3 Yield Optimization Strategies Publishers Should Already Be Using
The advent of header bidding opened the door to new paths to revenue for publishers, but it also added complexity. As time-consuming as managing your ad stack can be, actually optimising yields can be an even larger challenge. But, with the right strategies, it’s easier than it looks.
As publisher ad stacks have become increasingly complex, with a blend of direct sold and header bidding line items, the idea of simple yield optimization has seemed somewhat less achievable. And while simply allowing your ad stack to do its thing might seem like the simpler choice, there’s almost no question that you’re leaving money on the table.
So how do you get that revenue back in your pocket where it belongs?
Here are three straightforward yield optimization strategies which you should be using as a publisher to ensure you’re getting maximum returns for every one of your ad units.
Strategy #1: A/B Testing
For as long as creatives have existed, advertisers have been leveraging A/B testing to improve their results.
While it’s incredibly common for buyers on the demand side to consistently tweak and optimise their ad strategies, it’s much less common for publishers. But it doesn’t have to be that way.
If you’re using header bidding as part of your ad stack, here’s how you can adjust your strategy to see what delivers the best incremental lift… and what doesn’t.
- Discover your perfect number of bidding partners. Conventional programmatic wisdom holds that the more bidding partners you add, the worse the user experience becomes because of the latency involved in the bidding process. But the extent of this latency will be different for every website. That’s why it’s a good idea to test the impact of adding more bidders to your ad stack. To test this, you should add bidders until it negatively impacts either bounce rate or revenue, then roll back as required. To expand your testing, you can also move bid partners from client-side to server-side integrations to reduce load time – though this can reduce match rate (making it another good candidate for A/B testing).
- Experiment with Timeout Rate. With header bidding, publishers specify an amount of time they’re willing to wait for a valid bid response. The longer this Timeout Rate, the worse the experience for the user, and the higher the risk of lost traffic – and lost revenue. Experiment with longer timeouts until you find the balance between revenue and user experience. You can also set longer timeouts for below-the-fold ad units, because users will generally take longer to actually scroll them into view.
- Test out different line item priorities. If you’re using Google Ad Manager (GAM), you’ll know that direct sold line items using the top Sponsorship or Standard tiers are prioritised during ad serving – even if a higher CPM exists in a lower tier. One way to experiment with yield improvements is to set higher-CPM header bidding line items to one of these top-tier priorities in GAM, which will allow these partners to compete with direct sold line items – and improve your potential returns in the process.
Strategy #2: Analytics and Reporting
If you are anything like 90% of the world’s large digital publishers, you’re probably already using Google Ad Manager – but did you know that it offers a range of in-depth reporting options to help you optimise your yield?
Armed with this historical data, you can start to make data-driven decisions about your inventory layout, content design, or header bidding setup. There are too many available metrics to list them all here, so here are the metrics which are most likely to reveal yield optimization opportunities.
- Unfilled Impressions. When an impression goes unfilled, it means that no eligible line item was available to fill the ad slot. This metric is perhaps the best indicator of where to focus your attention, because it’s a direct representation of lost revenue. To lower the number of unfilled impressions, you can adjust your bid floors, integrate with new SSP partners, or even replace it with first-party creative.
- Coverage (or Fill Rate). This percentage-based metric represents the amount of ads which were served on a page vs. the number of ad requests which were processed. Put simply, the higher your coverage or fill rate, the higher your revenue. If your coverage is low, consider adding new demand partners or ad networks to avoid unsold inventory.
- Impressions not competing. This lets you know how many of your line items aren’t making the cut for auctions, which will negatively impact revenue. If this number is worryingly high, you can usually resolve the problem by reviewing your line item priorities. For example, you might have a high number of Sponsorship or Standard line items which are essentially preventing lower-tier line items (Network, Bulk, etc.) from competing.
Strategy #3: The VAST Waterfall
Whether you already leverage video ads, or you’ve merely dabbled in the past, you might be familiar with the IAB’s VAST specifications.
For the uninitiated, VAST, or Video Ad Serving Template, enables publishers to run video-based ads within their ad unit inventory with advanced delivery tools, tracking options, and smart features like dynamic insertion. No matter the website or device being used to view it, VAST helps publishers deliver a consistent video ad experience.
However, no system is perfect – and, sometimes, VAST errors can occur in the space between an ad impression being won and the ad being served. For example, a particular video creative might not be found, there could be an HTTP error, the VAST response times out, and so on.
When this happens, the impression is lost – and the potential revenue along with it. According to internal testing here at The MediaGrid, up to 13% of video supply results in errors with no ad being served.
Luckily, there is a backup plan.
The VAST waterfall, or client-side mediation, operates in much the same way as conventional programmatic waterfalls. If a particular ad request receives a VAST error in response, rather than simply erroring and producing a blank ad impression, it will instead request another VAST ad from the publisher’s ad server. This fallback will take place until the first frame of a video ad is played. If the video ad fails to play again, the waterfall continues until either an ad successfully renders or the network’s fallback limit is reached.
By using the VAST waterfall as a safety net, The MediaGrid clients have seen an uplift of 14% impression growth when running video ads.
Are you realizing the true potential of your inventory?
Implementing one or more of these yield optimization strategies should help you unlock incremental lift for your site’s revenue stream – but it doesn't end there. If you really want to unleash the potential of your content, we invite you to integrate with The MediaGrid. Not only will you gain instant access to premium curated demand from major agencies, but you’ll also benefit from increased bid transparency via real-time trading data and reduced risk of ad fraud.
To learn more about The MediaGrid – or to get your integration started in just a few clicks – reach out to our team today.