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Automation Layer

Custom automations running inside every account.

The automation layer we build for every client paid-search account — custom bidding rules, anomaly detection, feed routing, and reporting that runs 24/7 without waiting for a human to notice.

80+
Awards
14
Markets
16+
Years
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Automation Architecture

From triggers to actions.

Bid Change
real-time
Budget Alert
threshold
QS Drop
monitor
CPA Spike
anomaly
New Terms
discovery
Script Engine
ads-scripts
live
$ omnicliq gads --deploy
[feed] Campaigns synced ✓ 340 active
[bid] Strategies applied ✓ tCPA set
[track] Conversions active ✓ 99.8% acc
✓ Pipeline complete
0
Scripts
0
Saved/mo
0
↓ CPA
Adjust Bids
auto
Pause Ads
rule-based
Reallocate $
pacing
Add Negatives
mining
Send Alert
Slack/email

Automation that beats the default.

Every paid-search account we run has a layer of custom automations sitting on top of the platform's own automated bidding. The purpose is specific: feed signals into bidding that the platform's algorithm cannot see on its own, enforce business rules the platform defaults would otherwise ignore, and react to performance shifts faster than a human analyst could manually.

The automations cover the operational edges: bid adjustments driven by customer LTV, stock level, or margin data pulled from the BI layer. Budget pacing across campaigns and categories. Negative-keyword mining from query reports. Anomaly detection that flags sudden cost or conversion changes before they blow the monthly budget. Feed rules that route products into the right campaign structures based on product economics, not SKU count.

These are not black-box scripts. Every automation is documented, version-controlled, and deployable against new client accounts in a fraction of the time a custom build from scratch would take. The accumulated library is the reason accounts reach award-tier performance faster than a single engagement would normally allow.

What makes the difference.

01

LTV-Aware Bidding

Bidding modifications driven by first-party LTV signals from the BI layer. The platform's bidding algorithm gets signal that reflects customer value, not just conversion volume.

02

Anomaly Detection

Automated monitoring of campaign-level cost, conversion, impression share, and quality score movements. Alerts triggered before a drift becomes a budget incident.

03

Budget Pacing

Automations that pace budget across campaigns, categories, and markets against the monthly and quarterly targets. Flight-day math done by the automation, not by a spreadsheet that breaks when somebody forgets to update it.

04

Feed Routing

Product feeds routed into campaign structures automatically based on product economics — margin tier, price band, stock level, seasonality — not based on static SKU classification.

05

Query Mining

Automated query report analysis for negative-keyword opportunities and category expansion. Scale that is impossible to sustain manually across accounts running tens of thousands of queries per day.

06

Reporting Automation

Client and internal reporting automations that pull from the BI layer and produce the weekly and monthly deliverables without a human assembling them each time.

Deploying the automations.

01

Discovery

Account audit to identify where manual work is currently producing the most value — and where automation would match or exceed the human-driven outcome with better consistency.

02

Configure

Automations configured from our existing library where applicable. Custom automations built where the account's business logic or commercial rules require specific handling.

03

Deploy

Automations deployed into the account with audit logging enabled. Initial output reviewed daily, then weekly, then monthly as confidence is established.

04

Evolve

Automations evolve as the account grows and new patterns emerge. The library grows too — and every new automation we build becomes available to the rest of the portfolio.

Politikos Shop — flagship fashion department store

Politikos Shop.

+231%
Revenue
+225%
Transactions
+230%
Ad Spend
2
New Markets
Read full case study

Common questions.

Most repetitive work: bid adjustments, budget pacing, negative-keyword mining, anomaly detection, quality-score monitoring, reporting assembly, feed routing, and the business-rule enforcement work that otherwise sits in a spreadsheet somebody forgets to update. If it is repetitive and rule-based, it is a candidate for automation.
Yes. Automations run with full audit logging, scoped permissions, and pause controls. Nothing happens silently — every automation action is recorded and reviewable. Human-in-the-loop approval is enabled for any automation that can materially move spend until confidence in the rules is established.
No. The automations run inside your account and we handle the implementation, maintenance, and iteration. Our client-facing reporting surfaces what the automations are doing without requiring anybody on your side to read code.
Library automations can be live within the first 1-2 weeks of an engagement. Custom automations specific to your business rules typically take 2-4 weeks depending on complexity. The account does not wait 6 months to benefit from the automation layer.
Yes — our automations are designed to complement platform-native automated bidding, not replace it. The platform's bidding algorithm handles the moment-to-moment bid decisions; our automations feed it better signal, enforce the business constraints it cannot see, and react to situations it is not equipped to detect.

Ready to run the account with automation?

Let's talk about the automation layer we deploy against every paid-search account — and the library behind it.

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