How to balance data control and real-time personalization
Warehouse native CDPs promise cleaner data, but marketers need new strategies to deliver fast, relevant experiences.
Warehouse native CDPs promise cleaner data, but marketers need new strategies to deliver fast, relevant experiences.
Effective measurement depends on connecting signals across MMM, attribution, and incrementality instead of forcing a single source of truth.
As referral data disappears, this framework helps you measure marketing momentum without relying on perfect tracking.
AI 1.0 saved time. AI 2.0 makes money. The marketers who win will be Positionless.
Google is giving retailers new AI visibility metrics in Merchant Center, offering a closer look at how products surface in conversational shopping results.
AI answers often surface only a handful of vendors. Learn how to improve your B2B brand’s visibility and shape how AI systems frame it.
Marketing artificial intelligence (AI)
Competitor analysis goes beyond dashboards and weekly reports. Here’s how to use AI to think ahead instead of catching up.
47% of B2B companies reduced marketing roles due to AI, often by quietly eliminating backfills rather than announcing layoffs.
The most valuable email marketers know how to apply AI across automation, personalization, analytics, testing, and customer journeys.
A new API report card reveals major gaps in the systems marketers depend on for automation and AI workflows.
Marketing artificial intelligence (AI)
Conversational AI is reshaping advertising through real-time recommendations, dynamic creative, and autonomous optimization.
There was an opportunity for marketing teams to harness AI and change the way they work, and Ryan Warren, chief CRM officer at Razorfish, says many missed it.
Most marketing activity creates attention. The campaigns that earn trust and action are built on genuine customer understanding.
Organizations say they value feedback, but employees and customers notice when leadership listens without taking action.
New guidance from IAB Tech Lab aims to help publishers and content owners decide how to manage AI crawlers, bots, and other non-human traffic.
What you need to know about marketing on Reddit. Updated with details on the wew features for app advertisers.
Automation dominates modern B2B selling, but the deals that matter most still close through human relationships.
AI can speed up every marketing team. The bigger challenge is avoiding commoditization when everyone uses the same tools.
Companies may be avoiding expensive platform migrations, but they're creating a growing integration and complexity problem.
Companies that organize and structure metadata have a major edge in AI-powered search and personalization.
Mailchimp is not shutting down, but Intuit’s latest comments suggest the platform is entering a very different phase.
New research finds consumers accept AI in marketing when it adds value, but many reject ads that feel generic, intrusive, or emotionally hollow.
Consumers may choose brands emotionally, but AI agents will evaluate pricing, service, delivery, and loyalty value.
74% of enterprises that deployed AI customer agents have rolled them back after governance failures damaged CX and trust.
Experimenting with AI now gives you the advantage when everyone else tries to catch up.
Marketing artificial intelligence (AI)
AI mandates without structure are creating workslop across marketing teams. Here’s how to build a smarter adoption strategy.
The cross-channel ad ops problem is real and mostly ignored. Here's what it's costing performance marketers — and what's actually changing.
Consumers are caught in a battle between volume and relevance when it comes to messages, and AI can either help or hurt the problem.
Gartner research shows buyers want AI speed, but they still turn to humans for confidence and validation.
As AI changes discovery, brands need clearer messaging, stronger credibility signals, and content built for influence, not just visibility.
Campaign-based execution created disconnected teams, tools, and data. AI is enabling a more unified operating model.
New global research data reveals the tech gap quietly costing teams speed, revenue, and competitive ground.
Martech stacks have outgrown project-based management. Marketing teams need stronger ownership, governance, and service models.
Vibe coding can replace SaaS tools fast, but risks in security, integration and maintenance can quickly outweigh the savings.
AI recommendation engines rely on reviews, comparisons, and customer signals to decide which brands to surface and trust.
Google Analytics just made it easier to see how much traffic AI assistants are sending to your website.
Data was nice, but high-value, proprietary data you can use to train AI agents is even better.
AI tools improved how specialists work, but most organizations still operate through the same approvals, handoffs, and bottlenecks.
As AI agents start shortlisting vendors, structured, machine-readable content will determine which brands even get considered.
More than soundbites, these 10 quotes reflect the the real-world pressures facing marketing leaders today.