Connect's contact search lets you filter your database by contact details, tags, transactions, visits, campaign engagement, and form submissions. You can combine multiple criteria, preview results, and save any search as a reusable segment for campaigns and automations.
This article walks through how to run a search, what every field on each tab means, how operators and match logic work, and gives you example searches to try.
Table of contents
- How to run a search
- Search field categories
- Operators explained
- Understanding match logic
- Using purchase and integration filters
- Saving a search as a segment
- Example searches to try
- Best practices
- Troubleshooting
How to run a search
- Go to Contacts
- Click Search Your Contacts
- Pick a field to search by (e.g. Tags, Interested In, Number of visits, Purchase date)
- Choose an operator and enter a value
- Add more criteria as needed using + Add Another Search Field
- Click Search to view results
Search field categories
Basic Search — contact attributes
The contact's profile data and subscription status, held directly on the contact record.
| Field | What it means |
|---|---|
| First name / Surname / E-mail / Mobile | Standard contact details |
| Date of Birth / Age / Gender | Demographics |
| Tags | Custom labels manually applied to contacts (e.g. "VIP", "Regular") |
| Club & Social Membership | Membership status with a club or society linked to your venue |
| Email subscription / SMS subscription | Whether the contact is currently subscribed (true or false) |
| Email opt-out date / SMS opt-out date | When they unsubscribed (date filter) |
| Created / Updated | When the contact record was added or last modified in Connect |
| Source | How the contact entered Connect (POS import, booking, signup form, manual upload, etc.) |
Purchase — transaction history from POS
Filters based on what the contact has bought.
| Field | What it means |
|---|---|
| Purchase location | Which venue or site the transaction happened at |
| Reference | Transaction reference number (POS-generated) |
| Purchase amount | Dollar value of an individual transaction |
| No. of transactions | Total count of transactions for the contact |
| All time purchase total | Lifetime spend across all transactions |
| Single purchase total | Dollar value of one specific transaction |
| Transaction date | When a transaction happened (date filter) |
| First transaction date / Last transaction date | Earliest or most recent transaction date |
| Item description | Name of a line item purchased (e.g. "Margherita Pizza") |
| Sub-item description | A modifier or variant on an item (e.g. "Extra cheese") |
| Item quantity | Total quantity of a specific item bought across all transactions |
| Item quantity in single transaction | Quantity of an item in one transaction |
| Has transaction | Whether the contact has ever transacted (true or false) |
| Transaction category | POS-defined category (e.g. "Food", "Beverage") |
| Transaction item category | Category at the line item level |
| Purchase event | Transaction linked to a specific event |
| Transaction source | Where the transaction was captured (POS, online order, etc.) |
Visits — bookings and venue visits
Filters based on bookings and visits, separate from purchases.
| Field | What it means |
|---|---|
| Visit location | Which venue was visited |
| Booking date | When the booking is or was for |
| Booking status | Confirmed, cancelled, no-show, etc. |
| Visit creation date | When the booking record was created |
| Number of visits | Total visit count |
| Date of first visit / Date of last visit | Earliest or most recent visit date |
| Feedback score | Rating left after the visit |
| Pax | Party size (number of guests) |
| Visit event | Visit linked to a specific event |
| Visit type | Walk-in, booking, or other |
| Visit description | Notes or description of the visit |
| Visit source | Booking platform or capture source (e.g. SevenRooms, ResDiary, walk-in) |
Campaign — past campaign engagement
Filters based on how the contact interacted with previous Connect campaigns.
| Field | What it means |
|---|---|
| Sent / Not sent | Was sent, or wasn't sent, a particular campaign |
| Opted out / Did not opt out | Unsubscribed via that campaign, or didn't |
| Opened / Did not open | Opened the email (tracked via tracking pixel) |
| Bounced / Did not bounce | The email bounced — the recipient mailbox rejected it (hard or soft bounce) |
| Clicked a link / Did not click a link | Clicked any tracked link in the email or SMS |
ℹ️ Note — "Bounced" is not the same as "landed in spam". Bounced means the receiving mail server rejected the message (invalid address, mailbox full, etc.). Spam folder placement counts as delivered and won't show up under Bounced.
Form Submission — form data
Filters based on Connect signup and feedback forms.
| Field | What it means |
|---|---|
| Form name | Which form was submitted |
| Submission date | When it was submitted |
Operators explained
Once you select a field, choose an operator to define how Connect matches values:
| Operator | What it does | Example |
|---|---|---|
| Equals | Exact match only | "First Name equals John" matches John but not Johnny |
| Does not equal | Excludes exact matches | "State does not equal VIC" returns everyone outside VIC |
| Contains | Partial match | "First Name contains John" matches John, Johnny, Johnathan |
| Is empty | No value set for that field | "Date of Birth is empty" finds contacts with no DOB |
| Is not empty | Has any value for that field | "Email is not empty" finds all contacts with an email |
| Greater than / Less than | Numeric or date comparisons | "Total spend greater than 300" |
| Within last X days | Relative date range | "Last visit date within last 30 days" |
Different field types (text, number, date, dropdown, etc.) will show different operator options.
Understanding match logic
When you combine multiple search criteria, the match mode controls how they work together:
Match all conditions (AND) — A contact must meet every criterion to appear in results. Use this when you want to narrow down to a very specific group.
Match one or more conditions (OR) — A contact only needs to meet at least one criterion. Use this when you want a broader audience.
⚠️ Common mistake: If your results look off, check your match mode. Using OR when you meant AND (or vice versa) is one of the most common search issues. Also watch for stacking "equals" on the same field in AND mode — a contact can't have a first name that equals both "John" AND "Jane" at the same time.
Using purchase and integration filters
For contacts created through integrations (e.g. POS, WiFi, bookings), some data lives on transactions rather than on the contact record itself.
To target contacts by venue, location, or recent spend, switch to the Purchase tab and use filters like:
- Purchase Location equals [Venue name]
- Transaction date within last X days
- Total spend greater than [amount]
This is especially useful for multi-venue organisations that need to segment by location.
Saving a search as a segment
Any search can be saved and reused as a segment — a dynamic, always-up-to-date list of contacts that match your criteria.
- Run your search
- Click Save This Segment
- Give it a clear, descriptive name
- Click Save
Once saved, you can use the segment in campaigns, automations, and reports without rebuilding the search each time.
See: Segments for more detail on creating, naming, and using segments.
Example searches to try
Here are some practical searches to get you started:
New customers
- Number of visits equals 1
- Created date within last 30 days
- Match mode: AND
Re-engagement
- Last visit date greater than 60 days ago
- Subscribed equals true
- Match mode: AND
Venue-specific
- Purchase Location equals [Venue A]
- Transaction date within last 90 days
- Match mode: AND
VIPs / High spenders
- Total spend greater than 300
- Number of visits greater than 5
- Match mode: AND
Birthday campaign
- Date of Birth month equals current month
- Subscribed equals true
- Match mode: AND
Best practices
- Start simple — begin with one or two criteria, then refine by adding more
- Name segments clearly so your whole team can find and reuse them (e.g. "Lapsed 60D – Email" not "Segment 1")
- Search for unengaged contacts regularly — suppress or clean contacts who haven't opened or clicked in 180+ days to protect your email reputation
- Avoid overly complex searches — too many criteria can slow performance. If needed, split into smaller, focused segments instead
- Use purchase filters for venue targeting — don't rely on contact fields alone if the data comes from transactions