Optimisation of spend has always been a critical element to advertisers given the somewhat volatile nature of the ad industry. However, while regulatory, legislative and commercial curveballs are being thrown at a rapid rate, concurrently new technological solutions are being developed to overcome such issues.
In this Q&A with ExchangeWire, Marin Software co-founder and CEO Chris Lien (pictured below) discusses how machine learning has been used to optimise ad spend and measurement, as well as how this can feed into cross channel marketing strategy.
Why have nearly a quarter of advertisers adopted Responsive Search Ads, despite still being in beta?
Despite initial skepticism from advertisers when Responsive Search Ads (RSAs) were first announced at Google Marketing Live 2018, our data shows that adoption has been very healthy. In fact, our Q1 2019 Benchmark Report shows that 24% of advertisers on the Marin platform are already using RSAs.
RSAs allow machine learning to optimise ads for each impression to serve the best possible message for each user. This improves performance and simplifies the ad copy creation process and has been shown to deliver good results. Many advertisers are experimenting with the format and increasing use of the ad format to see how it compares with Expanded Text Ads (ETAs).
How will machine learning be used to optimise search spend? How do you envisage these technologies being used across the rest of the industry?
Dynamic ads are already in use in display and Facebook offers Dynamic Creatives which are very similar to RSAs.
Machine learning applications are also particularly suited to bidding and forecasting use cases in digital advertising. Advertisers should be looking for optimisation algorithms that combine the latest in machine learning with detailed data on account performance to improve predictions and drive better performance for paid search accounts. Machine learning can also be used to search for additional untapped growth, unlocking the potential of long tail keywords through advanced clustering techniques.
What more can be done to optimise ad spend across the web and on mobile? How can wastage be combatted?
For many advertisers, better use of audience targeting and segmentation of first party data is a great way to achieve spend optimisation:
1. Show relevant and engaging ads to the right people (at the right time)
2. Use intelligent audience segmentation to filter out poorly qualified prospects and focus ad spend on your core target audience
Keeping a close eye on the performance of any channel, through to conversion, will enable marketers to quickly turn off spend that isn’t working, whether it be through poor targeting or darker reasons, like ad fraud.
What opportunities and challenges do you foresee for cross-channel marketing over the coming year? Will the decline of the third-party cookie and the rise of unified IDs have a major effect on these campaigns?
Attribution and conversion tracking is certainly a challenge for modern marketers, particularly with the decline of third party cookies and further restrictions on first-party cookies. Apple’s Intelligent Tracking Protection has restricted all third-party access to cookies for purposes such as advertising and tracking to a one-day window back in 2017.
Since traditional programmatic display is built on third-party cookies, ITP makes it harder for smaller publishers and many third-party ad tech providers to offer audience targeting capabilities based on prior web behaviour or browsing patterns. ITP 2.2 (announced in May 2019) goes even further by forcing the expiration of first-party cookies to one day.
What does this mean for advertisers?
We believe it’s time for advertisers to upgrade measurement solutions, and we have three key recommendations:
Move away from tracking via redirects: Redirects have been considered third-party by Safari for years, but now they’ve moved to close all the tracking/redirecting loopholes. Do not use redirects for new programs and be sure to move to a more modern approach for existing programs.
Estimate Safari conversions based on Chrome users: This is an easy and low-touch option but raises some accuracy questions. This approach is used by Google, but it often performs differently for mobile users because Safari reaches a younger, more mobile, and more affluent demographic than Chrome.
Upgrade your measurement source: With the latest iteration of Safari ITP, it’s clear that measurement solutions purely relying on client-side logic (i.e., standard website tracking tags) will no longer work. Work with a tracking provider that can provide the tools to ensure tracking in an ITP world.