How conversion modeling helps you measure what matters
Share this page
How conversion modeling helps you measure what mattersFebruary 2023
When it comes to ad campaign performance analysis, you don’t have to settle for data gaps. With conversion modeling, you can make sense of the data you have and solve unknowns — all while maintaining accurate and effective performance measurement. Learn from Barbara Piermont, ads privacy director of go-to-market strategy for Americas at Google, as she shares three reasons why conversion modeling can help you meet people’s privacy expectations and drive growth.
[upbeat bass line underscores intro and continues throughout video]
Barbara Piermont: Are you trying to figure out the best way to analyze ad performance while maintaining a high standard of privacy? Conversion modeling can help get that done.
Marketers used to be able to understand every step of the customer journey, from click to purchase. But measurement isn’t as straightforward anymore, due to shifts in people’s expectations for privacy, global regulations, and tech platform standards. That said, you don’t have to settle for gaps in your data.
Conversion modeling helps you make sense of the data you have to solve for unknowns in the customer journey and maintain the accuracy of your measurement.
So let’s dig in on how conversion modeling can help. Simply put, conversion modeling helps you gain a more accurate and complete picture of your ad performance.
Eighty-five percent of digital media professionals say that the loss of accurate measurement is one of their top three challenges. And that’s because observable data that makes your ads more relevant is limited. It could be due to, for example, people moving across devices or using different browsers.
This is where conversion modeling can help. It uses machine learning to analyze various trends and signals, including your first-party data, to predict outcomes that would have otherwise gone unmeasured.
Thanks to the insights you gain from conversion modeling, you can also optimize your campaigns more effectively. These insights act as signals for tools like Smart Bidding, enabling you to learn who your most valuable customers are so you can reach more relevant audiences and drive better results.
Conversion modeling ensures that your measurement remains privacy safe. It works by filling in gaps that come from people’s varying consent choices with machine learning insights. This way, you can continue to respect people’s privacy while still gathering the insights you need to grow.
Eighty percent of advertisers are using or considering using machine learning to help with measurement in a privacy safe world. It gives marketers like you the opportunity to meet people’s privacy expectations and drive growth.
So to review: Conversion modeling helps you gain a more accurate picture of your ad performance. It helps you optimize your campaign more effectively, and it helps you maintain privacy-safe measurement. The great news is that conversion modeling is already built into many measurement solutions.
By adding these tools to your toolkit today, you’ll be working with the most accurate data, so you stay ready for whatever’s coming tomorrow.
For more insights to help move your business forward, subscribe to Think with Google’s YouTube channel. And definitely hit that notification bell so you’re up on our latest content. Thanks for watching.
Others are viewing
Marketers who view this are also viewing
How conversion modeling improves your marketing with new sources of measurement data
Customer journey mapping: The path to loyalty
How AI is helping marketers
Customers want control over their data — and won’t hesitate to switch brands to get it
How to create a privacy strategy that builds brand trustWatch now
Why CPG brands need an end-to-end measurement strategy in today’s uncertain market
Driving growth in a changing privacy landscape: The digital marketing playbook
3 ways to multiply business results with Google AI-powered solutions and strategiesWatch now