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.
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.
Why Marketing Ops Teams Are Adopting AI
SFMC audience requests pile up because they all route through SQL. Why marketing ops teams are adopting AI, and what it actually changes day to day.
QAiry vs Manual SQL: Building Audiences in SFMC
Hand written SQL or conversational AI for SFMC audiences? A candid look at where each approach wins and where the real time savings come from.
Best Ways to Build Audiences in Salesforce Marketing Cloud
Filtered data extensions, SQL queries, Audience Builder, or Data Cloud? A practical look at the four ways to build an audience in SFMC, and when each one breaks.
How Non-Technical Marketers Can Build SFMC Audiences
A practical look at what marketers can build alone in SFMC, where the no-code tools stop, and how to describe an audience so it holds up in production.
