Case Study Search

How Tinuiti Helped Murad UK Boost New Customers by 125%

The Challenge

People don’t search for skincare the way they used to. Instead of typing “Murad” into Google, buyers are asking much more specific questions, like “Murad cream for dry skin with retinol.” For this reason, old-school marketing setups tied to exact keyword matches no longer move the needle.

Murad needed a smart system that could look past the exact words and understand what the shopper actually meant. The goal? To maximize visibility, relevance, and new customer conversions. Because Murad also had its sights set on new-user growth, the brand’s paid search strategy needed to expand its customer base, not just squeeze more revenue from existing buyers.

AI is a key priority for Unilever Prestige, and for Murad in particular, not only as a tool for automation or efficiency, but as a way to connect with people in more meaningful ways.
— Elisa Orlandi, Brand & Business Director, Murad

Results

+28%

improvement in ROAS during Broad Match and AI Max testing

+98%

YOY ROAS improvement for shoppable Performance Max campaign types

+84%

more conversions in the test cell

+54%

higher conversions YoY

By partnering with Tinuit to rebuild its Google Ad strategy, Murad saw massive, record-breaking growth compared to the previous year. We implemented an AI-first architecture built around Broad Match, AI Max, and New Customer Acquisition bidding to increase revenue, improve efficiency, and transform Murad’s search program into a proactive growth system rather than a reactive, keyword-only tool.

How We Did It

Tinuiti completely rebuilt Murad’s Google Ad strategy to be “AI-first” using three main tools:

Broad Match & AI Max: Instead of guessing every single keyword a customer might type, we let Google’s AI interpret complex searches and automatically show Murad ads to people showing genuine interest.
New Customer Acquisition (NCA) Bidding: We told the AI to specifically hunt for and prioritize people who had never bought from Murad before, helping the brand expand its customer base.
Smart Budgeting (tROAS): Finally, we trained the AI to balance aggressive growth with cost efficiency, ensuring the system didn’t just throw money away but instead targeted shoppers most likely to spend.

Adapting to the New Search Landscape

Instead of relying on strict match-type controls, the team embraced Broad Match, supported by AI Max, to interpret the intent behind complex, long-tail skincare queries and match ads to relevant searches as they emerged.

This approach reflected the reality of evolving search behavior influenced by conversational search and AI Overviews: more informational, nuanced queries that traditional keyword setups struggle to capture. Broad Match cast a wider net than previous Phrase Match configurations, while AI Max applied audience signals and machine learning to decide which impressions to pursue and how to bid, filling gaps in branded coverage and unlocking new pockets of demand.

Testing Broad Match and AI Max in Tandem

To minimize risk and ensure performance, Tinuiti deployed Broad Match and AI Max together across Murad’s non-core branded search campaigns within a rigorous A/B testing framework. Existing setups were tested against the new AI-supported architecture, validating results before any account-wide rollout.

In this dual-layer system:

Broad Match expanded reach beyond legacy match types.
AI Max interpreted intent and dynamically matched ads to complex branded skincare searches using audience signals and machine learning.

By structuring tests across multiple campaigns and reading performance against the legacy setup, Tinuiti ensured the transition was controlled and data-driven. Once results proved out, the Broad Match + AI Max combination became an evergreen tactic, with Murad achieving 100% AI Max adoption outside of core brand campaigns and opting into the full suite of AI Max functions.

Engineering Sustainable New Customer Growth With Performance Max

Alongside search, Murad prioritized expanding its base of new users in 2025. To support this, Tinuiti implemented New Customer Acquisition (NCA) bidding across Performance Max campaigns and paired it with target ROAS (tROAS) to find a “sweet spot” between aggressive acquisition and cost-efficiency.

NCA bidding allowed the account to prioritize users who had not previously purchased from Murad, while tROAS ensured the AI focused on queries and audiences likely to deliver the highest conversion value. Over time, this shifted Performance Max optimization from pure conversion volume toward conversion value, driving 84% more revenue and 54% more conversions year over year, with higher average order values—a sign that the platform was finding more valuable customers, not just more transactions.

All Performance Max campaigns had NCA tactics applied, and together with value-based bidding strategies, Google’s AI was able to optimize with greater freedom, balancing scale and efficiency while aligning with Murad’s strategic objective of sustainable brand growth.

Outcomes

For Murad UK, the work proved that leaning into Google’s AI suite can transform a search account from a reactive, keyword-driven tool into a proactive, intelligent system. The account now interprets evolving customer intent in real time, captures complex branded demand that strict match types would miss, and balances revenue growth, efficiency, and new customer acquisition in a way manual management alone could not technically achieve.

For Tinuiti, the engagement showcased AI Excellence in practice: the courage to fully leverage machine learning, the discipline to test and validate changes through controlled A/B frameworks, and the ability to architect an AI-first structure that treats search and Performance Max as a unified growth engine. The result was more scale, better ROAS, and a materially larger new-customer base—clear evidence that when AI is treated as a strategic lever rather than a plug-in, it can drive lasting business outcomes.