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The customers table with its filter and grouping controls

Customers

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customers
Choose between a tag and an attribute first, because that decision is most of the work. Tags collect customers into groups; attributes record facts about one customer. Build the segment out of something the customers table can find, which rules out anything living in a free-text note. A segment is only useful if you can act on it: email it, price for it, report on it.

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Prerequisites

Required permissions: customers:customer in view and manage. All four system roles hold every operation on it. Creating attributes and tags is managed in Settings. See Attributes & tags.
Decide before you start:
  • Is this membership or a fact? Ski club member is membership, so a tag. Licence class B is a fact, so an attribute. See the first step.
  • Who maintains it? A tag applied by hand needs someone to keep applying it. An attribute collected at checkout maintains itself.

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The walkthrough

1

Choose tags or attributes

Pick by whether you would ever want to know the value. If yes, use an attribute; if the only question is in-or-out, a tag is simpler.Both are filterable columns in the customers table, so either can drive a segment. Full detail on the distinction is in Customer groups.
2

Build a group with tags

Apply tags on a customer’s General tab, on the Tags card. The tag set is shared across your customers, so a tag applied here is available everywhere and appears in the table’s Tags column.Keep the taxonomy small and agree the list before you scale it. Tags proliferate quietly: three people inventing vip, VIP and v.i.p. produce three groups where you wanted one, and nothing merges them for you.Use tags to restrict what a group can see, since a listing can be limited to customer tags. That is how a members-only or trade-only offer is built. See Create and publish a listing.
3

Record facts with attributes

Create the attribute once, then set it per customer by hand on the Attributes tab, or automatically by collecting it at checkout.Prefer collected attributes, because they maintain themselves as customers order. An attribute nobody fills is a column of blanks, which is worse than not having it.Choose the type carefully, because it decides how useful filtering is. A select attribute filters to exact choices, a number by range, and a date by period. A text attribute filters by substring, which is the weakest of the four.
4

Filter the table down to the segment

Combine filters to isolate the group. Anything in the table is fair game: tags, attributes, Marketing consent, Customer type, Language, Created, and the billing and shipping address columns.Some combinations that earn their keep:
  • Marketing consent is true, plus a tag, for the segment you are allowed to email.
  • Customer type is Business, plus a Tax / VAT ID that is set, for companies you can invoice.
  • Language, for a campaign that only exists in one language.
  • Created in a period, for customers acquired by a specific push.
Use Group by on a tag or a select attribute instead, and the table splits into every segment at once. That is the faster read when you are exploring.
5

Save the segment as a view

Save the filter as a view, so the segment is a tab rather than a reconstruction. Views appear on the table’s tab row, and the panel at the right of that row searches, reorders and hides them.Save the ones you use routinely, so consented Finnish-speaking members stops being a query somebody remembers and becomes a thing anyone on the team can open. See Tables.Reordering and hiding tabs is per-user and per-browser, so your arrangement is yours. The views themselves are shared.
6

Use the segment

Take a saved view to one of three places:
  • Export it, since the export respects your filters, sorts, groupings and visible columns. That is how a segment reaches an email tool. See Export customers.
  • Restrict a listing to it via tags, for members-only or trade pricing.
  • Read it, for a straightforward count of how big a group actually is before you plan around it.

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How do I know it worked?

  • The filter returns the customers you expected, and a spot-check of two or three confirms they belong.
  • The count is plausible. A segment of three when you expected three hundred usually means the attribute is unfilled rather than the segment being small.
  • The view is saved and opens to the same set tomorrow.
  • The export contains the columns you need, not only the ones the table happened to be showing.

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Troubleshooting / common pitfalls

Usually an unfilled attribute. Filtering on an attribute only finds customers who have a value for it, and an attribute added last month is blank on everyone who ordered before that.Count how many customers have the attribute set at all before trusting a filter on it. An attribute collected at checkout fills over time, but it never backfills.
Nothing deduplicates tags, and there is no merge.Pick the survivor, re-tag the affected customers, and remove the others. Then agree who may create tags, because this is a taxonomy problem rather than a tooling one. See Customer groups.
It is not a tag or an attribute. Free text on a profile, or an answer that landed on an order line, is not a customer column.Make it an attribute and collect it going forward. See Collect customer data at checkout.
Marketing consent is a column, and it is the flag that says whether you may.Make consent part of every marketing segment rather than a check you do afterwards. See Export customers.
A saved view does. It is a filter, so it re-resolves every time it opens and picks up customers who newly match. A tag does not: it is applied per customer and stays until someone changes it.Express the group as a filter on attributes rather than as a tag somebody has to maintain, where its definition is a rule rather than a decision.

Export customers

Getting a segment into an email tool.

Collect data at checkout

Filling attributes without anyone typing.

Customer groups

Tags, attributes, and the taxonomy question.

Tables

Filters, grouping and saved views in full.