Adthena Pivots Roadmap To Match Brands' Economic Challenges

Adthena has made a pivot in its plans to support brands as more are making efforts to save money and gain a higher return on ad spend.

“We've pivoted the product roadmap hard to match the macro climate environment,” Ashley Fletcher, CMO at Adthena, wrote in an email to Search & Performance Marketing Daily. “No one wants to waste budgets right now.”

The company introduced several technologies on Friday. One is designed to automate when a brand’s ad should appear or not, keeping in mind competitive bids on keywords or terms.

Brand Activator, aimed at assisting brands to save money, automatically monitors and identifies the terms. If competitors have not bid on the term, the bidding is automatically paused to save money. Bidding resumes when a rival re-enters the auction in Google Ads.

It works with Google Ads and tracks the return on investment by day and search term.

Even large brands became early adopters. One enterprise company signed on seeing about $6,000 per week in savings on Google Ads by better controlling the advertising and not wasting budgets.

Trademark monitoring has always been a challenge, but more so now, Fletcher said.

Trademark Takedown focuses on the workflow as advertisers push out budgets. Adthena continues to observe rising brand infringement in Google Ads. It’s not clear if Performance Max can accurately catch when infringements occur.

Adthena also introduced an innovation in artificial intelligence (AI), overlaying ChatGPT onto its ad copy indexed from Google.

AI gives direction when creating ads on theme, pricing, sentiment and more. It is pushing the technology into its Labs feature for users.

Adthena’s machine-learning technology analyzes thousands of new daily ad-copy insights for clients. ChatGPT raises the support by helping them optimize Performance Max campaigns to achieve a higher return on ad spend and return on investment.

It helps to see data through the black box of automation of Google Ads as it identifies missing opportunities.

Company developers are re-training GPT-3, the model that ChatGPT was built on, to ask natural-language questions. It allows brands to explore data and uncover new insights in a way not possible before.

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