Across the marketing funnel, AI in Martech is moving from promise to process. In Salesforce’s ninth State of Marketing study, marketers rank generating content, analyzing performance and driving best offers as the most common AI tools for marketing use cases.
These are clear signs that AI and the CMO are already tightly connected, with AI being woven into day-to-day execution – not parked in innovation labs.
For CMOs and marketing leaders looking for practical tech solutions for marketing leaders and clear examples of how to use AI for marketing, here are three ways AI is becoming an unmissable part of the modern marketing team.
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AI-Powered Personalization: Turning Data into Revenue Growth
Why it matters now Personalization isn’t a nice-to-have; it impacts revenue. In a recent HubSpot survey, 44% of marketers said offering customers a personalized experience “increased sales significantly.” That’s a striking proof point for CMOs trying to justify deeper investment in data, decisioning and creative ops.
How AI is optimizing the work Generative and predictive models help teams scale what used to be hand-built. AI-powered chatbots can resolve queries with brand-safe answers, while still delivering a unique personal experience.
Meanwhile enterprise landing pages can now automatically adapt to context (target source, segment, behavior) without manual production of hundreds of variants.
Use case Vervoe, an HCM skills platform, used Twilio Segment to personalize ad copy to a target’s specific job role and objectives. The company reported a 2x - 5x average lift in campaign conversions. And a 25% reduction in customer acquisition cost. All from switching to dynamic, role-specific messages.
Predictive Analytics: Smarter Insights, Stronger ROI
Why it matters now Salesforce’s 2024 research tied the rise of AI in marketing directly to two families of use cases: generative AI and predictive AI, noting that over half (54%) of AI-using marketers apply predictive tools today.
For CMOs that don’t want to be left behind, they should be considering how AI and analytics can identify moving trends and changing attitudes. Further down the buyer journey, analytics can also inform leaders about churn risk – an upgrade on legacy dashboards.
How AI is optimizing the work Modern analytics platforms surface patterns no human eye will catch – and do it at speed. For example, it can scan to detect sentiment shifts on social media, or even in conversations with customers.
Analytics can also identify hidden links between customers, helping teams to then refine segmentation. This also helps to schedule interventions with at-risk customers. High-risk customers can be flagged and routed towards ‘save plays.’
Case study NinjaCat adopted 6sense AI solutions to sharpen targeting for its “Big Data Day” campaign. By analyzing the relevant LinkedIn community, the team engaged 397 high-value accounts - a 422% increase on prior campaigns. All while cutting cost-per-click by 48%. That’s the practical value of predictive account selection meeting precise media activation.