
Data-Driven Marketing: What It Is, Why It's Crucial Now, and How to Get Started
Discover how data-driven marketing boosts personalization, decision-making, and ROI with practical tips to get started. Read more.
Data plays an essential role in successful marketing campaigns. Without it, customer wants and online interactions are unknown. Businesses collect data but it is often imperfect and scattered, creating identity gaps. Marketers must close customer identity gaps to provide relevant, engaging experiences and propel their brands forward.
Identity gaps occur when businesses lack understanding of visitors identities and behaviors. Without a complete understanding, personalization is limited and customer experience is poor which leads to revenue loss. Common identity gaps are anonymous visitors, cross-domain roadblocks, data timeout, and missing data.
By capturing data across channels and devices and connecting it to a unified identity graph, marketers can analyze customer data in real-time and optimize the customer experience. Closing identity gaps leads to better targeting, segmentation, messaging, and brand-building, ultimately leading to better engagement and business success.
How Marketers Can Use Identity Graphs to Understand Their Customers Better
Don't worry ... it's FREE!
Discover how data-driven marketing boosts personalization, decision-making, and ROI with practical tips to get started. Read more.
Measurement is evolving fast. See how lessons from mobile ad measurement are helping define signal-agnostic, media-neutral, and privacy-first measurement framework for today's evolving ecosystem. Read more.
Data clean rooms have revolutionized how organizations collaborate on data while preserving privacy. Learn how this technology works, enhancing data security and fostering privacy-compliant partnerships. Read more.
Inaccurate marketing data wastes budgets and weakens campaigns. Discover how data accuracy enhances targeting and performance. Read more.
Discover how B2B SaaS marketers can maximize ROAS by relying on usage to predict lifetime value (LTV) and avoid the cost-per-acquisition (CPA) trap. Read more.
What's preventing enterprise marketing teams from realizing the full potential of their data analytics? How sophisticated are marketers' current approaches?