A Case Study on Reallocating Budget from Brand to Non-Brand Search

Many eCommerce brands assume rising CPCs and competition are the main reasons their PPC programs stop scaling.

In reality, the biggest issue we often see is poor campaign structure and inefficient budget allocation.

At 9 Digital Media, we recently analyzed several large PPC accounts and discovered a common pattern:
brands were overspending on branded search while underinvesting in non-brand acquisition campaigns.

Using a suite of AI tools, we rebuilt the campaign structures and reallocated budgets.

The result: significant revenue growth with minimal or even lower total spend.

The Problem

Across multiple accounts we analyzed, the issues were very similar:

Campaign structures built years earlier
Brand and Non-Brand campaigns blended together
Overlapping keywords competing internally
Limited negative keyword strategies
Weak keyword clustering
Shopping feeds lacking keyword coverage
Budget allocations driven by habit rather than performance

In short, accounts were optimized for maintenance, not growth.

The AI-Driven Optimization Framework

To address this, we used approximately 10 AI-driven analysis tools and automation frameworks to rebuild the search programs.

These tools helped us:

1. Reorganize campaign structures

AI clustering models reorganized campaigns into cleaner brand vs non-brand frameworks.

AI models detected internal bidding conflicts across campaigns.

3. Build theme-based keyword clusters

Machine learning grouped keywords into tight thematic clusters, improving:

Quality scores
Ad relevance
Landing page alignment

4. Advanced Search Query Report analysis

AI models processed massive SQR datasets to identify:

profitable keyword clusters
irrelevant query patterns

This allowed us to expand profitable themes and aggressively negate poor queries.

5. Improve keyword coverage

AI tools analyzed missing keyword gaps across campaigns and product categories.

6. Build stronger negative keyword frameworks

AI discovered irrelevant search patterns that human analysts often miss.

7. Optimize ad copy to landing pages

Natural language models analyzed landing pages and created more relevant ad copy variations.

8. Analyze Google Merchant Center feeds

AI models evaluated:

SKU coverage
keyword gaps in product titles
product attribute optimization

9. Analyze historical seasonality

AI examined historical data to predict high-opportunity keyword clusters for upcoming seasonal campaigns.

10. Identify budget inefficiencies

Finally, AI models analyzed spend allocation across campaign types and identified where additional budget would produce incremental revenue.

The Strategic Change

The biggest insight from the AI analysis:

Brand campaigns were consuming too much budget while producing limited incremental growth.

So we reallocated budgets to non-brand acquisition campaigns to drive more customer acquisiton.

Remember that most Branded search spend is for demand capture and not demand generation!

Results Across Four Accounts

Client 1

Category	Spend Change	Revenue Change
Brand	-41%	-6%
Non-Brand	+132%	+312%
Total	+5%	+19%

Despite cutting brand spend significantly, total revenue grew nearly 20%.

Client 2

Category	Spend Change	Revenue Change
Brand	-30%	-8%
Non-Brand	+167%	+589%
Total	+17%	+15%

Non-brand campaigns scaled dramatically while overall spend increased only modestly.

Client 3

Category	Spend Change	Revenue Change
Brand	-49%	-5%
Non-Brand	+107%	+308%
Total	-3%	+30%

Total spend actually decreased, yet revenue increased 30%.

Client 4

Category	Spend Change	Revenue Change
Brand	-46%	-10%
Non-Brand	+128%	+304%
Total	-2%	+20%

Again, flat spend but significant revenue growth.

The Real Lesson

Most PPC accounts do not suffer from “competitors”

They suffer from inefficient allocation and outdated structures.

AI allows marketers to analyze millions of data points quickly and uncover opportunities that manual analysis often misses.

Final Thought

When properly implemented, AI in PPC is not about replacing marketers.

It is about empowering them to see patterns faster, restructure campaigns smarter, and invest budgets where incremental growth actually exists.

How AI Transformed PPC Performance in 2025