A new metric for search and display will allow advertisers and agencies to measure relevance. Announced on Monday, Ad Strength offers insights and best practices that inform marketers about image choices, predictions on click-throughs and copy diversity.
The new metric seeks to assist customers of Google’s search ads, responsive display ads, and Universal App campaigns. The details of the new metric are set to be released next week on the dedicated Google Ads blog.
“Let’s face it, most of the ads online are rubbish,” said Tobias Wilson, CEO of APD Group. “They’re functional, BAU, ‘keep the lights on’, done in-house assets that exist to tick boxes vs ‘shift’ boxes. I think this will help lift the standard of those kinds of ads and hope that it’s widely adopted as consumers deserve more. Even from BAU work, in fact, especially from BAU work!”
According to Google, users of this Ad Strength metric will need to provide at least five variations in headlines and descriptions before machine learning can offer a prediction based on known click-through rates (CTR) and conversion rates.
Serving as a barometer, the Ad Strength metric will score the selected image and copy choices from poor to excellent, based on headlines, descriptions, and other visual assets that are the foundations of effective ad combinations.
“Agencies are continually presenting the efficacy of ads through KPIs related to a campaign, without being able to tightly attribute any of that success to creative,” said Alex Thoma, business transformation lead at APD Group. “And often results are dressed up and presented in silos. Responsive ads will take the guesswork out of creative, and has the potential to deliver excellent upside on campaigns.”
Thoma believes the opportunity is to connect dynamic personalized ads to bespoke onsite experiences, using AI to automate an optimized user experience for better conversion rates. “When that happens we can all pack up and go to the beach,” he says. “For good.”
According to Google, users of this Ad Strength metric will need to provide at least five variations in headlines and descriptions before machine learning can offer a prediction based on known click-through rates (CTR) and conversion rates. For display ads, marketers will be expected to provide at least 15 image variations and at least five variations of logos, headlines, and description per display ad.
“Those of us running ads want to get the best results, reaching the right people,” said Erik Magelssen, digital content director at Click2View. “Even perhaps the ones we haven’t thought of, in the fastest, cheapest (most relevant) way possible.”
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