Late last year (2019) in-market audiences was introduced with both Google and Bing (Google Ads somewhat ugly cousin) rolling out in-market audiences for their search platforms after being available on the google Display Network since 2014.
In-market audiences allow you restrict the type of audience your Display and Search ads are shown to with a click of the button. You can define your new audience by their online behavior, giving you the ability to only show your ads to those Google considers Business Professionals or users who have recently been searching for similar products/services.
These new tools/audiences, are a hugely valuable feature for these two Search goliaths and you probably think everyone should switch these audiences on buuuut before doing so, you may need to consider the rough and the smooth.
Pardon? What exactly is in-market audience?
In-market audiences use machine learning to analyze trillions of search queries and browsing activities to predict purchase intent.
What does this mean? This means that you can now target people based on their online behavior NOT just their most recent search query. As a direct result, you can be sure to display ads that are relevant to audiences at the right time to the right folks.
Past browsing behaviors show the kinds of products and services that users are actively interest in, allowing you to reach people who have displayed high purchase intent signals.
Due to the sheer volume of search queries both of these search giants have access to, you in-turn have access to this same data giving you far more control and precision over your targeting and far greater access to an audience with a good level of intent.
For example, if a user is reading watch review websites and watching watch comparison videos, Google may deem them to be keen to purchase a camera and put them in the relevant in-market audience. Without needing keyword targeting or targeting based on interaction with the brand, advertisers can target users who demonstrate these kinds of signals.
This is an amazing illustration of what machine learning can achieve when given good sample data and provisioned to the right application.
In-market audiences may not sound all that new compared with Other audience targeting options offered by Google BUT they represent a group of users who are truly low down in the purchase funnel.
The difference between in-market audiences and affinity/custom affinity is that the former is tied to temporary behavior whereas the latter type is for getting audiences based on their general interests and behaviors.
Remarketing lists for search ads (RLSA) audiences and similar audiences also show some indication of being to conversion but unlike those, in-market audiences may be entirely unfamiliar with your brand and site – and they’re better for acquisition.
They all have different advantages so using different kinds of targeting is best for greater coverage.
One of the greatest elements of using in-market audiences is the ability to layer them with other audiences and create an even more detailed demographic – targeting not only interests but gender or age. You can set in-market audiences to targeting or observation mode at the campaign level. Usually, with few exceptions you would set audiences to observation mode.
Using this setting allows you to observe how the audiences are performing and then set appropriate bid modifiers once you’re sure you’ve chosen the right audience.
Targeting mode will reduce your reach dramatically so should only be used if you really only want to target the people in the in-market audience and nobody outside of it.
However as much as an advocate I am of using AI and automation to help get the edge, some caution is necessary when jumping in.
When in-market audiences were released, they were celebrated for showing the potential to improve existing campaign performance at no additional cost to advertisers. We could simply click a button to say ‘advertise to this group of people, specifically’.
Whilst the audiences are overall smaller in size, the users are theoretically far more switched on and likely to click. This should result in less impressions but a far higher conversion rate.
It’s true – using these types of improvements can generate impressive results there is a bit of more to it than clicking one of the radio buttons in Google Ads.
Generally, using in-market audiences can lead to great improvements to performance for existing campaigns. We’ve done a number of tests with clients in the technology space and an aggregated view showed that in-market audiences made up to 15 percent of ad clicks and were unsurprisingly more likely to convert at a lower CPM.
In cases like these, you can keep seeing great results simply by raising bids and expanding coverage – as you know your ads will mostly be shown to those within your set criteria. In some cases, we have also seen declines in performance and in other cases we have experienced a rise in costs.
It kind of makes sense because if everyone uses the same in-market audiences, they may not be quite as effective for everyone anymore.
Your competitors may be trying to appear in front of the same audience and if all of your competitors start using the same audience, we’re all going to end up in the same place we were at before in-market audiences we’re introduced.
Google have said that more audiences are on their way which will reduce competition for specific audiences as competition will be less dense. Niche audiences will be more valuable to businesses and so may become more expensive as competitors raise their bids on them.
It does without saying that it’s super important to keep the quality of ads and landing pages as high as ever. It’s also absolutely crucial to carefully monitor performance and make sure to differentiate between campaigns, choosing audiences as specifically as possible will avoid wasting budget on users who are less likely to convert.
Anyone with lots of data from existing campaigns should definitely implement in-market audiences as part of the core strategy and measure the results of doing so. As time goes on and Google’s AI/Machine learning becomes more intelligent, the results should increase and if we’re optimising our campaigns then our results should see plenty of blue sky.
As with any new campaign strategy, continuous testing and reporting are crucial. Comparing results with in-market audiences configured vs standard targeting practices should generate some extremely interesting results for most and provide marketers with an opportunity to get ahead of the pack – at least for the short – medium term.
Keep measuring. Keep comparing. Most importantly, keep revising your best practices whilst keeping an eye on new Google Ad features because if you’re one of the first to exploit a new feature, you’ll be able to make hay whilst your competitors are still at the breakfast table deciding if their eggs should be sunny side up.
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