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 modelling, you can make sense of the data you have and solve unknowns — all while maintaining accurate and effective performance measurement. Discover three reasons why conversion modelling can help you meet people’s privacy expectations and drive growth.
Find more insights and videos from our How to Think About series and on the Think with Google YouTube channel.
[upbeat bass line underscores intro and continues throughout video]
Barbara Piermont: Are you trying to figure out the best way to analyse 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 analyse 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 optimise 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 optimise 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
Top digital marketing trends and predictions for 2023
How to build a successful measurement plan for 2023
Case StudyCase Study
How automation helped Game deliver on its price-beat promise
C-suite chemistry: How CMOs and CFOs can partner to drive business success
3 early holiday shopping trends for the 2021 festive season
Today’s African consumer and how they’re shaping the future
New trend: Long attention spans for long-form videos
Pricing pain: How brands can adapt amidst inflation