Search engine marketing’s meteoric rise over the last decade is due, in large part, to the superiority of query-level targeting as compared to other online advertising channels. The targeting edge that SEM once held, however, may be slipping.
Indeed, for many advertisers and many verticals, SEM may no longer be the best channel for laser-focused advertising. In this article, I look at five types of online targeting and compare the functionality of SEM versus two other popular marketing channels – self-serve display advertising (Google Display Network) and programmatic display advertising.
Types Of Online Targeting
Before I delve into the specific targeting features of online marketing channels, let me suggest a framework for evaluation. Broadly speaking, there are five types of online targeting currently available to online marketers:
- Query – what is the user searching for?
- Location – where is the user located?
- Time – what time of day, day of week, and time of year is it?
- Device – are they on a mobile phone, tablet, or computer (and what is their operating system and carrier)?
- Behavioral – who is the user, demographically, or psychographically? Note: this is the broadest of my five factors, since I’m including data like offline purchase behavior and social sentiment in this category – over time, I could see this factor broken into several separate groups as targeting matures.
Round 1: Query-Level Data
Query-level targeting has always been the selling point of SEM, and AdWords (and Bing/Yahoo, of course!) are still the clear champions when it comes to targeting users based on queries. That said, GDN does interpret the semantic relevance of a website to allow advertisers to try to use query-level data in display; and, third-party search retargeting companies like Chango, Simpli.fi, and Magnetic offer query-like targeting throughout the display ecosystem.
But let’s face it, query-ish display targeting still pales in comparison to the real deal – SEM! If you are marketing an established product (i.e., something people would be searching for), SEM should be your most important channel.
Round 2: Location Data
Location targeting is vital for local businesses with limited geographic reach, but also very important for any business that might see differences in purchase behavior by geography. In general, geography can be inferred by one of five ways:
- Geo-modifiers in a query (e.g., “Chicago mortgage rates”)
- The IP address of a user’s device
- The semantic content of a page the user has recently visited
- A user’s self-defined location when s/he registers online (such as signing up for a Gmail account).
- First-party or third-party data
AdWords uses all of these geographical inferences except for first - or third-party data – when targeting users on desktop search. This is both good and bad news. On the plus side, Google has a lot of different ways to infer a user’s location, which can be helpful when someone a block from your pizza restaurant searches for “great pizza restaurants for lunch” and you want to market to them.
On the other hand, if Google uses the wrong inference to target the user (e.g., the user is registered on Gmail in your home town but happens to be 50 miles away when doing the pizza search), you might end up with unprofitable geo-targeting. Google has rectified this dilemma – at least to a degree. AdWords now allows advertisers to choose whether they want to target only users who use a geo-modifier, or who are in a specific location, or both.
While GDN and Display cannot use geo-modifiers in a query as accurately as AdWords, they do allow for better usage of first- and third-party behavioral data. To clarify what these two forms of data are, first-party data is information collected directly by an advertiser (i.e., if a consumer has purchased something in the past from you), while third-party data is generally anonymized data collected and sold to the advertiser (e.g., based on our data, this user buys a lot of dog food).
GDN allows advertisers to access a limited set of third-party geographic data via their “interests” and “topics” functionality. In the example below, you can select people who are “interested” in a particular geographic region of California (which I assume is more or less synonymous to that person living in that region):
You can also “sort of” use first-party targeting in GDN via remarketing. For example, if you have pages on your site that are geo-targeted (for example, “Mountain View pizza directions”), you could, in theory, limit your GDN advertising exclusively to people who visited that page via remarketing, effectively creating a Mountain View-only campaign.
Ultimately, however, this quasi-behavioral targeting on GDN pales in comparison to what is available to advertisers via programmatic display buying on ad exchanges. Sophisticated display advertisers leverage “data management platforms” to leverage reams of first-party data and multiple third-party data sources to create hyper-local campaigns directly targeted to specific user groups (or even individuals).
In other words, in a well-executed display campaign, it is possible for the advertiser to actually know the user’s home location (via first-party data), broad interests (via third-party data), where they are currently located (via IP address), and – to a lesser extent – the geographic nature of the content the ad is appearing adjacent to.
Given the high relevancy of geo-modifiers in search and the equally high accuracy of first-party data in a programmatic display campaign, I’m calling this one a tie between AdWords and Programmatic Display (sorry GDN)!
Round 3: Time-Of-Day, Day-Of-Week, Time-Of-Year
AdWords and GDN have decent day-parting functionality, though it is a bit buried in the settings (perhaps on purpose, so as to avoid melting the brains of newbie SEMs). Effectively, you can make 49 automated bid adjustments a week by time-of-day or day-of-week (seven per day):
For most advertisers, I suspect that this is more than sufficient. That said, programmatic display buying does provide more time-based granularity via “real time bidding ” (RTB for short). As the name implies, RTB allows advertisers to make ad buy decisions every time an impression is available for purchase. In theory, this means that advertisers can make millions or billions of decisions within a 24-hour time period.
In reality, I’m not convinced that demand side platforms (DSPs) – the technology that programmatic buyers use to buy advertising in real time – are truly analyzing whether an impression at 6:01 am and 6:02 am deserve different bids based on time-of-day, but there certainly is more time-based functionality available via display than the 49 time slots currently available via AdWords and GDN.
That said, it’s important to note that Google’s conversion optimization tools – the “conversion optimizer” on AdWords and the Display Conversion Optimizer (DCO) on GDN – do make changes to bids in real time, and have the potential to adjust bidding more than the 49 times you are allowed via the self-serve tool. So, in a way, AdWords and GDN advertisers do have access to an RTB tool, just without the ability to make manual adjustments that a display advertiser can make with a DSP.
Results: A Three-Way Tie! (Overall Score right now is AdWords: 3, Programmatic Display 2, GDN 1)
Round 4: Device Targeting
Once upon a time, AdWords and GDN had AWESOME device targeting. It seems like it was so long ago . . . Unless you have been living under a rock without Internet access, you should know by now that Google’s new “Enhanced Campaigns” settings will effectively remove almost all the device granularity previously available to advertisers. Just to show the difference graphically, here’s the before and after functionality:
It turns out that the level of targeting Google used to offer was superior to the current targeting available in programmatic display buying; but, as a result of enhanced campaigns, programmatic buying is now the superior targeting option. With programmatic buying, you can still target users by device and carrier, something that is now not available in AdWords.
So, with a heavy heart, the winner in this category is: Programmatic Display
Round 5: Behavioral Targeting
Going into the final round, we have a two-way tie for first place – Google 3, Programmatic Display 3, and GDN 2. It’s still a wide-open race!
Behavioral data in AdWords is limited to non-existent. To my knowledge, Google currently does not allow advertisers to leverage third-party behavioral data in their search ad buying (though I have heard rumors of betas that do this). On the first-party side, the only way to leverage actual knowledge of user behavior is to use remarketing lists for AdWords, but – as with Google’s other remarketing products – this is only first-party in the sense that you know a user visited a page of your site.
GDN goes a step further than AdWords by providing the aforementioned “interest” and “topic” third-party targeting options, though you are limited to Google’s data only (not the case with programmatic buying). And, on the first-party side of things, you are limited to remarketing only.
Programmatic display buying has an advantage over AdWords and GDN on both the first-party and third-party behavioral side. First-party data in programmatic buying has the potential to be much richer than just retargeting – for example, a retailer could target sets of users based on a “recency, frequency, and monetary” methodology, with the data derived from actual customer purchase behavior. On the third-party data side, there are dozens of behavioral data companies more than willing to sell advertisers slices and dices of data.
The winner of this round, with a technical knock-out, is Programmatic Display buying.
Tallying Up The Scores!
The final result: Programmatic Display 4, AdWords 3, GDN 2 – congrats to programmatic display buying! Now, before you go and scrap your SEM campaigns and dedicate 100% of your resources to RTB and DSPs, let me state for the record that there are still many – many! – products and services that will perform better in SEM than in display, simply because SEM is almost always at the end of the conversion funnel, and display is often closer to the beginning.
The best result for almost any campaign is to max out SEM to capture folks in the last stages of purchasing, but to also identify targeting upstream opportunities on GDN and programmatic display to fuel additional demand.
I recognize that this has been a bit of an epic post (anyone out there still reading?). For a graphical description of the targeting benefits of each of these channels, check out the image below or download the chart here.
Opinions expressed in the article are those of the guest author and not necessarily Search Engine Land.