How Customer Match works
You take a list of customers you already have, hash the identifiers so the raw data is never exposed, and upload it to the platform. The platform matches those hashes to its own logged-in users and builds an audience from the overlap. You can then show ads to that audience, exclude it, or use it as a seed for lookalike modelling. Because the input is people who chose to do business with you, a Customer Match audience is among the highest-quality first-party assets an account can activate.
The three jobs it does
Customer Match earns its keep in three ways. As targeting, it reaches existing customers for retention, upsell, or win-back. As exclusion, it stops prospecting budget from paying to acquire people who already bought, which is one of the fastest ways to cut waste. As a seed, it gives lookalike and similar-audience models a clean, high-intent starting set. The exclusion use is the one most often skipped, and it is frequently the highest-return change available on a spending account.
Match rates and list hygiene
Not every record on your list will match, because a customer must be a recognisable platform user for the hash to connect. Bigger, cleaner, better-formatted lists match at higher rates, and stale or malformed data quietly shrinks the audience. Consent is a hard requirement, since you are activating personal data, and the list should reflect people who agreed to marketing. Keeping lists fresh and correctly formatted is unglamorous work, but it is what decides whether Customer Match reaches a useful share of your customers.
How iClick uses Customer Match
iClick activates Customer Match on all three fronts, but treats exclusion as the first win, suppressing existing customers from prospecting so acquisition budget is not spent re-buying people who already converted. Clean lists seed better lookalikes and power retention and win-back campaigns, with consent and hashing handled as non-negotiable. The recurring finding is that most accounts own a strong customer list that is never uploaded, leaving free efficiency on the table.
