Insights on AI and the Future of Marketing
Explore expert perspectives, practical strategies, and real-world use cases on AI-powered marketing, customer engagement, Salesforce Marketing Cloud, and audience personalization.
How AI Is Changing the Role of CRM Teams
AI is shifting CRM teams from writing every query by hand to defining audiences and reviewing results. Here is what moves, what stays, and what to learn next.
How Non-English Teams Struggle with SFMC SQL
SFMC's interface speaks many languages, but SQL does not. Here is where non-English teams lose time and how to reduce the dependency on a few specialists.
Top SFMC Segmentation Approaches in 2026
Filters, SQL, engagement scores, Data Cloud and AI: how the main SFMC segmentation approaches compare in 2026, and how to pick the right one for each audience.
How French Marketing Teams Use AI in SFMC
French-speaking teams work in an English platform. Here is where they lose time in SFMC and how conversational AI turns French requests into reviewable SQL.
The Death of Manual Segmentation
SFMC segmentation still runs on SQL and data views. See how Salesforce's own no-code segment canvas and Einstein tools are changing who can build an audience.
How QAiry Handles Data Views
SFMC data views hold your engagement history but only answer SQL. Here is what they retain, where queries go wrong, and how QAiry reads that layer.
Why Enterprise CRM Teams Need Faster Audience Creation
Slow audience builds do not just delay one campaign in SFMC. At enterprise scale they set the calendar, narrow testing, and burn out your SQL specialists.
What's New in QAiry 3.1
Smarter metadata understanding, four types of data extension, Manual Edit as a builder, SQL as an entry point, and Waterfall refreshes. What shipped in 3.1.
Alternatives to Manual SQL Segmentation
Five ways to build SFMC audiences without hand-writing SQL, what each approach is genuinely good at, and where each one runs out of room.
