“Displaying Search” is a column capturing the intersection of display advertising and search marketing.
Today’s column is written by Justin Merickel, VP of New Product Development and Marketing at Efficient Frontier, a search engine marketing solutions company.
The other day a group of us at Efficient Frontier gathered in a conference room to discuss display optimization. We met to dig into the comparative ROI for various audience segments, including site-driven retargeting and 3rd-party purchased segments. One of our lead engineers developed an interesting analogy that mapped audience targets to search term types. The search term to audience segment analogy is an interesting way to think about relevance and tactically design portfolios of targets for display campaigns.
Before jumping into display, let me set up the analogy by talking about term types in search. We tend to think about search terms in three buckets: head, torso, and tail. Head terms have mass amounts of queries but are less specific in query intent, torso terms have decent query volume and some specificity in intent, while tail terms tend to have little volume but have very clear intent. Additionally, in search marketing, we typically isolate brand terms into their own category.
With that in mind, the display to search analogy goes like this: retargeting is like search brand terms, 3rd party data buys are like search torso and tail terms, and site or content targeting is most like search head terms. Let me play it through with you in more detail.
Site retargeting typically delivers strong ROI but is limited in scale. The only value question clients ask is what percentage of retargeting conversions would have occurred without the influence of ads. Luckily, the question of incremental value for retargeting is a fairly straightforward one to address with testing.
Moving outside of retargeting, our goal is to stay relevant to our advertisers in display media. Through a 3rd-party data company, we can buy specific audience targets like car or retail shoppers. If you get to a directly relevant segment, the response rates and conversion rates are likely to be strong, but still pale in comparison to retargeting. While 3rd party audience segments are in-market, a portion is likely to have a strong brand affinity for a competitor. For example, in targeting domestic truck shoppers for Dodge via 3rd-party data, some consumers may prefer Ford making it difficult for Dodge to gain consideration and conversion.
Volume is also a primary consideration in 3rd-party targeting. Targeting an in-market domestic truck shopper purchased via a 3rd-party data provider may result in reasonably strong segment volume (torso). Whereas targeting that in-market truck shopper on auto specific content will improve relevance but reduce volume potential (tail).
Search torso and tail terms often have intent clearly indicated in the query. Torso and tail terms perform very well in clicks and conversions but most often trail brand term performance by a significant margin. For example, a company like Best Buy will likely perform well on terms like “40 inch Plasma TV” due to their strong relevance and brand for consumer electronics. The consumer has indicated their interest in a product that Best Buy offers, but they may prefer to research at Sony or buy at Amazon rather than Best Buy, making conversion rates lower than brand terms where intent and brand affinity are both present.
Finally, in both display and search we have the challenge of addressing more broadly relevant audiences. Going back to the Dodge example, targeting auto specific sites or content is an example of a more broadly relevant tactic. The Dodge Ram relevancy to this set of auto inventory will be lower than targeting domestic truck shoppers. Yet the larger addressable audience size makes the general auto shopper an important segment for Dodge to engage. Your ad engagement and conversion rates will be lower but to achieve maximum scale it critical to address this audience.
In the third piece of the analogy, general audiences in display are like head terms in search. In search, head terms are always high volume but harder to make yield strong returns. The intent of a search query like “electronics” isn’t clear. The consumer could be seeking information on DVD player repairs or be in the market for a plasma TV. Yet these terms are critical to use in paid search campaigns in order to add scale both in direct conversion and by influencing the consumer during their purchase cycle.
At the end of the day, I believe the analogy of audience targets to keywords holds some water. Intent data creates advertiser relevancy. But as with a portfolio of search terms, in display you need a variety of audience targets to maximize scale. Cherry picking only the most relevant audiences in display, or using only brand terms in search, will yield incredible ROI but no scale.
Additionally, the analogy of audience targets in display to keywords in search highlights the importance of bidding to value. Clearly, the audience value will dissipate as you get less relevant so the price of the combination of data plus inventory must decrease commensurate to results. And the results of various audience targets may shift hour to hour, as frequency rises, or as content adjacency varies necessitating regular bid updates.
Clearly, there is value in optimizing display on site, frequency, ad size, and geo/demo data. But in our view, if you just start by establishing an audience value based on their relevance to your product, you will be ahead of the game. Just don’t lose sight of the forest for the trees. Optimize to the potential of the portfolio not the component parts.
Follow Efficient Frontier (@efrontier) and AdExchanger.com (@adexchanger) on Twitter.
