PPC3 Tactics for Demographic Targeting on the Google Display Network

3 Tactics for Demographic Targeting on the Google Display Network

Targeting users via psychographic and demographic information on the Google Display Network is nowhere near as easy as Facebook. But with some effort, research, and a patchwork plan, you can apply your defined Facebook audiences to your GDN efforts.

targeting-demographics-arrowA major reason online marketers are attracted to Facebook advertising is the ability to segment audiences with razor-sharp accuracy.

Wouldn’t it be great to create campaigns with a similar strategy on the Google Display Network (GDN)?

We’ve pulled together a plan that can help segment your audience by demographic/psychographic profiles on the Google Display Network.

When compared to the specificity of Facebook and the relatively easy-to-use user interface (UI), the strategy laid out in this article is patched together with duct tape and glue. This is because locating a specific demographic on the GDN can require utilizing and blending targeting strategies.

For this article, let’s say we’re targeting affluent men over the age of 50. The objective of this strategy is to discover and target content on the GDN that these individuals would likely be reading.

Topic Targeting

Within the GDN campaign options, you can target placements by Topic. This means that Google scans the content of each page and places it under a designated Topic. You can target and exclude specific Topics depending on the audience you’re trying to reach.

Below is a snapshot of the Topic Targeting option within the Display Network tab of the AdWords UI. Within this example we have selected Topics that should appeal to our target audience:

topic-targeting-option-gdn-adwords

Because our target audience is affluent men over the age of 50, we have chosen topics such as business finance, business services, banking, golf, etc. These topics might seem a little cliché, but they are relevant.

Interest Targeting

Another tactic for the GDN is utilizing Interest Categories. Often advertisers don’t understand the difference between Topic Targeting and Interest Targeting. At a high level:

  • Topics target the content of a specific page.
  • Interests target the attributes of a specific person.

How does Google determine a demographic profile and related interests for you and everyone else? Here is the scoop straight from the AdWords Support information:

When someone visits an AdSense partner website, we analyze the content of the page and site to show contextually relevant ads. We also use these page topics as well as data from third-party companies to associate interests with a visitor’s anonymous cookie ID, taking into account how often people visit sites of those categories, among other factors.Google may use information that people provide to websites on the Display Network — such as social networking sites — about their gender, age, and other demographics. We may also use the websites people visit and third-party data to infer this information. For example, if the sites a person visits have a majority of female visitors (based on aggregated survey data on site visitation), we may associate the person’s cookie with the female demographic category.

Interests can be added to each individual campaign within your GDN options screen, similar to adding Topics.

If you plan to utilize an Interest cluster in a variety of campaigns, you should create a Custom Combination. To do this, you should enter the “Shared Library” section of your AdWords account, and then enter the “Audiences,” section.

From here you can build a new custom combination, give it a title, and save it for future use. Below is a screenshot, focused on our target audience (men over 50):

new-custom-combination-gdn

On the flip side, you can also create Interest clusters for exclusion.

For example, you may want to gather a series of interests that would appeal to a younger audience (under 18) and exclude them from your campaigns. This can help qualify your traffic and improve performance. However, keep in mind this may limit your distribution as well.

Placement Targeting

Selecting specific placements (websites) to target can be overwhelming due to the extensive inventory on the GDN. However, DoubleClick Ad Planner is a useful tool when conducting placement research based on audience information.

Within Ad Planner you can research sites via Audience, Content, and Placement segmentation. To target affluent men over 50, I entered these parameters within my search:

ad-planner-search-parameters-affluent-men-over-50

By entering my specific search criteria, Ad Planner suggested a series of websites that may be relevant to my target audience. Of course, it’s up to you to sort through the laundry of suggested websites and create your own media plan within Ad Planner.

A great feature within Ad Planner is that their search results provide specific websites as well as the topic under which this URL this fits. If you find that a large number of suggested sites fall into a category, you may want to try targeting those general topics, rather than individual websites, and this can help increase impression volume.

What About Demographic Bidding?

Previously, AdWords offered a demographic bidding option. You could multiply bids based on user demographics. However, around March 28 of this year this feature was retired.

We never found this tool to be very useful because data was extremely scarce on which to automatically adjust bids.

Summary

Targeting users via psychographic/demographic information on the GDN is nowhere near as easy as Facebook. But if you have defined audiences within your Facebook campaign, then you can apply them to your GDN efforts – but it just takes a bit more effort, research, and a patchwork plan.

One caveat with this strategy: conversion rates can be lower via Topic and Interest targeting. Reason being is that you are relying on Google to determine the topic of specific pages, as well as the interests of a specific person. With Facebook, you are often targeting demographic information provide specifically by users and there is less room for interpretation (and error).

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