Normalized claim
Quantified impact: 13% increase
Increased conversions by 13%.
Last evidence check: Jun 1, 2026
Blue Zinc Media scales PPC success through automated portfolio bidding
Use case typePricing optimizationUpdated Jun 13, 2026
Blue Zinc Media, a UK-based digital marketing and lead generation agency, faced the challenge of efficiently managing massive pay-per-click (PPC) advertising accounts with a small team. Their objective was to meet strict cost-per-acquisition (CPA) targets across millions of keywords while maintaining the flexibility and performance clients demand. By partnering with Microsoft Advertising, Blue Zinc Media implemented an advanced Portfolio Bidding solution, enabling fully automated bid management. They relinquished manual controls and restrictions, granting the machine-learning-driven system unrestricted access for dynamic, outcome-based optimization. The result was a measurable increase in conversions (up 13%), maintained CPA within target, and successful scalability of the model for additional accounts, helping deliver sales growth for their clients.
- Organization
- Blue Zinc Media
- Industry
- Professional Services
- Location
- United Kingdom
- Published
- March 2025
Reported outcomes
+13%
quantified impactRevenue & growth
Strategic outcomes
Speed & agilityFully automated bid managementScale & capacityManaged more accounts effectivelyInnovation & cultureReplicated automation for other campaignsCustomer experience & trustDelivered more sales for clients
Catalog median for revenue & growth deployments: +40% across 68 reported metrics. Compare benchmarks →
Why do we believe this?Outcome claims, sources, and evidence checks
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Blue Zinc Media
- Provider
- Microsoft
- Maturity
- Unknown
- Linked source
- Microsoft Advertising
No explicit deployment-stage evidence found.
Customer identity supportedSource describes one deploymentMaturity evidence evaluated
Primary read
Use case focus
Showing 2 of 2
- 1Automated Portfolio Bidding for PPC Campaigns
- 2Machine-Learning Optimized Ad Spend Allocation
- Oversized PPC accounts with millions of keywords overwhelmed a lean team.
- Need to hit demanding CPA targets month over month.
- Manual bid management was time-consuming and hard to scale.
- Flexibility was required for bespoke client needs, but manual controls created bottlenecks.
- Adopted Microsoft Advertising's Portfolio Bidding automation.
- Removed manual bid adjustments, negative keywords, and site exclusions to fully leverage automation.
- Capacity for dynamic machine-learning optimization of bids across massive search inventories.
- Duplicated successful automation strategies for other client campaigns.
Technologies
- Increased conversions by 13%.
- Cost per acquisition was consistently maintained within target.
- Boosted scalability so the team could manage more accounts effectively.
- Enabled strategy replication for other client campaigns leading to more sales.
Sources & evidence1
Evidence: Medium60/100Evidence strength
- Customer explicitly identified
- Primary source available
- Quantified outcome available
- Technical implementation details available
- Recent evidence check available
- Last evidence check: Jun 1, 2026.
Live sourceStill referenced
The case's original source is still reachable.
- Cited source last checked Jun 1, 2026 — ok (0/1 broken).
Measures whether this deployment's public evidence persists — not whether the system is still in production.
Type: Case StudyPublished: Mar 5, 2025Publisher: Microsoft AdvertisingEvidence: PrimaryConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
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