Customers

The Customers page in the dashboard has two surfaces: a list view for finding customers, and a profile view for digging into one customer's full history and risk picture.

The list view

Open Customers in the left nav. You'll see Customer List (N) where N is the total customer count on your account.

Customer lists

By default, the Customers page is empty — you build your own customer lists by defining the criteria for each one. Each list appears as a tab across the top of the page, and clicking a tab scopes the customer list to that filter. The customer count in the title updates to match.

A typical Pinch account ends up with 5–10 lists. Common ones merchants build:

• Frequent Returners — customers with high return rates over the trailing period
• High Order Customers — customers placing many orders, your repeat buyers
• Damaged Returns — customers whose returns have been marked damaged on inspection
• In Store > 70% Return Rate — customers buying in-store with disproportionately high return rates (a classic switch-fraud pattern)
• High AOV Bracketing — customers with 60%+ return rate and average order value over $500 (high-value bracketing or wardrobing candidates)

These are examples, not defaults — you author the conditions that matter to your business.

Creating a list

Top-right of the Customers page, the hamburger menu next to Download opens three options: Create List, Edit List Conditions, Delete List.

Click Create List to open the condition builder:

• Name — what shows on the tab (e.g., "Frequent Returners")
• Condition builder — one or more rules of the form Where [Variable] [Operator] [Value]. Variables come from the Variables library and include things like return_rate_by_value_by_email, customer_value_by_email, orders_placed_from_this_email_in_last_6_months, etc. Operators are standard comparisons (Greater than, Less than, Equal to, Contains).
• + Add condition — add more rules to the same group (AND logic)
• + Add subgroup — add a nested group with its own AND/OR
• Sort by — pick any variable and sort ASC or DESC

Save the list and it shows up as a tab. Switch between tabs to see different cohorts of customers.

Import a list via CSV is the alternative on the same modal — paste a CSV of emails to create a fixed list rather than a condition-based one. Useful for one-off cleanup work (e.g., emails flagged by your CS team).

What you do with a list

A customer list has two outputs:

1. Export. The Download button (top-right of the page) exports the currently-active tab as a CSV with all visible columns. Use this to push customers to your CRM, share with a marketing team for win-back campaigns, or audit an abuse cohort manually.

2. Drive a Playbook. A list can power a Playbook — when a customer enters the list (matches its conditions), the playbook fires its action chain. Common patterns:

   • List "Frequent Returners with VIP value" → playbook tags them as vip-recovery and emails a personal offer
   • List "Suspected Wardrobers" → playbook adds a monitor Shopify tag and notifies CS on Slack
   • List "Returns-blocklist" → playbook emails the customer the policy change and adds an order-blocking tag

The same list can drive multiple playbooks, and the playbook re-evaluates the condition continuously, so customers move in and out of lists as their behavior changes.

Editing or deleting a list

Same hamburger menu → Edit List Conditions opens the condition builder pre-populated with the active tab's rules. Changes take effect immediately — customers re-evaluate against the new conditions on the next event.

Delete List removes the tab and (if connected) detaches it from any playbook. The list's customers stop being treated specially the moment the list is deleted — but customers who were already tagged by a playbook keep their tags until another playbook removes them.

Columns

Column	What's in it
Email	The customer's email. Click to open the profile.
Customer Value (USD)	Lifetime net value to your store — orders minus refunds minus your loaded return cost. Can be negative for net-loss customers.
Total Orders	Number of orders placed by this email.
Return Rate	Items returned divided by items purchased.
Last Return	Date of their most recent return event.
Country	Two-letter country code.
Suspected Abuse	Severity label — LOW, MEDIUM, HIGH, or NA if no abuse signal.
Abuse Risk Score	0–100 — the customer's current Pinch Assessment.

All columns are sortable. The default sort varies by the list's configured Sort by rule.

The profile view

Click any email in the list to open the customer profile. The profile is organized into four sections.

Header KPIs

Four cards across the top summarizing the customer's value to your store:

• Customer Value — net lifetime value (revenue minus refunds minus return cost)
• Return Rate — items returned divided by items ordered
• Total Order Value — gross revenue from this customer
• Total Orders — number of orders placed

A negative Customer Value with a high Return Rate is the classic abuser signal.

Customer panel

Identity and account history:

• Name as recorded on the orders
• Email address
• Phone number
• First Order date
• Last Order date

A timestamp in the top right shows the most recent activity Pinch has for this customer.

Location Details panel

Every billing and shipping address Pinch has on file for this customer. Each address shows:

• The full address as a single line
• A Street View link that opens Google Street View
• An icon indicating type (billing, shipping, etc.)

A Map toggle in the top right of the panel shows a map view of all addresses. Useful for spotting customers shipping to many different addresses (forwarding services, mules) or multiple customers shipping to the same address (multi-account abuse).

Pinch Assessment panel

The most important panel for risk decisions.

• Score: 0–100 with a gradient bar showing where this customer falls (green = safe, red = high abuse risk)
• Suspected Abuse Type: the pattern that best fits this customer (Wardrobing, Empty Box, Copycat, etc., or N/A)
• Triggered Workflow: the workflow branch that last ran on this customer (e.g., Very High Returns Low Value Customer Email)
• Key Risk Indicators: the individual variables that drove the score, with their current values. Examples:

Variable	What it measures
customer_value_by_email	Net value Pinch attributes to this email
orders_placed_from_this_ship_add_in_last_6_months	How many orders shipped to this same address recently
num_email_per_ship_address_in_last_180_days	How many different emails ship to this address
return_due_to_size_ratio_by_ship_address	Fraction of returns this address has filed citing size
return_rate_by_value_by_email	Dollar-weighted return rate for this email
customer_value_by_ship_address	Net value at the address level
orders_placed_from_this_ip_in_last_6_months	Orders coming from this IP
customer_value_by_ip	Net value at the IP level
orders_placed_from_this_email_in_last_6_months	Recent activity on this email
return_rate_by_value_by_ship_address	Dollar-weighted return rate by address
return_due_to_size_ratio_by_email	Size-reason return ratio by email

A negative customer-value variable with a high return-rate variable on the same row is your clearest tell.

• Social: any social-profile signals Pinch has matched (Instagram, etc.)

Customer History

The bottom half of the profile. Two tabs:

Order History tab

A table of every order Pinch has on file for this customer. Columns:

ORDER ID, DATE, TYPE (Online, In-store), DECISION (Allow/Deny/Review), CUSTOMER, EMAIL, PHONE, SHIPPING, BILLING, IP, DEVICE ID, PINCH ID, AMOUNT, RETURN AMOUNT, DAMAGED RETURN.

The right side has shortcut buttons:

• All Orders — toggle between only-orders-with-returns and all orders
• Email — switch to email-level rollup
• Time-range chip (1Y by default)
• Filters — opens a drawer for narrowing by decision, amount, return status, etc. A badge on the button shows how many filters are active

Customer Graph tab

Visualizes how this customer's identifiers (email, phone, billing, shipping, device IP, device fingerprint) link to other customers in your store. The same person operating under multiple emails, or multiple accounts shipping to the same address, becomes obvious here.

A Connection Types filter row at the top of the graph lets you toggle which edge types are shown:

• Email
• Phone
• Billing
• Shipping
• Device IP
• Device

A Labels toggle shows or hides node labels.

For customers with no linked identifiers (single email, single device), the graph is essentially empty — that's a good signal in itself.

See Pinch Identity Number for the underlying model.

Ask AI

A floating Ask AI button in the bottom-right of the profile opens a customer-context chat. Type a question and the assistant has full visibility into this customer's history, score, and graph. Useful for:

• "Why is this customer's score so high?"
• "Has this customer ever had a Triggered Workflow for abuse before today?"
• "Are there other customers linked to this device?"
• "What's the strongest single reason to deny this return?"

The chat is scoped to one customer at a time — opening a different profile starts a new conversation.

Day-to-day use

Operators typically use Customers in three ways:

1. From the Review queue, click a customer email to open their profile and check context before approving/denying a flagged return.
2. Weekly proactive review — open whichever list matters for the week (Frequent Returners is a common starting point), sort by Abuse Risk Score, and look at the top 10–20 to see if any need a manual outreach or a tag update.
3. CS support requests — when a customer emails support asking why a return was denied, the rep opens the customer profile, reads the Triggered Workflow and Key Risk Indicators, and responds with the relevant policy from your return-policy URL.

See also

• Review queue — links to customer profiles for context
• Pinch Identity Number — the linking model behind the Customer Graph
• Analytics — segment-level views of the same customer data
• Playbooks — what happens automatically when a customer enters a segment