How BIURO Built a Scalable Job Ad Publishing System and reduced ad setup time by 85%

The Challenge: Fast-Growing Recruitment Team, No System Built for Scale

BIURO is a fast-growing recruitment business advertising 10 to 15 job roles per day across multiple locations in the Baltic States. For them, job ads aren’t marketing experiments. They’re operational infrastructure.

Speed, accuracy, and consistency directly affect hiring outcomes.

As volume increased, BIURO hit a familiar ceiling: manual execution became the limiting factor.

The Reality Before Automation

BIURO already had partial automation in place. It helped, but it didn’t scale.

Before the new system:

• Job ads were around 50% manual

• Ads were built directly inside Meta Ads Manager

• Copy was partially automated

• Creatives were not

Even with templates, the process still required manual Canva updates, creative versioning, asset uploads, and repeated cross-checking of job details.

At BIURO’s volume, this added up fast.

Meta Ads Manager itself was a major bottleneck.

When running dozens of campaigns across multiple locations, a significant amount of time was lost simply:

• Loading campaigns and ad sets

• Switching between accounts, campaigns, and locations

• Waiting for changes to save or publish

• Re-checking targeting, budgets, and creatives for each variation

Even when the team knew exactly what to do, being inside Ads Manager for hours every week was unavoidable.

The numbers:

• 10 to 15 job ads per day

• 70 to 95 ads per week

• Around 30 minutes per ad

That meant roughly 30 hours per week or 120 hours per month, with two team members tied up in repetitive execution.

Scaling further would have required hiring more people just to keep ads live. In recruitment, that creates a real problem. When ads are delayed, hiring slows down. When hiring slows down, everything else follows.

The Real Constraint

This wasn’t a creativity problem. It wasn’t a budget problem either.

Once BIURO reached this volume, incremental improvements to individual ads stopped mattering. The real challenge became executing reliably at scale.

As volume increased, the process relied on too many tools, too many handoffs, and too much manual checking. Small inefficiencies compounded, and consistency became harder to maintain.

The Setback: Engineering for Risk at Scale

This was not a plug-and-play rollout.

High-volume publishing leaves very little room for error. Small mismatches that are tolerable at low volume become serious problems at scale.

Early versions of the system surfaced exactly the issues that needed to be resolved before going live: keeping ad copy aligned with live job listings, maintaining precise location accuracy across regions, and accounting for differences between Meta previews and live ad behaviour.

At the time, ad creative generation required particular care. Image models were improving quickly, but production-grade reliability wasn’t guaranteed yet. Prompting alone wasn’t enough to consistently produce realistic, recruitment-safe creatives across roles and locations without edge cases.

Because of that, the system was intentionally run in a non-publishing mode.

Ads were generated, reviewed, and refined without being activated. Outputs were checked directly inside Meta, creative prompts were iterated and constrained, and guardrails were added wherever inconsistencies appeared. The goal wasn’t novelty. The goal was predictability and safety at volume.

Live publishing was enabled only once accuracy, consistency, and creative reliability were proven.

That risk-controlled rollout is why the system now runs reliably at high volume without constant human checking.

The Solution: An Internal Ad Publishing System

We didn’t build “automation”. We built infrastructure.

The goal was deliberate: one control surface, one review step, one action to publish. No jumping between tools. No fragile workflows. No hidden manual work.

System Architecture at a Glance

Source

• BIURO’s website job listings

Control Layer

• Google Sheets acting as an internal ad publishing console

• Custom buttons, menus, and functions

• Clear status tracking and approvals

Why Google Sheets

Google Sheets was chosen deliberately as the control layer. The BIURO team already used it daily, which meant zero training, zero adoption friction, and no additional tooling costs.

Beyond simple data entry, Sheets supports custom menus, buttons, and scripted logic, allowing it to function as a lightweight internal publishing console. It provided a clear, readable, and reliable interface for approvals and control, without introducing another system to manage.

Logic Layer

• Validation rules for salary, role, and location

• Structured ad templates

• Budget caps to prevent overspend

Execution Layer

• Python-based Meta Ads API publishing

• Pre-configured campaign and ad structure

This allowed BIURO to manage high-volume ads from a single interface their team already knew and used daily.

How the System Works End-to-End

1. Website Scanning

The system scans BIURO’s website for new job listings. Scraping was used initially to remove dependency on API access and speed up deployment, while keeping the system architecture ready for direct API integration later.

2. Data Extraction

Each job is pulled into a central Google Sheet with all key details: job title, location, salary, and job link.

3. Ad Generation

Ad copy is generated automatically using structured prompts. Creatives are generated automatically using refined, role-safe prompts that were stress-tested across multiple roles and locations. Location-specific messaging is applied, and salary and role details are validated before anything moves forward.

4. Structure and Safeguards

Correct locations are applied automatically, budgets are set with hard caps to prevent overspend, and the Meta ad structure is pre-configured so nothing is left to chance.

5. Centralised Review

Everything appears in one Google Sheet: copy, creative preview, and status. There’s no need to open Ads Manager for setup, no Canva edits, and no tool switching. 

6. Publishing

Once approved, ads are published via the Meta API.

Guardrails That Made It Reliable

To run safely at scale, the system includes salary validation to prevent incorrect figures, precise location matching across copy and creative, budget limits to avoid overspend, and iterated prompts that produce consistent, compliant outputs every time.

This removed the need for constant human checking, rework, and second-guessing.

The Results

Time Savings

Before

• Around 30 hours per week

• Around 120 hours per month

After

• 3 to 5 hours per week

• 12 to 20 hours per month

Result: 85 to 90% reduction in ad setup time

Speed

Before: Around 30 minutes per job ad
After: Around 5 minutes per job ad

Ads that used to sit in a queue now go live the same day, often within minutes of being approved.

Team Impact

Two team members were freed from repetitive execution work. One person can now oversee the entire ad operation and focus on higher-value strategic work instead.

Error Reduction

The system dramatically reduced manual mistakes, cut down on back-and-forth communication, and ensured consistent messaging across all locations.

What This Unlocked for BIURO

This system wasn’t built just to save time. It changed how BIURO operates:

• High-volume hiring no longer creates internal bottlenecks. 

• New locations can be added without rebuilding workflows from scratch. 

• Growth is no longer tied to headcount in the marketing team. 

• Marketing execution stopped being a constraint on hiring and operations.

The same system is now rolling out in Latvia and Estonia without needing to rebuild anything from the ground up.

Client Feedback

“The results exceeded our expectations. What used to be a complex, manual process inside Ads Manager has been replaced with a well-structured, reliable system. Job ads now go live quickly and accurately, all from one clear interface. The real value is the consistency and confidence it brings. Everything runs smoothly, and it’s impressive how much this has simplified our daily work. We are truly grateful to the AI Formula team for making this shift possible.”
– Eglė Zajankauskaitė, Marketing Project Manager

Who This Type of System Is For

This works best for organisations that run high-volume ads, operate across multiple locations, depend on speed and consistency, and want to scale without hiring more execution staff.

Recruitment, real estate, franchises, marketplaces, and similar models where repetition slows growth will see the most immediate impact.

Want Something Like This?

If your team is rebuilding the same ads every day, switching between tools to launch simple campaigns, or hiring people to handle work that should already be systemised, you already know the hidden cost.

We help growing businesses replace manual marketing workflows with systems that publish faster, scale cleanly, and stay reliable at volume.

If this sounds familiar, a short call is usually enough to see whether a system like this makes sense for your business.