January 8, 2019
The Evolution of Google Exact Match & What It Means for PPC Advertisers
Have you ever found yourself saying, “These non-brand PPC campaigns just don’t perform well”? There are definitely areas where competition is fierce and non-brand performance can seem elusive, but there are also often performance gains to be had if you are willing to dig a bit deeper to find the right target audience.
Let’s say you are an advertiser who sells premium black leggings. Your price point is quite high, and the quality of your leggings is some of the best in the industry. You have already maxed out spend on brand and targeted non-brand terms, and since you still want to grow, you begin bidding on the keyword ‘black leggings.’ However, even though this keyword matches exactly with what you sell, you’re seeing minimal conversions at an extremely high spend.
The reason for this is that you have now entered an auction that doesn’t just include the same core competitors you encounter with very targeted non-brand keywords. Now, you are going up against big box retailers and other advertisers who also offer black leggings but at varying price points and quality. Not only that, but you have no idea exactly which types of leggings the searchers themselves are looking for based off their queries.
While there is nothing in the users’ searches to qualify them, we know there are qualified users out there who are searching these generic, non-brand searches. So how do we still serve ads for these high-funnel searches without totally compromising our profitability in the process? The answer lies in Google’s Audience Insights tool.
In order to determine your prime customer audiences, take a look at your top revenue-driving customers and build a customer match list. Then, upload this customer match list into AdWords. Note that AdWords will take a few days to actually match your emails to Gmail users, but once that is done, they can provide you with some fairly accurate statistics around your top performing cohorts (example below).
Once you have these insights, you can leverage them to build your customer audiences and proactively apply those audiences to your non-brand campaigns to make them more targeted. Going back to the ‘black leggings’ example, rather than serving ads for all users seeking out black leggings, you can proactively limit your targeting to only show ads to users who are female, between the ages 18 to 24, and who live in zip codes associated with the top 20% of US household incomes. While these searchers are not specifying the types of leggings they are looking for in their queries, we know based on their demographics that they are a more qualified audience for us than the general population.
Before you give up on lower-performing non-brand PPC campaigns, try using Audience Insights to identify your target customers and ensure you’re showing ads to the most qualified audience possible.