The Future Of Paid Search (From A Data Perspective)

Over the past five years, the media buying world has changed dramatically.

The incredible advances in adTech (Advertising Technology) and consumer electronics have opened up the doors for never-before-seen targeting and measurement capabilities. Especially in the field of programmatic and audience-based buying, we have made progress at a rate that has even outpaced consumer behavior.

future-computer-woman-shutterstock

As I’ve mentioned previously, we know more about our consumers today than we can leverage without creeping them out. So how has this inside knowledge changed marketers’ online ad-buying behavior?

Historically, we would buy ads based on a context-centric model, very similar to the way we would buy ad space in a magazine. If we were a manufacturer of luxury cars, we would buy ads in car enthusiast magazines. The same holds true for the way we’ve been buying space online; we would buy ad inventory on sites that focus on luxury automobiles.

However, today’s technological innovations and the rise of real-time platforms have led to audience-based, programmatic buying. We know, understand and evaluate each visitor on an individual basis and can serve those visitors hyper-targeted ads based on their specific profiles.

If you are unfamiliar with the way programmatic audience-buying works, please feel free to have a quick look at my recent post, Why Every Marketer Needs to Understand Programmatic. To summarize it, this audience-based buying is one-on-one marketing based on single impressions earned through virtual auctions/real-time bidding (RTB).

  1. As a prerequisite, a publisher/website is integrated with a SSP (supply side platform) and the advertiser/buyer will leverage a DSP (demand side platform).
  2. When a user (let’s call her Melissa) is loading a page on publisher.com the SSP will attempt to fill the ad request created by the user.
  3. The SSP then sends the request to the RTB exchange with the pertinent information about Melissa (browser, cookie data, device, URL, content type, etc.)
  4. The RTB exchange distributes the request to multiple DSPs of which most will have a cookie on the user’s browser.
  5. The DSP will often leverage a data management platform to obtain knowledge about this user (browsing history, activity on other sites, purchase history) as well as obtain third-party data (such as credit card data, household income, and purchase patterns). All this user data triggers the ad request.
  6. Based on the DSP algorithms, a maximum bid is being calculated and matching creative will be sent to the exchange.
  7. Upon completion of the auction, the winning creative will be shown. If there was sufficient user history, a dynamic ad based on previous user behavior might be shown. This could have pre-populated fields or show a product the user previously looked at.
  8. The page is served to the user and any engagement and behavior will be recorded.
  9. By the way, all of this takes less than a second.

This simplified view shows us how amazingly powerful audience-based buying is. PPC platforms like Google AdWords have always provided some basic segmenting parameters, which allow you to target ads based on some audience metrics (and as recently as last week, added parental status to its segmenting).

However, I believe that in order for search to remain competitive with other forms of digital marketing, Google and Bing will have to allow advertisers to connect their audience data to the individual searcher.

Once we have the ability to make bid and ad decisions based on both the query and on the data we have about the individual, we will be able to execute more precise and effective search campaigns than ever before.

Take The Following Example…

We are a luxury automotive brand, and recently launched our new $120k SUV. Now historically in search, we assume that anybody searching for that SUV is a potential consumer.

However, we all know that not every consumer looking at this SUV is really in the market for this type of vehicle. There are many automotive fans who are just curious: people looking for images, kids ogling their fantasy cars, or people just doing general research.

This is where valuable third-party cookie and profile data come in. Companies like Nielsen provide detailed audience segments around age, credit, income, auto ownership and other criteria. For automotive intelligence, companies like Polk provide detailed audience segments on current car ownership, in-market data, attitudes and other hyper-relevant data that guides programmatic ad buying (sample of Polk segmentation).

If we were able to combine this kind of data with our search campaigns, the possibilities really open up.

For example, we would be able to bid low or not show our ad to viewers that are below our target age group or have a household income too low to afford this type of car.  We would be able to increase our bid for high-potential consumers that match all our requirements (income, age, neighborhood, current car, etc.) and increase our chances of showing our ad to that audience.

I am sure you can see the potential for higher conversions from combining this valuable audience data with searchers and with advertisers’ bids. As I mentioned, Google offers some audience guidance via AdWords, but it’s not even close to what’s possible through programmatic ad buying.

To further highlight my point here, data from companies like Kantar Shopcom let you target users by the type of products they buy; if you are a manufacturer for a soda company, you could bid high on consumers that buy a lot of units of your competitor’s brand.

Another great ability this type of integration would allow for, is the use of sequencing.

We could display specific ad copy based on previous user actions. If we identified you as someone in the market for an SUV and you already engaged with ads regarding a specific model in other channels, we could serve you ad copy based on that behavior. Or if we know you also researched a competitive brand, we’d serve ad copy highlighting our competitive benefits.

The potential of audience-based ad buying is huge, and the future of paid search is getting more exciting for those of us who love data. We have not even scratched the surface yet regarding how laser-focused we can get when it comes to reaching the digital consumer.

Building more and more profile data in AdWords will blow the roof off of what we can do with programmatic ads. Google, the ball is in your court.

 (Stock image via Shutterstock.com. Used under license.)

Opinions expressed in the article are those of the guest author and not necessarily Marketing Land.

Related Topics: Channel: Search Marketing | Display Advertising | Display Advertising: Programmatic Media Buying | Google: AdWords | Google: Marketing | Google: Search | Search Marketing | Search Marketing Column

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About The Author: is the Sr. Partner, Managing Director of Strategy at GroupM. He is a digital veteran with over 14 years of experience in advertising. For the past three years, he has led the search practice across the GroupM Network; today, he leads the agency’s search and social engagement strategy group.



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  • Joshua Ballantine

    Very interesting. I always wondered how programmatic affects search. Are there any companies that are already doing this type of programmatic buying on search?

  • http://predicative.com/ Chad at Predicative.com

    Audience data has been the traditional way to target since the practice started in the 50s. In recent years, three concerns have arisen around using data on individual preferences online:

    1) consumers and regulators becoming more protective
    2) the rise mobile which is a problem for cookie pools
    3) the US is saturated with cookies, but there are HUGE markets in other countries that Experian/Acxiom do not have consumer data on

    The truly new thing that is happening now is big data. This gives us targeting capabilities that challenges the traditional ways, and cannot be defeated by an adblocker. Combine THAT with RTB and you have the future of online advertising.

 

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