
10M
Users
2M+
Publishers
100B+
Ads annually
Two million publishers leaving revenue on the table without Auto Ads
Auto Ads used ML to place ads and find inventory site owners missed, but most publishers never turned it on. The integration was one snippet, yet it read opaque if you did not ship code daily. Manual placements stayed familiar; the ML path sounded like a black box. Automated monetisation only paid off after setup finished; competitors were ready to capture anyone who quit halfway.
Segmented email: explain the product, paste the tag, verify reporting
We used email to close the gap: segmented sends so each publisher saw copy that matched where they were stuck: first what Auto Ads actually did, then how to paste the tag, then what to check in reporting. Side-by-side examples showed ML placements next to manual ones; follow-up messages walked through the code with screenshots. Publisher stories with real revenue lifts went out as proof, and deeper mails covered mobile anchor ads, AMP, and cross-device setups for people ready for more.
Higher completion, fewer tickets, more inventory surfaced by ML
Completion rates went up once the emails explained Auto Ads in plain steps, and support tickets dropped. More publishers switched Auto Ads on, so Google's models could surface inventory that manual setups skipped.
Publishers spent less time babysitting placements and more time on their sites; AdSense kept category leadership because adoption finally matched product depth.
“I am not a developer. I used to quit halfway through documentation that only makes sense if you already ship code, so earning stayed out of reach. Short steps, plain English, emails when I stalled, and I went from stuck to earning in days, not lost weekends trying to read manuals I could not follow.”
Choose the right plan for your team.