Layering Up for Fall: Layered Targeting in the GDN
Published: November 16, 2016
Author: Madeline Fitzgerald
The sweaters and hoodies and boots have been broken out: we’re knee-deep in fall. But if that’s the only layering you’re doing this season, your paid media could be missing out.
Google, Facebook, Bing, and more have an extremely wide variety of advanced targeting tools available, whether you’re building an ideal audience from scratch or finding consumers similar to your current customers. Google’s simple-but-powerful Custom Affinity Audiences for display campaigns, for example, go unused in many accounts. But no matter how powerful the tool, there is always room to narrow further. Layering up on targeting elements saves you from wasting spend on users who are not likely to click or convert.
For instance, let’s say you are targeting small business owners in a display campaign. Interests, keywords, or in-market audiences can approximate this group pretty well. However, for a new campaign, you specifically want to target owners of small coffee shop chains. A custom affinity audience could help you get closer to the intersection of small business owners and ultimate coffee experts, like so:
If you’re not seeing the performance you expect, however, layering up can knock out some of the spend you’re wasting on non-converting viewers. Narrowing your targeting this way will decrease CPA and improve ad rank and ROAS.
To layer up on this custom affinity audience, there are two tests you should run: First, logic. Looking at the above example, Google finds applicable users in all age demographics. Yet realistically, “18-24 year olds” will not actually be the coffee shop owners that you’re trying to target. Deselecting or decreasing the bid on this demographic—pulling on that additional layer, the cozy cardigan—will help make sure your ad is serving to decision makers.
The second test comes in where logic leaves off: data. Most assumptions about your target audience will not be quite so obvious. For instance, you can probably assume that most coffee shop owners will be with their customers from 7am to 9am, not on their computers or mobile devices. Check the data. The only thing worse than wasting spend when your target audience is elsewhere would be missing out on traffic because you did not check the data before making your assumption.
Similarly, keeping an eye on the data regularly will help you determine which other targeting and optimization levers you should pull. Let’s say you run a high-end car customization and repair service. A great targeting tool for a display campaign would be the Auto Enthusiasts affinity audience. Let’s layer up, adding targeting for people currently in the marketing for auto maintenance and managed placements for the most popular car sites.
You’ve pulled on your scarves and undershirts, but check the data: maybe the managed placements have negatively impacted your performance by narrowing too drastically, and your KPIs were better before this last layer.
Don’t forget to keep an eye on the estimated audience size. You can’t wear every cozy fall sweater on one day, and using every targeting tool and bid adjustment will limit your audience too drastically, until you’re only targeting a few thousand users.
With a big enough audience and strategic use of targeting tools, these tactics can be applied to other types of display campaigns like GSP or app install ads, or to social media (layering using Facebook Audience Insights, anybody?). Layering puts your ad in the right place at the right time, improving conversion rates and marketing ROI as a whole—not to mention keeping you warm in the autumn chill.