Case Study

    Google Ads Ecommerce Growth Case Study

    How we scaled two websites using Shopping, Performance Max, and tighter intent control

    Client Overview

    Client Type

    Ecommerce Retailer

    (2 websites)

    Industry

    Multi-brand Retail

    Markets

    UK

    Platform

    Google Ads

    The client operates two ecommerce websites selling branded products. Prior to working together, both accounts were limited by tracking inaccuracies, wasted spend, and under-utilised Shopping and Performance Max campaigns.

    The Problems (Before)

    1

    Inaccurate or incomplete conversion tracking

    2

    Poor visibility on true ROAS and performance

    3

    Spend wasted on low-intent and generic search terms

    4

    Best-selling brands not prioritised correctly

    5

    Shopping and Performance Max under-utilised or mis-structured

    6

    Brand and model-specific searches not fully captured

    What We Changed

    Every change was made with profitability and scale in mind.

    Fixed Tracking

    Google Ads + GA4 tracking rebuilt to ensure accurate revenue attribution

    Shopping Restructure

    Rebuilt Shopping campaigns around best-selling brands

    Performance Max Launch

    Introduced Performance Max to scale proven products

    Intent Prioritisation

    Prioritised brand + model specific search terms

    Waste Reduction

    Cut irrelevant queries, tightened match types, improved negative keyword coverage

    Budget Optimisation

    Shifted budget toward highest-intent traffic only

    Results — Website 1

    Website 1 Google Ads performance growth chart showing conversion and revenue uplift

    Consistent growth driven by improved tracking, Shopping, and Performance Max optimisation.

    Strong uplift in conversions over time

    Clear improvement once Shopping + PMax were introduced

    Reduced volatility after removing wasted spend

    Better performance consistency month-on-month

    Results — Website 2

    Website 2 Google Ads performance growth chart showing rapid scaling

    Rapid scale achieved once high-intent structure and product focus were implemented.

    Significant increase in conversion volume

    Budget scaled only once profitable

    Best-selling products prioritised

    Brand and model searches captured efficiently

    Client data anonymised. Results shown are real but shared responsibly.

    Key Takeaways

    Fixing tracking unlocks better decisions

    Shopping + Performance Max work best when structured properly

    Brand and model-specific searches drive the highest intent

    Cutting waste is just as important as scaling spend

    Focused optimisation beats broad "set and forget" strategies

    This Approach Works Best For

    Is this the right fit for your business?

    Ecommerce brands with multiple products or brands

    Stores struggling with ROAS inconsistency

    Businesses wasting spend on low-intent traffic

    Brands ready to scale once profitability is proven

    Want Similar Results for Your Account?

    Get a free Google Ads audit and see where your account is leaking spend or missing opportunities.

    Frequently Asked Questions

    Can you share exact numbers?

    We keep specific revenue and spend figures confidential to respect client privacy. The charts shown represent real performance data with the exact numbers anonymised. What matters most is the trajectory — both accounts saw significant, sustained growth after our optimisation work.

    Do you work with ecommerce brands like this?

    Absolutely. Ecommerce is one of our core specialisms. We work with online retailers across various industries, from fashion and homeware to specialist B2B suppliers. If you're running Shopping, Performance Max, or Search campaigns, we can help.

    How long did results take?

    Initial improvements were visible within the first month after fixing tracking and restructuring campaigns. The major scaling you see in the charts happened over 3-6 months as we continuously optimised and reinvested into what was working.