YouTube is a great platform for generating brand awareness and Google is continuously working on new types of audience targeting for the platform. In order to reach an audience that is in the process of making a purchase Google released “Custom Intent Audiences”. Custom Intent Audiences allow us to show ads on YouTube to people that have performed particular searches on Google. For example, if you are a health care company you could show video ads on YouTube to people that have previously searched for “sports physicals”.
Custom audiences can be very useful and in order to understand when to use a particular audience you have to compare the options against your marketing objectives. In this article we focus on the difference between In Market Audiences and Custom Intent Audiences but there are other options:
- Demographic Audiences
- Custom Affinity
- Life Events
- Remarketing Lists
- Similar Audiences
- Combined Lists (AND/OR relationships between custom audiences)
In Market Audiences & Custom Intent Audiences
Custom Intent Audiences are similar to Google’s In-Market audiences but there are a few differences. According to Google In-Market audiences target people that are in the research phase. With In-Market audiences we can target a much broader audience and generate more awareness and the options for targeting are limited to more generic categories. We also can’t tell Google what specific keywords we want to target. Shown below are some examples of In-Market audiences:
Custom Intent Audiences are similar to In-Market Audiences but Google will use our keyword data to build an audience more likely to complete a purchase. We have tested these audiences and found that we do need to carefully manage the placements of the ads and add exclusions when necessary.
How Are Custom Intent Audiences Built?
We emailed Google to ask them exactly how their algorithms build the Custom Intent Audiences and they in addition to doing the search they also have to show intent to purchase.
Quote from Our Google Rep:
“Custom Intent is like an in-market audience that has the intent and is in the market to purchase, sign up, fill out a form, etc. Just because they are researching or seem interested, doesn’t mean they have intent to do anything just yet.”
Google will not reveal exactly how their algorithms determine that someone searching a particular keyword is more likely to fill out a form or take action. They do claim to be using machine learning to help build these audiences so the only way to determine if it is useful or not is to run experiments for your business and measure the results.
Machine learning algorithms can be helpful but they still have to be carefully watched and managed. We have found that managing the placements is necessary in order to get good results.
The list of targeting options continues to grow on all digital ad platforms and what type of targeting we choose depends on your campaign objectives. Whenever a new targeting option is available it is important to test it and compare the performance against your objectives. We have found that there needs to be a careful balance between human management and machines to make campaigns perform for your business.
Sean periodically teaches as an adjunct professor on the topic of search engines and search marketing at MSU and is a member of their computer science advisory board. He completed coursework for his PhD in machine learning at MSU. He was the founder and publisher of SEMJ.org. Sean holds four engineering patents, has a B.S. in physics from the University of Washington in Seattle, and a master’s in electrical engineering from Washington State University. As president and director at metric ppc, Inc. he focuses on search marketing, internet research, and consults for large companies.