Advertisers may be damaging their campaigns with blanket ads.txt adoption, new research from Infectious Media shows.
Infectious Media, the programmatic and technology specialist, has published research today showing how advertisers can damage their campaign performance with an unsophisticated implementation of ads.txt authorised buying.
- Buying Direct brings a 60% higher proportion of sales than Reseller
- Buying Direct is 37% more expensive, and 24% more prone to fraud than Reseller
- The value in Resellers is widely dispersed, not all Resellers are the same
- The “Unknown” long tail still provides value for advertisers
Some of the findings of the research back up industry assumptions about performance being improved by cutting out middlemen, for example 60% higher transactional conversion rate through Direct than through Reseller inventory. Where others go against the prevailing view, such as, Direct inventory brought 24% more fraud that Reseller.
One of the most important insights for advertisers is the level of value still achievable from buying “Unknown” inventory, or sites not participating in ads.txt. The research found that Unknown inventory still drove a significant number of sales, and to disregard it would harm client campaigns.
Dan Larden, Infectious Media’s Strategic Partnerships Director, said, “Brands need to be careful in making assumptions around the definitions ads.txt has introduced. Many industry players are talking about these terms in a blanket way. Our research shows a more sophisticated approach is needed.
“Blunt implementation of ads.txt on the buy side could damage advertiser campaigns unnecessarily. Advertisers need to be asking their agencies and tech providers for a deeper understanding of the inventory they are buying to ensure the right strategies are in place for each inventory type.”
Infectious Media undertook the research to determine the best way to use ads.txt data to improve client campaign performance. It used proprietary technology to classify auctions based on the ads.txt category. It combined this data with campaign data over a three-week period to test the performance of the seller types.