In this week’s digital news to watch, Google is pushing marketers toward a unified Data Manager API, replacing legacy pipelines for audience and conversion data and requiring migration away from older integrations, while a separate Search Console bug has recently been fixed, meaning reported impressions may drop even though actual performance remains unchanged.
AI-driven search is reducing the effectiveness of traditional keyword targeting in favour of broader intent and audience signals, signalling a shift in how campaigns need to be structured. On social platforms, Meta has improved ad delivery on Instagram through its Adaptive Ranking Model, which uses richer real-time engagement signals to boost relevance and has already driven gains in clicks and conversions. Meanwhile, growing consumer concern suggests that introducing ads into AI search experiences could undermine trust, highlighting a potential challenge as platforms look to monetise these emerging environments.
Google unifies audience & conversion data with its new Data Manager API
Google’s Data Manager API, launched December 2025, consolidates first-party data ingestion by replacing separate pipelines for Customer Match, conversions, and DV360 audiences into a single endpoint. From 1 April 2026, Customer Match uploads via the legacy Google Ads API stopped working entirely. New developers must now use the Data Manager API, with existing users facing a March 2027 migration deadline.
The API offers privacy features like confidential matching, supports REST and gRPC, and includes a diagnostics UI. Early adopter Treasure Data reported 80% less engineering effort. Google plans full feature parity across its advertising products by end of 2026.
Meta boosts ad relevance with new Adaptive Ranking Model
Meta has rolled out an improved ad serving process for Instagram via a new Adaptive Ranking Model. The updated model is able to process more engagement elements for each user in real time, while also reducing system load to ensure optimised delivery of more relevant promotions.
Meta outlined the update on its engineering blog, using complex technical language to say that Instagram users are now seeing more relevant ads.
In essence, Meta is using large-scale processing, the same as it now uses for its AI models, to improve ad display and ensure more individual engagement factors are measured when deciding which ads to show each user.
Since launching on Instagram in Q4 2025, the Adaptive Ranking Model has delivered a 3% increase in ad conversions and a 5% increase in ad click through rate for targeted users. This should drive better return on ad spend.
