Display ad campaigns ads shown on select, targeted sites across ad networks that have granted permission to show ads and are compensated for it. The Google Display Network, and the Microsoft Audience Network are predominant for PPC.
Display campaign reports are designed differently because these campaigns often support upper-funnel and mid-funnel activity. Reporting places more emphasis on engagement metrics, custom KPIs, attribution, conversion performance, and financial ratio metrics, using data from Google Ads and Microsoft Advertising.
There are eight different ways to target ads on the Google Display Network (GDN) and YouTube. Each targeting option is based on either the content of websites across the GDN or the behavior of users who move through the network.
To plan display campaign targeting, we first determine which targeting methods are most likely to support the campaign goal. These may include in-market, placement, affinity, custom intent, customer list matching, topic, demographic, and remarketing audiences.
Display targeting usually requires testing before the best-performing audience type and configuration become clear.
Display campaign optimization takes time. Targeting, creative, placements, and engagement quality must all be tested together before the campaign reaches reliable, refineable performance.
For every PPC account and display ad campaign, we create a conversion value model for each type of conversion event and (related), select a method for click attribution modeling. When a conversion occurs, the value for that conversion is distributed ("attributed") up through the sales funnel, with weighting as defined by the click attribution model.
In our conversion value model, what we are after is the gross margin (value) that each conversion action is producing. In the case of a display campaign that advertises products, the conversion value would likely be (sales price-sales tax)*(average gross margin).
Conversion value modeling is important because it allows for calculating the two most important metrics in paid search: return on ad spend, and advertising margin. But more importantly, it provides valuable information back to the automated bidding algorithms, which use machine learning to maximize the performance of the campaign.
Display campaigns are more likely to generate "conversion assist" clicks than final-click conversions. For this reason, click attribution is important for assessing the display campaign's role in conversion performance. But accurate conversion tracking is also important with display.
For this reason, we implement 100% conversion tracking coverage, whether the events being tracked are transactions, form submissions, phone calls, or other meaningful events.
We've found that less than half of existing campaigns have full conversion tracking implemented, and even when conversion tracking is implemented, it is more often than not lacking full coverage.
There is a reason for this – conversion tracking can be difficult to implement and test.
Display campaign optimization depends on testing the right mix of audience targeting, ad creative, engagement signals, attribution, and bidding strategy. As performance data builds, the campaign can be refined through better reporting, improved traffic quality, and automation that supports the larger PPC strategy.
After a display campaign launch, serving can be erratic during the first two or three days. This varies by ad platform, campaign design, targeting configuration, and bidding strategy. Average-size display campaigns usually begin developing a more consistent serving pattern within a few days of launch.
Once a display campaign stabilizes, we look for major issues, such as a single targeting method, audience, or ad group consuming excessive ad spend. We monitor the audiences that pull the campaign into auctions and make corrective adjustments across our display campaign post-launch checklists, dialing the campaign into the type of serving pattern, or “orbit,” we’re looking for.
When setting up display campaign serving parameters, our preference is usually to allow the campaigns to initially run 24x7x365. We can then use that data to optimize the campaign schedule, as we have measured what times and days of the week are most effective.
In some b2b markets, we will run campaigns on weekdays only and perhaps not overnight. There are some common mistakes to avoid, for example in the US making sure East coast campaigns stay on late enough to shop up for West coast end-of-day business traffic.
The reason for running campaigns (at least initially) 24x7 is that many campaigns perform well at surprising times – days of the week, and hours of the day you would not expect.
Display campaign competitive assessment clarifies the market before launch — reviewing competitor positioning, ad messaging, creative patterns, and landing pages to guide targeting and creative.
Display campaign audiences are the primary means for targeting display campaigns. Audience selection starts with understanding the customer’s demographics, behavior, interests, and intent, then using in-market audiences, affinity audiences, placements, customer lists, demographics, and exclusions to improve campaign targeting.
Because display ads are "advertisements" versus direct response marketing, the performance of display campaigns is even more dependent upon, and sensitive to the design of the ads, as compared to search ads.
The display ad channel is fundamentally different to search ad channels. Display ads deliver advertising messages, versus search ads which contain direct response marketing messages. We're showing display ads to audiences who likely may have a related need or interest, but haven't expressed search intent.
Search ads are display on search engine result pages, which the person searching has requested. Display ads are shown on websites where users are not necessarily expecting them. That's quite different from search ads where the user is searching for what you offer.
We've tested different creative approaches to invent, improve, test, and optimize display ads. Our process is based upon the classic creative process, mapped into digital advertising.
The ad group structure in display campaigns is used to separate and test targeting methods, targeting configurations, ad images, and ad copy. Without clear ad group structure, it is much harder to evaluate which combinations of targeting and ads are working.
Some targeting methods require multiple ad groups to better control and observe results. For example, custom intent targeting by URL or placement targeting for specific websites may work best with separate ad groups. Using ad groups strategically helps evaluate targeting and ad quality more quickly.
