The engineering behind Leadzai’s Siinda Innovation Award

Leadzai’s award-winning Location Matcher automatically matches campaign locations across Google, Meta, and Microsoft, eliminating targeting errors for new campaigns. This is the story behind the AI feature that won the Siinda Innovation Award.

Location Matcher is an AI feature that automatically maps campaign locations across Google, Meta and Microsoft from a single Google Maps input. Built to eliminate location targeting errors across advertising networks, it was recognised with the 2026 Siinda Innovation Award in the Location Platforms and Lead Generation category. Before its launch, 2% of campaigns served clicks outside their intended target area, affecting €2,460 in monthly ad spend. Since deployment, targeting errors for new campaigns have dropped to zero, and the feature now powers 100% of new campaigns created on the platform.

The challenge of multi-network targeting

Running a local campaign across Google, Meta, and Microsoft sounds simple. You pick a location. You publish.

Each advertising platform handles location data differently. Google Ads, Meta, and Microsoft Advertising all use their own location structures and naming conventions, which don’t always align. As a result, translating locations between platforms was prone to errors, leading to situations where campaigns were unintentionally targeted outside the intended area.

‍While users selected a specific location within the platform, the corresponding campaigns could be configured with a different location in the advertising networks, making accurate geographic targeting difficult to guarantee.

For agencies managing dozens of SMB campaigns across multiple networks, this created a silent operational problem. While slight differences in location targeting between advertising networks are expected, the real issue arose when campaigns were configured with locations that fell completely outside the advertiser’s intended target area.

As the platform displayed only the location originally selected by the user, these discrepancies were not immediately visible during day-to-day campaign management. In many cases, the issue only surfaced after clients reported receiving clicks from locations they had never intended to target.

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