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Client

Magazon

Industry

Marketplace

Services

Google Ads

Tools

Text 5

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Overview

From Broad Advertising Activity to a More Selective Acquisition System

CabinetSet needed to increase sales-related conversion volume without allowing acquisition costs to rise at the same pace.

The account covered a large national market, an extensive product catalog, and several sources of customer demand. The main opportunity was not simply to buy more traffic. It was to concentrate advertising investment around the locations, products, audiences, and conversion signals with the strongest commercial potential.

Advantrise rebuilt the paid media structure across Google Ads and Meta Ads, introduced more selective targeting and product priorities, and connected advertising platforms with downstream sales feedback.

The objective
Generate more commercially meaningful conversions while improving acquisition efficiency.


Market selectivity


Direct more budget toward locations with stronger purchasing and delivery potential.


Product focus


Prioritize cabinet models and product groups with stronger demand potential.


Better conversion feedback


Help advertising platforms learn from stronger sales outcomes rather than raw activity alone.

Why Broad Targeting Limited Efficient Growth

CabinetSet’s commercial potential was not distributed evenly across its markets, products, and incoming traffic.

A broad account structure could generate activity, but it gave the platforms limited guidance about where additional budget was most likely to produce a viable sale. At the same time, irrelevant searches, weaker markets, and low-value conversion activity could consume budget or distort optimization.

Market constraint


Uneven Geographic Potential


Purchasing power and delivery practicality differed between locations. A uniform national approach could not reflect those differences.

Product constraint


Different Demand by Product


Not every cabinet model or product group deserved equal campaign exposure and budget priority.

Measurement constraint


Noisy Optimization Signals


Spam, low-value activity, and incomplete downstream feedback could prevent campaigns from learning from the strongest commercial outcomes.


The central problem:

the account needed to distinguish stronger commercial demand from activity that was unlikely to become a viable sale.

A Four-Part Strategy for More Selective Growth

The strategy centered on giving the advertising platforms clearer signals about where commercial potential was strongest.

Market value, product demand, search intent, audience relevance, and sales feedback were treated as connected parts of the same acquisition system. This allowed campaign decisions to focus on the combinations most likely to produce a meaningful conversion.


Market priority


Separate Markets by Commercial Potential


Give stronger locations clearer bidding and budget priorities while deprioritizing areas with weaker purchasing or delivery economics.


Product priority


Focus on Higher-Potential Products


Concentrate exposure around cabinet models and product groups with stronger demand instead of distributing visibility evenly.


Demand quality


Reduce Irrelevant Search Activity


Protect budget with tighter search-term control and a continuously refined negative keyword system.


Sales feedback


Return Stronger Outcomes to the Platforms


Connect the client’s sales review process with offline conversion imports so campaign learning reflects downstream value.

How the Paid Media System Was Rebuilt

The strategy was implemented through several connected workstreams. Each one addressed a different source of wasted spend or weak campaign learning.

Performance Max


Rebuilt Automation Around Commercial Priorities


Performance Max campaigns were reorganized around stronger product groups, audience signals, and geographic priorities. This gave automation a more useful framework for deciding where to find additional conversions.

Geography


Managed Markets by Business Value


Higher-potential and lower-potential locations were separated so budget and bidding decisions could reflect differences in purchasing power, demand, and delivery practicality.

Product mix


Prioritized Stronger Products and Models


Campaign exposure was concentrated around cabinet lines with greater demand potential. Product priorities were evaluated together with market conditions rather than as isolated catalog decisions.

Traffic quality


Refined Audiences and Search-Term Control


Audience signals were developed to support stronger campaign learning. A large negative keyword library reduced exposure to irrelevant, weak-intent, and commercially unsuitable searches.

Paid social


Added Meta as a Complementary Demand Channel


Meta Ads expanded reach beyond existing search demand and generated an additional source of sales-related conversion activity.

Optimization feedback


Connected Advertising With Sales Outcomes


Offline conversion tracking helped return stronger downstream outcomes to the advertising platforms after they were reviewed by CabinetSet’s sales team.

Channel roles
Google Ads captured and scaled active demand. Meta Ads added incremental reach and another source of conversion activity.
Conversion Feedback

Connecting Advertising With Offline Sales Outcomes

Front-end conversion activity did not provide enough context for long-term optimization.

CabinetSet’s manager reviewed incoming opportunities in HubSpot. Advantrise configured the tracking connection needed to return relevant downstream outcomes to the advertising platforms.


01


Paid Interaction


A potential customer engages with a Google or Meta campaign.


02


Commercial Conversion


The customer completes an action connected with the sales process.


03


CabinetSet Sales Review


The client’s manager reviews and classifies the opportunity in HubSpot.


04


Offline Outcome Import


Relevant downstream outcomes return to the advertising platforms.


Responsibility remained clear:

CabinetSet’s team handled sales review and qualification; Advantrise configured the tracking and feedback connection.

Measurement

How the Public Comparison Was Built

Google Ads was used as the primary source for the before-and-after comparison. The public conversion metric consolidates CabinetSet’s commercially meaningful sales outcomes under one reporting definition.

Monthly averages were used so reporting windows of different lengths remained comparable. Secondary engagement activity was excluded from the reported conversion total.

Exact spend, revenue, order volume, and internal campaign details remain confidential. Percentage changes and indexed values communicate the direction and scale of the improvement without disclosing those figures.

Source


Google Ads

Comparison


Baseline vs. peak monthly average

Conversion Scope


Commercially meaningful outcomes

Public Format


Percentage and indexed results

What the Rebuilt System Changed

The account moved from broad advertising activity toward a system organized around relative commercial value.

Geographic segmentation created clearer control over where advertising investment was directed. Product prioritization concentrated exposure around stronger opportunities. Search-term exclusions reduced weak demand, while offline conversion imports gave the platforms more useful downstream feedback.


More Selective Budget Use


Market decisions reflected purchasing potential and delivery practicality instead of uniform national coverage.


Stronger Product Focus


Campaigns concentrated more exposure around products and models with greater demand potential.


Better Platform Learning


Campaign optimization could use downstream outcomes reviewed by CabinetSet’s own sales team.

The result was a more scalable acquisition system: higher conversion volume, a stronger conversion rate, and a lower average cost per conversion.

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