What Are Customer Properties?
Customer Properties is a persistent customer data layer built directly into Qtrac. Unlike standard visit data that resets with each interaction, Customer Properties remembers key customer context across every visit and appointment including status, flags, preferences, history, loyalty tier, and more. Properties are organized into categories and templates, assigned to workflows, and surfaced in both associate-facing views and Insights reporting.
Properties can be assigned directly to fields so that data like Member ID is always captured and stored, or populated through rules-based scenarios so that events like "customer abandoned" automatically move a customer into a High Risk category.
Think of it this way: a customer's risk level, loyalty tier, or student ID doesn't reset each time they walk in. It travels with them.
Why Does It Matter?
For Your Customers
Teams no longer need to re-ask basic questions every visit. Associates can see who the customer is, what they value, and what has happened before, delivering more relevant and connected service that builds trust over time.
For Operations
Persistent attributes drive intelligent decisioning. Customer properties can power prioritization and routing rules, enable meaningful segmentation in Insights reporting, and support personalization in customer touchpoints while they wait.
For the Business
Customer context compounds. As properties accumulate from real interactions, the platform becomes more effective over time, improving satisfaction, enabling segmentation, and making every customer touchpoint more relevant and measurable.
How Properties Work
Properties vs. Visits
Visit data records what happened that day — the service, the outcome, whether they abandoned. Properties record what is true about the customer right now. Even if you pull up a visit from 6 months ago in Insights, the property columns will always show the customer's current property values, not what they were at the time of that visit.
Property Types
There are two practical types to use:
- Text — a free-form value (e.g., a phone number, an email address, a date)
- Dropdown — a fixed set of options (e.g., High Risk / Medium Risk / Low Risk)
Categories
Properties are organized into categories to keep things manageable. Example categories:
- Customer Identifiers — fields like mobile phone, student ID, or email
- Customer Risk — fields like risk level or fraud flag
- Purchase History — fields like last purchase date or lifetime value
How Customers Are Recognized Across Visits
For properties to follow a customer, Qtrac needs a way to identify that "this person today is the same person from last time." You do this by mapping a workflow question to a property field — for example, mapping the "Mobile Phone" question to the Mobile property.
When a returning customer enters their phone number, Qtrac looks it up, finds an existing record with that number, and automatically loads all properties attached to that customer — even properties from a different identifier (like a student ID they provided on a prior visit).
Note: This is different from the Customer Profile, which only recognizes customers by phone or email. Properties can recognize customers by any mapped identifier — student ID, loyalty card number, account number, etc.
How Properties Get Updated: Rules
Properties don't change on their own — you control them through Advanced Rules. Examples:
| Trigger | Action |
|---|---|
| Customer completes service | Set Risk Level → Low Risk |
| Customer abandons 3 visits in a row | Set Risk Level → High Risk |
| Service outcome = "New Card Provided" | Set Last Purchase Date → Today |
| Customer sends a message containing "cancel" | Set Sentiment → Frustrated |
| Customer completes service (any) | Set Sentiment → Satisfied |
Once a property is set, it stays that value until another rule fires and changes it.
Industry Use Cases
🏦 Banking
Use case: Customer risk and relationship tier tracking
A bank branch uses Qtrac to manage the lobby. When a customer joins the virtual queue, they enter their account number. Qtrac maps this to a "Customer Identifier" property.
Properties configured:
- Risk Level (dropdown: Low / Medium / High) — updated when a teller flags a suspicious transaction outcome
- Relationship Tier (dropdown: Standard / Premier / Private Banking) — set when a customer completes a qualifying service
- Last In-Branch Visit Date (text) — updated every time the customer completes a visit
Branch managers can pull up any customer in Insights and immediately see their risk flag and tier — across every branch visit, not just the most recent one.
🎓 Education
Use case: Student identification and service history
A university registrar's office uses Qtrac for in-person advising queues. Students enter their Student ID when joining.
Properties configured:
- Student ID (text) — mapped directly from the workflow question; used as the recognition identifier
- Program (dropdown: Undergraduate / Graduate / Part-Time) — set when a student checks in for advising
- Advising Flags (text) — a note like "Needs Financial Aid Review" added by an advisor via a rule when a specific service outcome is selected
On a student's third visit, even if they forget their student ID, Qtrac recognizes them by their phone number (also mapped). Their advising flag is already there — staff sees it the moment they check in.
🏛️ Government
Use case: Case tracking for returning residents
A DMV or social services office needs to track the status of ongoing cases. Residents check in by entering their driver's license number or case number.
Properties configured:
- Case Status (dropdown: Open / Pending Documentation / Resolved) — updated when a clerk marks a service outcome
- Preferred Language (dropdown: English / Spanish / French / Other) — set on first visit, persists for all future visits so staff is pre-informed
- Flagged for Supervisor Review (dropdown: Yes / No) — set when a specific escalation outcome is selected
Staff at the window can see the resident's case status and language preference before they even speak — without looking up a separate system.
🛍️ Retail
Use case: Loyalty and purchase tracking
A retail store uses Qtrac at the customer service desk. Customers enter their loyalty card number or phone number to join the queue.
Properties configured:
- Loyalty Tier (dropdown: Silver / Gold / Platinum) — updated when a purchase of a qualifying amount is recorded as a service outcome
- Last Purchase Date (text) — set to today's date when the outcome "Purchase Completed" is selected
- Return Customer Flag (dropdown: Yes / No) — automatically set after a customer's second visit
Associates handling returns or inquiries immediately see if a customer is Platinum tier — and can treat them accordingly before the conversation even starts.
🏥 Hospital / Healthcare
Use case: Patient risk and visit context
A hospital outpatient clinic uses Qtrac for check-in. Patients enter their date of birth or patient ID.
Properties configured:
- Patient Risk Level (dropdown: Standard / High / Critical) — set based on triage outcome
- Mobility Needs (dropdown: None / Wheelchair / Assistance Required) — set on first visit and retained for all future visits
- Preferred Contact Method (dropdown: Phone / SMS / Email) — set when a patient fills out a preference form
When a high-risk patient checks in, the clinical coordinator sees the flag immediately — no chart lookup needed. Mobility accommodations are already noted so staff can prepare before the patient reaches the desk.
Viewing Properties in Insights
In the Insights module, you can add Customer Property columns to any visit report. This lets you view a visit from any date and see the customer's current property values alongside it — useful for spotting patterns like "customers who abandoned 3+ times tend to be High Risk today."
The Baseline to Activate to Prove Framework
Before activation, measure your current rate of repeated questions per visit and associate handle time. After activation, use the Customer Properties dataset in Insights to show reduced repeat questions, faster handle times, and improved routing accuracy.
If you are interested of how to configure and use this please use the following articles:
How to Configure Customer Properties
How to Use Customer Properties in the Queue
How to use Insights with Customer Properties data
If you still have any questions please feel free to reach out to your assigned Cusotmer Success Representative or our Qtrac Support Team.
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Articles in this section
- Introduction to the Charts & Pivots Output Insights types
- Auto Call: Keeping Queues Moving Without Manual Intervention
- Service Guides: Standardizing Excellence at the Moment of Service
- Customer Properties: A Persistent Data Layer That Remembers Every Customer
- How to Join a Virtual Waiting Line
- How a Greeter Adds a Customer to a Virtual Queue by Qtrac
- How to Call a Customer from the Virtual Waitlist
- The Virtual Queue: Effective Use When Foot Traffic is Low
- Appointment Scheduling with Qtrac Virtual Queuing
- Digital Queuing: Helping Customers Without Mobile Devices.