Floor pricing, partner weighting, layout, and refresh — all tuned per impression by models that learn from your traffic. Here's what changed when publishers turned it on.
○ Before · manual ad opsjan–mar
Static floors. Wrong partners. Same layout for everyone.
$2.40 rpm
flat 12-week baseline · industry median
● After · ai optimization onapr–jun
Dynamic floors. Bidder weights tuned hourly. Layout per audience.
$5.93 rpm
+147% · sustained · same inventory
The full lift
Every metric, moved the right way.
Avg CPM
$2.40
$5.93↑
vs baseline+147%
Viewability
61%
94%
vs baseline+33pp
Auction win rate
38%
71%
vs baseline+87%
Time on page
1:42
2:28 ↑
vs baseline+45%
Inside the pipeline
Four models. One impression at a time.
Each model is independently auditable. Nothing is a black box — you see the decision, the inputs, and the lift.
01 · floor model
Predicts the highest floor each bidder will clear.
Trains on 90 days of bid responses. Updates every 15 min.
02 · partner weighting
Tunes which SSPs see which inventory.
Routes your premium slots to the partners that pay for them.
03 · layout policy
Picks ad density per session.
Balances revenue against bounce — different for first-time vs return.
04 · refresh timing
Knows when to refresh, when to wait.
No fixed interval. Triggers on viewability + engagement signals.
Case · independent news network
We turned it on a Tuesday. By Friday RPM was up 2.4×. Nothing else changed on our side.
M. Rosales
Head of Programmatic · La Calle Media
Daily RPM · 12 weeks
$2.41 → $5.96
+147% sustained
0 layout changes
Live optimization · last 60s
Your dashboard, after Tuesday.
Live7d30dYTD
Avg CPM · last hour
$5.93
↑ +$0.21 vs prev hr
Win rate
71.2%
↑ +1.4pp last 12h
Viewability
94%
↑ stable · 14d
Decisions / sec
847
↑ +12% vs forecast
Realtime CPM14d avgBaseline
Signals the model watches14 ranked by impact
Every decision weighted, ranked, audited.
The model isn't a black box. Each signal contributes a measurable share of the lift — and you can see it.
Historical bid response curves
+$1.41
Audience cluster recency
+$0.78
Slot viewability percentile
+$0.62
Time-of-day demand pattern
+$0.55
Geo × device pair
+$0.48
Page topic vector
+$0.41
Scroll velocity / dwell
+$0.34
Inventory freshness
+$0.28
Partner latency drift
+$0.22
Refresh fatigue model
+$0.17
From the teams who flipped the switch3 of 500+ teams
Results, without the rituals.
+2.4× RPM
My ad ops team used to spend Tuesdays tuning floors. They don't anymore. The dashboard does it every 15 minutes.
M. Rosales
Head of Programmatic · La Calle
+87% Win Rate
Partner weighting was always guesswork. Now the model picks per impression. I cannot un-see this.
L. Karim
Director of Yield · Argo Daily
+33pp Viewability
We didn't change a single line of layout code. The refresh model figured out when to reload and when to wait.
S. Chen
Eng Lead · Tideway Network
Honest answers06 tough questions
What people actually want to know.
Will it work on day one?+
Yes, but it gets better. The models reach steady-state lift in 7–14 days as they learn your traffic.
What if it makes a bad call?+
Every decision is logged, reversible, and bounded by safety rails (floors, density caps). Override per slot.
Is this auto-bidding? Won't Google penalize it?+
No — it's yield optimization (publisher-side). Independent of any DSP bidding strategy.
Can I audit the model?+
We publish per-decision logs and model cards every month. Open one in the dashboard.
What about ad density compliance?+
Hard-coded constraint. The model can't violate density rules, only optimize within them.
Cancel any time?+
Month-to-month. If it stops working for you we send you the partner relationships and a goodbye email.
AI yield optimization uses machine-learning models to set the best floor price, ad refresh timing, and viewability target for each ad unit in real time — replacing static floors and manually written rules.
How does WeForAds set floor prices?
WeForAds' models analyze billions of real-time bid signals to compute the optimal floor for every impression, automatically and around the clock, with no manual rule-writing.
How much more revenue can AI optimization deliver?
By pricing each impression correctly and reducing under-selling, publishers see higher RPMs. Across the full WeForAds stack, publishers average roughly 3× ad revenue within 90 days.
Do I need to configure or maintain anything?
No. Optimization runs automatically per ad unit — there are no floors, rules, or schedules for you to manage.
Does it optimize more than floor prices?
Yes. Beyond floors, the system tunes ad refresh intervals and viewability to balance revenue with page performance and user experience.
Is AI optimization privacy-compliant?
Yes. It relies on aggregated, real-time bidding signals and operates within GDPR and IAB consent frameworks through your CMP.