value is $63.*
# N-Day LTV A pivoted way version of Cohorted Financials such that LTV and CAC can be viewed as a trend over time. *This report represents the typical way that investors like to look at LTV to understand if a business is improving, stagnant or declining in terms of its ability to generate more value out of the customers it acquires since inception.* ## Definitions
| Name | Type | Definition |
|---|---|---|
| Days Since First Purchase | Dimension | Calculated as the number calendar days from the date of the first purchase, this dimension defines each series on the chart and each column within the table of this report. Depending on the Cohort Months filter, this report can output Days 0, 30, 45, 60, 90, 180, 360, and 720. Day 0 represents the partial calendar day in which the first purchase occurred. Day 1 and onward represent full calendar days afterwards. |
| Cohort Months | Dimension | A month range filter that can select the window of time in which a customer made their first purchase. |
| Cohort Interval | Dimension | Defaulted to Month. Each option groups first-time customers together into cohorts based on the interval selected. |
| Cohort Size | Metric | The number of customers acquired within the Cohort Interval. |
| Cumulative Customer Retention | Metric | The number of customers that have made one returning purchase by n-day / Cohort Size |
| Gross LTV | Metric | Cumulative Gross Sales / Cohort Size |
| Net Sales LTV | Metric | Cumulative Net Sales / Cohort Size Net Sales = Gross Sales - Discounts - Returns |
| Net Revenue LTV | Metric | Cumulative Net Revenue / Cohort Size Net Revenue = Net Sales + Shipping + Taxes |
| Contribution Profit LTV | Metric | Cumulative Contribution Profit / Cohort Size |
| Blended CAC | Metric | Direct Ad Spend / Cohort Size |
| Fully Loaded CAC | Metric | Total Marketing Spend / Cohort Size |
| Contribution Profit LTV Less Blended CAC | Metric | Contribution Profit LTV - Blended CAC |
| Contribution Profit LTV Less Fully Loaded CAC | Metric | Contribution Profit LTV - Fully Loaded CAC |
| Name | Type | Definition |
|---|---|---|
| Intervals Since First Purchase | Dimension | Calculated as the number calendar intervals (e.g. months) from the date of the first purchase, this dimension defines each series on the chart and each column within the table of this report. |
| Cohort Months | Dimension | A month range filter that can select the window of time in which a customer made their first purchase. |
| Cohort Interval | Dimension | Defaulted to Month. Each option groups first-time customers together into cohorts based on the interval selected. |
| Purchase Path | Dimension | First Segment -> Returning Segment
|
| Cohort Size | Metric | The number of customers acquired within the Cohort Interval. |
| Calculation Method | Metric | Defaulted to Cumulative. Incremental: The number of customers that have purchased a different segment than the one they started with on the Intervals Since First Purchase / Cohort Size Cumulative: Simply a cumulative version of Incremental |
| Metric/Dimension | Definition |
|---|---|
| Order Retention | Cohorted by when they made their first purchase (Cohort Interval), the number of returning orders divided by the number of orders from the cohort (Cohort Size) in the first interval (e.g. Month 0). For example, Month 1 retention reflects the number of orders in Month 1 from customers acquired in the same Cohort Interval divided by the number of orders that the same cohort made in Month 0. |
| Cohort Interval | This is a control available in the Filters menu with the possible options of Quarter, Month, Week, and Day. Each option groups first-time customers together into cohorts based on the interval selected. For instance, a customer that makes their first purchase on January 15th, 2024 is cohorted into Q1 2024 (quarter), Jan-24 (month), (week of) Jan 14, 2024, and Jan 15, 2024 (day). |
| Interval Since First Purchase | This is a control available in the Filters menu with the possible options of Month, Week, and Day. Each option calculates the calendar distance since the first purchase. |
| Segment | Unlike the Customer Retention report where customers are completely segmented by the first segment (e.g. Subscription) they purchase, this defines the segment that was actually purchased on both the numerator and the denominator of the Order Retention formula. |
| Metric/Dimension | Definition |
|---|---|
| Nth Order Retention | The number of customers that made an nth (e.g. 7th) order divided by the number of customers in the cohort. Unlike Customer Retention, where the retention is measured is measured over time and customers can skip intervals since first purchase, customers at one order number had to have also been in all prior order numbers. For instance, a customer that has made a 4th order will show up as being retained within the 2nd and 3rd order as well. |
| Cohort Interval | This is a control available in the Filters menu with the possible options of Quarter, Month, Week, and Day. Each option groups first-time customers together into cohorts based on the interval selected. For instance, a customer that makes their first purchase on January 15th, 2024 is cohorted into Q1 2024 (quarter), Jan-24 (month), (week of) Jan 14, 2024, and Jan 15, 2024 (day). |
| Max Days Since First Purchase | Important filter to use. Since a returning order can occur at any time, this filter controls for the length of time that each Cohort Interval has had to make x number of orders. |
| First Segment | The first segment (e.g. Subscription) that the customer purchased. |
What does the Customer Type field mean?
Here is how we define customer types: * By Purchase Order: * Order split based on their first purchase and all purchases that occur afterwards. A customer can only have one First-Time purchase. **This is the same way that Shopify categorizes First-Time and Returning.** * Customer Types: * First-Time: the first purchase a customer ever makes at your brand. * Returning: any purchase after the first purchase. * By Segment Purchase Order: * Order split based on the first time they purchase a segment and all purchases of the same segment afterwards. A customer can make more than one First-Time purchase in this method, but only one per Segment. **Commonly used to see how many orders are from the first purchase of a subscription.** * Customer Types: * First-Time: the first purchase a customer makes of a Segment. * Returning: any purchase after the first purchase of the Segment. * By SmartModel Basis: * Order split that lines up with the way the SmartModel breaks purchases into two categories. * Customer Types: * Month 0: any purchase that occurs within the month the customer was acquired, which is the same month they made their first purchase. * Month 1+: any purchase that occurs in a month that follows the customer’s acquisition month.What does the Product Customer Type field mean?
**Product Customer Type**: Based on the Product Dimension selected (e.g. SKU), we determine if the customer has purchased the same Product before. * *First-Time* means the customer has never purchased this product before - even if they are a Returning Customer Type. * *Returning* means the customer has purchased this product before. You cannot have a *Returning* *Product Customer Type* combined with a *First-Time Customer Type* because it is the first purchase ever by the customer.\ \ *(Identical products purchased within the same order are considered ties and do not matter to this calculation.)*What are the Amazon fees?
Check out our overview on Amazon fees [here](/using-the-web-app/reports/amazon-reports).What are the Tik Tok Fees?
* **Commission Fee**: An amount charged for each successful order, based on rates that differ for each product sub-category. * **Transaction Fee:** An amount charged for processing successful orders. * **Affiliate Commission:** When an Affiliate has helped seller sell a product, and the order has not been cancelled or successfully refunded before the settlement period ends, TikTok Shop will automatically deduct an amount from the order. Learn more about [Seller Fees](https://seller-my.tiktok.com/university/essay?knowledge_id=2602429108078338\&default_language=en\&identity=1) and browse through [Tik Tok Shop's FAQ](https://seller-my.tiktok.com/university/essay?knowledge_id=5183284380763905\&default_language=en\&identity=1).I have multiple Shopify Stores. How can I filter across my stores?
Simple open the "Customize" panel by pressing the button on the top right and selecting the store that you would like to see under the "Store" Filter on the bottom.What are all available dimensions in the multi-filter?
* The options available in each dimension are based on the time frame. Select a longer timeframe to find an older discount code * The options in each dimension are also listed based on frequency. ## **Use Cases** 1. I want to see Sales minus the one discount code that I used for an experiment 2. I would like to see Sales coming from youtube.com 3. I would like to see Sales from the Northeast or just NYC ***Exclude any…*** * *Discount Code* * *Channel Name* * *Country/Region/City* * *Tags* * *Payment Provider* * *Landing Site* * *Referring Site* ***Select greater/less than for…*** * *Units Sold (select greater/less than)* * *Purchase Order*How do I view Total Sales or just by Sub vs. Non-Sub?
Use the Chart Dimension field! Here's a Loom on how to do that:
How do you calculate the EOM Projections Values?
The entire projection functionality is based on your historical in-month cumulative growth trend for each one of these metrics. In other words, **the report uses the historical trends to create the plan projection** instead of a linear projection (month plan value / # of days).For the high and low projection values, the prediction interval is based on a 95% confidence margin of error around the average, which is based on the standard deviation seen across time for how a month will grow (*e.g. Day 10 is 25% of total month in one month, but it's 30% of total month in another month*). The earlier in the month we are the larger this prediction interval will be given the small sample relative to the month's number of days.
What does the field "Use Channel Actuals" mean?
This field defaults to all of the transactional channels we currently fully support. If you remove one of them, the report will recalculate with the assumption that the channel you removed is now held to the plan value, meaning any deviation from plan is caused by the channel that you are still selecting in the field. For instance, if you only have "DTC Online" selected, all other channels are going to be assumed at the exact forecasted plan value.What does "Cumulative Chart View" Mean?
The cumulative chart view shows your summed Sales performance (Day 1 + Day 2 + Day 3 + ... + ). This is a helpful view to analyze how you are pacing to your end of month plan forecast.\ The non-cumulative chart view does not sum up the daily values. Instead it shows each day as a stand-alone value (Day 1, Day 2, Day 3, ..., etc).Why are metrics beyond "Operational Expenses" not categorized by channel?
This is because our standard SmartModel template does not break out these metrics by channel.I currently only have AMZ connected - will the PvP still work for me?
Currently, this report works for companies that at least have a DTC channel that's updating on a daily basis.For the high and low projection values, the prediction interval is based on a 95% confidence margin of error around the average, which is based on the standard deviation seen across time for how a month will grow (*e.g. Day 10 is 25% of total month in one month, but it's 30% of total month in another month*). The earlier in the month we are the larger this prediction interval will be given the small sample relative to the month's number of days. ## FAQ
How do I use this report?
1. Select a plan you would like to view to compare to actuals 2. Select a chart view (cumulative vs. non-cumulative) *💡See below* 3. Select a metric to viewHow can I view Sales performance across different months?
The performance vs. plan report only shows the view for a current month. If you want to evaluate Sales performance in the past months, navigate to the DTC or Amazon Sales reports. \ **💡 Type in "DTC Sales" or "Amazon Sales" in the search box on the main reports page.**How can I view my Sales pacing for multiple plans at once?
Currently, you are only able to compare against one plan. However, feel free to open the report in multiple windows (copy & paste the URL) and get a side by side view between different plans.Is there another way to get regular Sales pacing updates?
Yes! Instead of always clicking on the performance vs. plan report, feel free to click the ⏰ icon on the top right of the report to schedule an email send to you and your colleagues. Feel free to send it daily to always be up to date with your Sales performance - right in your inbox.| Term | Description | Examples |
|---|---|---|
| Stores Selling | Individual number of ACTIVE stores you are selling at | Also known as POS (Points of Sales) or doors |
| POD | Points of Distribution: POS * SKUs | Highlights how many distribution points you have as a company within a store |
| POS Sales Dollars | Revenue of retailer | The revenue Whole Foods Store on 24th St. makes from selling one Protein Bar 12-pack chocolate |
| POS Scan Velocity (Units Sold Per SKU per Store per Week) | The # of products sold per individual store per week | “Our velocity for WholeFoods 24th St for Protein Bar 12-pack chocolate was 10 last week” |
| Distribution Center Velocity | The # of products or cases shipped by individual Distribution center per week/month | "Our KeHe Portland location has a ship_to velocity to Albertson of 1000 cases a week" |
| Units Sold Per Product | # of units sold per product | Protein Bar 12-pack chocolate sold 100 times yesterday |
| Units Sold | # of units sold Can be either POS based OR distributors shipped (units sold is calculated differently per store) | We sold 2000 units across all SKUs yesterday |
| POS Revenue per Product per Store Selling per Week | Retailer revenue per Product per store per week | As Whole Foods 24th St, I made $1000 in Protein Bar 12-pack chocolate Sales last week |
P&L Benchmarks Report
Quartile Ranking
Example of the hover menu in the table
The average amount of cumulative net sales a customer has made.
Net Sales = Gross Sales - Discounts - Returns
The average amount of cumulative contribution profit a customer has contributed. This metric blends the financial model with the transactional data we pull from the APIs. We use the contribution profit margin that's tracked for every month within the model and apply it to all purchases within the same month. (If we don't have the contribution profit margin yet due to unclosed financials, we pull a three month average forward from the financials that are closed.)
Contribution Profit = Contribution Profit Margin \* Net Revenue (not used as a metric in this report
The average cumulative profit a customer contributes to the company after direct marketing expenses are removed. Blended CAC is pulled from the financial model from closed actuals. (If we don't have the closed numbers for CAC for an unclosed month, we pull forward a three month average of actuals to use until that month is closed.)
Contribution Profit LTV Less Blended CAC = Contribution Profit LTV - Blended CAC
The average cumulative profit a customer contributes to the company after total marketing expenses are removed. Fully Loaded CAC is pulled from the financial model from closed actuals. (If we don't have the closed numbers for CAC for an unclosed month, we pull forward a three month average of actuals to use until that month is closed.)
Contribution Profit LTV Less Fully Loaded CAC = Contribution Profit LTV - Fully Loaded CAC
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