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Don’t Let Your Digital Advertising Performance Suffer in a World Without Cookies

October 26, 2020

conversion modeling on whiteboard
At Noble Studios, we’ve got teams dedicated to digital advertising. Their bread and butter? Reaching customers wherever they are at just the right time, with personally relevant messages that connect to convert.

Understanding the full performance of digital advertising is critical, but not always easy. Why? Because mapping the buyer’s journey online is not unlike finding a needle in a haystack.

As Think With Google details, paths to purchase often include people switching between browsers and devices before making the final purchase. The path to purchase isn’t always clear, so online advertisers have relied on cookies to better determine user information after people have clicked on an ad. Cookies have historically been a way for digital marketers to better understand ad performance.

However, increased user privacy regulations, strengthened data collection guidelines and recent cookie restrictions have changed the way in which digital advertisers are able to look at performance metrics. With increased regulations and larger blind spots in terms of determining successful conversions when tracking media measurement, it’s becoming harder to determine if a conversion occurred or not.

This doesn’t mean that tracking performance is impossible, though. It just means it’s going to look different, and at Noble, we’re on top of it. When tracking direct measurement might look a little difficult, we’re on top of measuring performance that is privacy-friendly and an accurate depiction of your customer’s behavior.

What is Accurate Measurement and Why is it Important?

When it comes to accurate consumer privacy regulations and performance measurement, have no fear: conversion modeling and machine learning are here to help. Say you’re unable to accurately attribute conversions to the customers who interacted with an ad because cookies aren’t present, and you cannot easily determine cross-device measurements, it’s crucial to create a modeling technique.

Google’s approach is to use a modeling foundation that allows measurable data and historical patterns to feed into algorithms. This helps to fill in gaps in the buyer’s journey while informing and validating measurement.

Not only is conversion modeling important when deciphering the complete privacy-centric depiction of customer behavior and trends, but it’s also important to analyze the performance of your business, and your advertisements, as a whole. It’s also about learning, optimizing and improving your ad experience.

Fill in the Gaps, Leverage Machine Learning

Modeling those tricky to navigate measurement gaps starts with a solid online infrastructure first. Think With Google recommends utilizing tools like Google Tag Manager and global site tag to tag for conversion measurement and ensure successful measurement within the Google platform. A solid foundation is needed first to capture conversion data and build a reliable modeling strategy. Luckily, our team can help!

Additionally, leveraging automation expertise and machine learning can help ensure you are observing and analyzing current signals like date and time, device and even conversion type. As Think With Google states, “richness and reach of data remain must-haves for reliable modeling.” Scale is a top priority when evaluating measurements for an accurate, comprehensive view across devices, browsers, platforms and operating systems.

Better Measurement with Noble Studios

Are you interested in capturing the most comprehensive view of your business performance through data-driven performance? Our team can help you learn about some steps to ensure you’ve got a solid foundation for conversion modeling.

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