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Customer segmentation

Customer segmentation is dividing a store's customers into groups by their behaviour or characteristics so that each group gets its own message, offer or bid.

How it works

A segment groups customers who should be treated alike, and it earns its place only when it changes the email, the offer or the bid. For a store, the usual splits come from behaviour: how recently a customer ordered, how often and how much. RFM segmentation is one method that combines the three. Customers can also be split by characteristics, such as location or the category they bought, or by stage: first order, repeat buyer, lapsed.

The store builds segments from its own order data, which Google Ads cannot read directly; a segment reaches Google Ads as an uploaded Customer Match list. Google Ads can mark such a list with a customer type, such as purchasers, high-value purchasers, disengaged purchasers or cart abandoners. The customer lifecycle goals in Google Ads rely on these types. RFM analysis for online stores walks through a spreadsheet method.

Example

Example store, not client data.

The tableware shop splits the 2,300 customers of the last 12 months by number of orders: 1,840 ordered once, 400 two or three times, 60 four times or more. It emails the 60 an early look at new collections. For ads, 60 is too few: a Customer Match file must hold at least 100 records, so the shop uploads all 460 repeat buyers as one list.

Not to be confused with

  • Custom label — segments products, not customers: the store groups products in its feed for Shopping and Performance Max campaigns.
  • Cohort analysis — groups customers by the month of their first order to follow each group over time. Segmentation groups them to treat them differently now.

Right and wrong readings

  • Wrong: “In-market and affinity segments in Google Ads are our customer segments.” Right: Google estimates those audience segments from people’s activity on Google products and other sites. The store’s own segments come from its orders and reach Google Ads as uploaded customer lists.

Sources