Are Your Ads Reaching the Right Audience at the Right Time?

Businesses spend millions on digital advertising, but without data-driven timing and geographic insights, many campaigns miss their mark. 40% of consumers prefer targeted ads over generic ones, yet many companies still rely on guesswork, leading to lower conversion rates and wasted ad spend.

Why External Data is Key to Smarter Ad Targeting

By analyzing historical campaign performance, consumer behavior, and website traffic, businesses can:

Optimize ad timing to reach audiences when they’re most likely to convert
Refine geographic targeting to ensure messaging aligns with local preferences
Improve conversion rates by delivering ads in high-engagement windows
Enhance customer experience with dynamic, personalized content

How It Works

🔹 Behavioral Insights – Analyzes website traffic, media exposure, and customer engagement to detect patterns
🔹 Predictive Targeting – Identifies when and where ads will perform best based on historical data
🔹 Dynamic Creative Optimization (DCO) – Customizes ads in real-time based on audience, context, and past performance

Real-World Impact: Smarter Targeting in Action

Red Roof Inn identified that 90,000 flight passengers are stranded daily due to weather cancellations. By leveraging third-party flight cancellation data, they launched mobile-targeted ads in affected areas, increasing revenue by 10%.

Turn Ad Spend Into Revenue with Smarter Targeting

Companies that leverage first-party behavioral data and enhance it with external insights gain a competitive edge in ad efficiency, engagement, and ROI. Don’t let your ad dollars go to waste—target smarter.

📩 Want to improve your ad targeting strategy? Let’s talk about how external data can maximize your campaign performance.

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Live Webinar

Is “Quality” Killing Your AI? Defining Data Fit for Strategic Success

February 18th, 2026 / 1:00 PM EST

Every data investment carries risk unless you know how to measure its “fit” for the mission. Many organizations assume that “high-quality” data is sufficient for AI and analytics, only to discover too late that data fit is the real determinant of success. In this live session from Blue Street Data’s Building with Better Data series, Andy Hannah and Malcolm Hawker unpack why data that works for BI can be dangerous for AI, leading to model failure, wasted spend, and lost trust. You’ll learn how to define, measure, and validate data fit so your models deliver reliable, business-aligned outcomes. Reserve your spot today!