The Highs & Lows Of Search Retargeting: Version 3.0 Is Here Already
I know this industry evolves fast, but damn! Just 18 months ago, most media planners and search marketers had not heard of search retargeting, and already we are in what could easily be called version 3.0. With the agency hat back on (for today), we look at whether this tactic is living up to the growing hype.
When the principle was first explained to me, I was running an agency display media team at a search agency that was focused on direct response clients; I was therefore interested in tactics that involved precise data points as a way to focus on user intent.
Search retargeting seemed to fit the mold perfectly: target just those individuals with display ads who have actually searched for the terms that were relevant to the client, eliminating nearly all wastage from the plan.
We were building what we called the agency’s “foundation layer” of display: site retargeting to fix on-site conversion, search retargeting to prospect and plug the leak from SEM, and social retargeting to add further scale to the audience. So we picked five clients who had a pre-agreed testing budget and rolled out search retargeting with an early vendor, only to see four out of five of the campaigns bomb!
The primary reason was that in Search Retargeting 1.0, there was no scale in the data and little effort invested in the media placement. The campaigns were great when spending $100, but as soon as the vendor tried to scale to fill the budget, they would have to broad match and lose the relevancy, and of course the ROI.
Growing The Data – Search Retargeting 2.0
But sticking with it, campaigns began to perform better over time, and in almost direct correlation with the quantity of data that was available. Now we could focus more on the relevant terms and ignore some of the broad head terms. And as any search marketer can tell you, volume comes from the broad terms, but ROI comes from the specific. With data volume no longer such a problem, search retargeting 2.0 was on the horizon.
The theory states that search retargeting should outperform most other display placements because of its accuracy, and even come close to the performance of your search marketing efforts — as an industry it simply was not there yet.
But with the intersection of search and display looking like the future of digital, I left the agency to go help make this work.
The Data High
Too many marketers went through a phase of being high on data, believing that a single reference point was all that was needed to generate great DR results. They lost sight, in their excitement, of the continuing importance of creative messaging and the context of the media placement. Knowing who to talk to is important, but doing that in the right environment and with the right story really matters.
As popularity in search retargeting grew, so did the funding, which allowed the successful players to build their own DSP (Demand Side Platform) technology to manage the quantity of data and build in these essential elements. Marrying thousands of keywords with thousands of potential ad placements is not easy though, particularly when you have to do it in real time and at the keyword level.
Advanced Optimization — Search Retargeting 3.0
In a recent Chango search retargeting campaign from a large retailer, the need for keyword level optimization is clear:
Search retargeting example 1:
- ‘clothes shop’ — CTR of 0.87%
- ‘clothes shopping’ — CTR of 0.25%
Search retargeting example 2:
- ‘shoes mens’ — 0.16%
- ‘mens shoes’ — CTR of 0.21%
The search marketer is used to a world where this type of analysis is commonplace, but what is different is the choice of media sources.
In SEM, you choose from two major engines and then can add the extended network, usually by just ticking a box and forgetting it. But with real-time display, including search retargeting, we can buy in excess of 100,000 QPS (Queries Per Second — a simple measurement of media capacity).
Therefore managing search retargeting campaigns today is complex. Typically a campaign will need to be optimized manually once a day, but then “machine learning” must be used to balance the multitude of options available.
In our examples above, the term “clothes shop” clearly had a better type of intent that “clothes shopping” for our client, but that could only be determined by analyzing the placement on tens of thousands of sites. The balance of people and technology provide the scalable solution (but interestingly also blur the line between agency and vendor).
In addition, search retargeting 3.0 leverages dynamic creative, but unlike a typical dynamic setup, there is actual search data to work with, producing richer and more relevant experiences for the end consumer. Search retargeting sprang out from a sea of providers buying on the exchanges, but now seems to be leading in terms of what can really be achieved.
A Blessing & A Curse
Search retargeting would probably not be the name our micro-industry chooses if it got to choose again. When media planners hear it they immediately get excited, as they know a good media plan should always include some type of retargeting. But their first assumption is that it targets their existing site visitors. Many conversations begin by saying this isn’t the retargeting you thought it was!
But once marketers understand, they see its value for the long term. Like site retargeting and the SEM program itself, it typically becomes an evergreen program, running continuously as a reliable source of revenue.
In Summary …
Search retargeting arrived on the media scene less than two years ago, and less than one year ago for most media planners. It leverages the power of search and executes it with the scalability of display. It is enormously complex because of the volume of both keywords and media placements, so early campaigns were often not successful (v1.0). But as the industry grew, so did the data, and with it came a certain amount of reach (v2.0).
Today, major brands invest hundreds of thousands per month on evergreen and seasonal campaigns in search retargeting thanks to the results that in-house DSP bidding technology allows for true keyword level granularity. Machine learning, dynamic creative and lots of experience means that version 3.0 is upon us … and growing.
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